diff --git a/module2/exo1/toy_notebook_en.ipynb b/module2/exo1/toy_notebook_en.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..47d1ded714316a9aebcee187d316d255880c9d30 100644
--- a/module2/exo1/toy_notebook_en.ipynb
+++ b/module2/exo1/toy_notebook_en.ipynb
@@ -1,5 +1,109 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3.141592653589793\n"
+     ]
+    }
+   ],
+   "source": [
+    "from math import *\n",
+    "print(pi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.128911138923655"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "np.random.seed(seed=42)\n",
+    "N = 10000\n",
+    "x = np.random.uniform(size=N, low=0, high=1)\n",
+    "theta = np.random.uniform(size=N, low=0, high=pi/2)\n",
+    "2/(sum((x+np.sin(theta))>1)/N)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "np.random.seed(seed=42)\n",
+    "N = 1000\n",
+    "x = np.random.uniform(size=N, low=0, high=1)\n",
+    "y = np.random.uniform(size=N, low=0, high=1)\n",
+    "accept = (x*x+y*y) <= 1\n",
+    "reject = np.logical_not(accept)\n",
+    "fig, ax = plt.subplots(1)\n",
+    "ax.scatter(x[accept], y[accept], c='b', alpha=0.2, edgecolor=None)\n",
+    "ax.scatter(x[reject], y[reject], c='r', alpha=0.2, edgecolor=None)\n",
+    "ax.set_aspect('equal')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.112"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "4*np.mean(accept)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +120,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module2/exo2/exercice.ipynb b/module2/exo2/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..2b953641d72573e7cf60bfe1f6cdbe4dd0c32d92 100644
--- a/module2/exo2/exercice.ipynb
+++ b/module2/exo2/exercice.ipynb
@@ -1,5 +1,211 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9, 12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "DataSet = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n",
+    "print(DataSet)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The average of DataSet is 14.11\n"
+     ]
+    }
+   ],
+   "source": [
+    "# average\n",
+    "\n",
+    "def averageOfList(num):\n",
+    "    sumOfNumbers = 0\n",
+    "    for t in num:\n",
+    "        sumOfNumbers = sumOfNumbers + t\n",
+    "\n",
+    "    avg = sumOfNumbers / len(num)\n",
+    "    return avg\n",
+    "\n",
+    "\n",
+    "print(\"The average of DataSet is \" '%.2f' %averageOfList(DataSet))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2.8"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# minimum\n",
+    "\n",
+    "min(DataSet)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "23.4"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# maximum\n",
+    "\n",
+    "max(DataSet)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14.5"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# median\n",
+    "\n",
+    "import statistics\n",
+    "statistics.median(DataSet)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "standard deviation is 4.31\n"
+     ]
+    }
+   ],
+   "source": [
+    "# standard deviation\n",
+    "\n",
+    "print(\"standard deviation is \" '%.2f' %np.std(DataSet)) \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Standard Deviation: 4.31\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "dataset=[14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n",
+    "print('Standard Deviation:', '%.2f' %np.std(dataset))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAEICAYAAABPgw/pAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAADkdJREFUeJzt3X+M5HV9x/Hnq6CkBbRHbyGgnFuRNNAaD3MFGhoLVSw/0gAh2lKlV0NzaCHR1MZcrKnUaoJ/qKRpQ3sGeqcCDYkgNGALRSzYUMpBCRxFw48eAne9O4otP6xV4N0/5nvtuOzuzO7M7ex97vlILjPfHzPfz32Ze+6Xz87spqqQJO39fmLSA5AkjYdBl6RGGHRJaoRBl6RGGHRJaoRBl6RGGHTttZJsTPLpeba/kOTNSzkmaZIMupZEkq1Jfphk5Yz19yepJNPjPmZVHVRVjw8Y18lJnhr3saVJMOhaSv8GnLd7IclbgZ+c3HD2vCT7TXoM2ncYdC2lLwO/3be8FvjS7oUkv5hkR5L9+9adm+T+eZ5zRZKbkjyf5O4kR/U9tpK8pbt/RpJ/7fZ7OskfJDkQ+DpwRDc980KSI5IckOSyJNu6P5clOaDveT+WZHu37XdnHGdjksuT3JzkReCUJGcm+ZckzyV5Msklfc813T3+A9227yX5YHcuHkjyn0n+bLEnXPsWg66l9E/A65Ic0125/gbwld0bq+oe4D+AU/se8356Xwjmch7wx8AK4FHgM3PsdwVwYVUdDPwC8I2qehE4HdjWTc8cVFXbgD8ETgRWA28Djgc+AZDkNOD3gXcBbwF+ZZZj/VY3joOBbwEv0vtC9tPAmcCHkpw94zEnAEd35+SybgzvAn4eeG+S2Y4j/RiDrqW2+yr9VODbwNMztm+iF3GSHAL8GnD1PM93XVX9c1W9BFxFL8Kz+RFwbJLXVdX3quq+eZ7zfcCnqmpnVe2i9wXj/G7be4G/qqqHqur73baZbqiqf6yqV6rqB1X1zap6sFt+ALiGV38h+JNu31vofQG4pjv+08CdwHHzjFcCDLqW3pfpXcH+Dn3TLX2+Avx6koPoxfPOqto+z/P9e9/97wMHzbHfucAZwBNJ/iHJL83znEcAT/QtP9Gt273tyb5t/fdnXZfkhCS3J9mV5L+ADwIrZzxmR9/9/55lea6/l/R/DLqWVFU9Qe+bo2cA182y/WngLuAcelfF8023LOS491TVWcChwNeAa3dvmmX3bcCb+pZXdesAtgNv7Nt25GyHm7F8NXAjcGRVvR74CyAL+gtIQzDomoQLgF/t5rBn8yXgY8BbgetHPViS1yZ5X5LXV9WPgOeAl7vNO4CfSfL6vodcA3wiyVT3Nss/4v/n+q8FPtB9H+Cnum2DHAw8W1U/SHI8vf9DkcbOoGvJVdVjVbV5nl2up3eFfP080V+o84GtSZ6jN+Xx/m4s36YX8Me7d5QcAXwa2Aw8ADwI3Neto6q+DvwpcDu9b8Le1T3//8xz7N8DPpXkeXpfAK6dZ19p0eIvuNBylOQxeu9K+ftJj2U+SY4BtgAHdN+YlSbGK3QtO0nOpTcP/Y1Jj2U2Sc7ppnFWAJ8F/saYazkw6FpWknwTuBy4qKpemfBw5nIhsAt4jN5c/IcmOxypxykXSWqEV+iS1Ij9B+8yPitXrqzp6emlPKQk7fXuvffeZ6pqatB+Sxr06elpNm+e791qkqSZkjwxeC+nXCSpGQZdkhph0CWpEQZdkhph0CWpEQZdkhph0CWpEQZdkhph0CWpEUv6SVFJrza9/qaJHHfrpWdO5Ljac7xCl6RGGHRJaoRBl6RGGHRJaoRBl6RGGHRJaoRBl6RGGHRJaoRBl6RGGHRJaoRBl6RGGHRJaoRBl6RGGHRJasTAoCc5MsntSR5O8lCSD3frD0lya5JHutsVe364kqS5DHOF/hLw0ao6BjgRuCjJscB64LaqOhq4rVuWJE3IwKBX1faquq+7/zzwMPAG4CxgU7fbJuDsPTVISdJgC5pDTzINHAfcDRxWVduhF33g0HEPTpI0vKF/BV2Sg4CvAh+pqueSDPu4dcA6gFWrVi1mjNIeN6lfAyeN01BX6EleQy/mV1XVdd3qHUkO77YfDuyc7bFVtaGq1lTVmqmpqXGMWZI0i2He5RLgCuDhqvp836YbgbXd/bXADeMfniRpWMNMuZwEnA88mOT+bt3HgUuBa5NcAHwXeM+eGaIkaRgDg15V3wLmmjB/53iHI0laLD8pKkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1AiDLkmNMOiS1Ij9Jz0Aqd/0+psmPQRpr+UVuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1YmDQk1yZZGeSLX3rLknydJL7uz9n7NlhSpIGGeYKfSNw2izrv1BVq7s/N493WJKkhRoY9Kq6A3h2CcYiSRrBKHPoFyd5oJuSWTG2EUmSFmWxQb8cOApYDWwHPjfXjknWJdmcZPOuXbsWeThJ0iCLCnpV7aiql6vqFeCLwPHz7LuhqtZU1ZqpqanFjlOSNMCigp7k8L7Fc4Atc+0rSVoaA384V5JrgJOBlUmeAj4JnJxkNVDAVuDCPThGSdIQBga9qs6bZfUVe2AskqQR+ElRSWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWqEQZekRhh0SWrEwKAnuTLJziRb+tYdkuTWJI90tyv27DAlSYMMc4W+EThtxrr1wG1VdTRwW7csSZqggUGvqjuAZ2esPgvY1N3fBJw95nFJkhZosXPoh1XVdoDu9tC5dkyyLsnmJJt37dq1yMNJkgbZ498UraoNVbWmqtZMTU3t6cNJ0j5rsUHfkeRwgO525/iGJElajMUG/UZgbXd/LXDDeIYjSVqsYd62eA1wF/BzSZ5KcgFwKXBqkkeAU7tlSdIE7T9oh6o6b45N7xzzWCRJI/CTopLUCIMuSY0w6JLUiIFz6Nr3TK+/adJD0BKY5H/nrZeeObFjt8wrdElqhEGXpEYYdElqhEGXpEYYdElqhEGXpEYYdElqhEGXpEb4wSJJS25SH2pq/QNNXqFLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiMMuiQ1wqBLUiP2H+XBSbYCzwMvAy9V1ZpxDEqStHAjBb1zSlU9M4bnkSSNwCkXSWrEqFfoBdySpIC/rKoNM3dIsg5YB7Bq1aoRD7dvmV5/06SHIGkvMuoV+klV9XbgdOCiJO+YuUNVbaiqNVW1ZmpqasTDSZLmMlLQq2pbd7sTuB44fhyDkiQt3KKDnuTAJAfvvg+8G9gyroFJkhZmlDn0w4Drk+x+nqur6m/HMipJ0oItOuhV9TjwtjGORZI0At+2KEmNMOiS1AiDLkmNGMdH/5fEJD9ks/XSMyd2bEnj03pHvEKXpEYYdElqhEGXpEYYdElqhEGXpEYYdElqhEGXpEYYdElqhEGXpEbsNZ8UnSR/FZykvYFX6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0w6JLUCIMuSY0YKehJTkvynSSPJlk/rkFJkhZu0UFPsh/w58DpwLHAeUmOHdfAJEkLM8oV+vHAo1X1eFX9EPhr4KzxDEuStFD7j/DYNwBP9i0/BZwwc6ck64B13eILSb4zwjEnbSXwzKQHsRfwPA3mORpOM+cpnx3p4W8aZqdRgp5Z1tWrVlRtADaMcJxlI8nmqloz6XEsd56nwTxHw/E8LcwoUy5PAUf2Lb8R2DbacCRJizVK0O8Bjk7ys0leC/wmcON4hiVJWqhFT7lU1UtJLgb+DtgPuLKqHhrbyJanJqaOloDnaTDP0XA8TwuQqldNe0uS9kJ+UlSSGmHQJakRBn0ISbYmeTDJ/Uk2T3o8y0WSK5PsTLKlb90hSW5N8kh3u2KSY1wO5jhPlyR5untN3Z/kjEmOcTlIcmSS25M8nOShJB/u1vuaGpJBH94pVbXa98T+mI3AaTPWrQduq6qjgdu65X3dRl59ngC+0L2mVlfVzUs8puXoJeCjVXUMcCJwUffjRHxNDcmga9Gq6g7g2RmrzwI2dfc3AWcv6aCWoTnOk2aoqu1VdV93/3ngYXqfSPc1NSSDPpwCbklyb/ejDDS3w6pqO/T+gQKHTng8y9nFSR7opmScRuiTZBo4DrgbX1NDM+jDOamq3k7vJ0telOQdkx6Q9nqXA0cBq4HtwOcmO5zlI8lBwFeBj1TVc5Mez97EoA+hqrZ1tzuB6+n9pEnNbkeSwwG6250THs+yVFU7qurlqnoF+CK+pgBI8hp6Mb+qqq7rVvuaGpJBHyDJgUkO3n0feDewZf5H7dNuBNZ299cCN0xwLMvW7kB1zsHXFEkCXAE8XFWf79vka2pIflJ0gCRvpndVDr0flXB1VX1mgkNaNpJcA5xM70ec7gA+CXwNuBZYBXwXeE9V7dPfEJzjPJ1Mb7qlgK3AhbvnifdVSX4ZuBN4EHilW/1xevPovqaGYNAlqRFOuUhSIwy6JDXCoEtSIwy6JDXCoEtSIwy6JDXCoEtSI/4XfaVuDbJvIrIAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Histogram plot\n",
+    "\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "  \n",
+    "# frequencies\n",
+    "DataSet = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n",
+    "\n",
+    "  \n",
+    "# plot title\n",
+    "plt.title('My histogram')\n",
+    "  \n",
+    "# function to show the plot\n",
+    "plt.hist(DataSet)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +222,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module2/exo3/exercice.ipynb b/module2/exo3/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..104dad66000b25198d8af8dcbdc1ef319351d2a4 100644
--- a/module2/exo3/exercice.ipynb
+++ b/module2/exo3/exercice.ipynb
@@ -1,5 +1,90 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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lW/1xevPovqaGYNAlqRFOuUhSIwy6JDXCoEtSIwy6JDXCoEtSIwy6JDXCoEtSI/4XfaVuDbJvIrIAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Histogram plot\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "  \n",
+    "# frequencies\n",
+    "DataSet = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n",
+    "\n",
+    "  \n",
+    "# plot title\n",
+    "plt.title('My histogram')\n",
+    "  \n",
+    "# function to show the plot\n",
+    "plt.hist(DataSet)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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87J89bLutIXeQSSYMWcVZZDNuzceOuFLUatClBEExk9yRQa/JHXQpcHRPHoDFoLc7KOiSjvNKYKMu2zJcAG3doxIUFQhiQ5CHzoKEBye0YQ+9KP9/5MIGOl1qDF3YCRfXG7i0YR911pBVIzgI2NdebsiYdAQHowwGayl8pnatBSy3n7bIyv0Ng67notfbqnEF4Fy3l4ceWWGRSpGSehOHEQZdMFJYs1x4RmtVD4genNAMRC809O9fLNuObSdsNhVbPjag5WTn9eCg83V4kgsQbW9wq7dazCZ3pKGztR7bo6VdsgCp5qFrGwcz7HXDQ1dcHnqUvVyEhy4YGLpdinueWY5F+h5g9gPvUhgBNCssIHqQjWPrQfn/Y5fKtmPbCaxLZMuytkZbRSEjGQbO6aFPOErggWikpm6X6llDFoMeILk0ZdXWFtcJS1V0SS76JgbA2Mhq7Q7aHRW1dgdThZTteSJtzqV2kU5KwQ/cBYRBF/jyz2dW8DN/+hAen98MfvAQENSoiqUsHprozXxNudPFk5crrmPbLkxyqFhzshUV+XTSkB5YkFTtUlRaHaOnCqBVigLRbGS8JlWlAA/9fz90Ee/6kwddMhKDrZd56GWLh87Wa02PZAbfmeWSSUpoRzhTVARFBQPB8/rwg51W8w0KNUuuMS8X3emhR62hP71QMV5jp+l7LUVFSzfE9s6DHeTTkktyYd6tvcCGeei7LzUZo9gku4ful4d+Vv/+PbNY5d7PDPS+8SzSUsL4ncUNADMoWpc7Zh8XD8kliitRRe32rJZBGHSBL3O6ZxSHfGzA7gXzPOKVahulbNKoYox63Uxumcindq1iErBXTdZlu4fOXqfM6WkSpeRiDHpwSC5+676wrn3/nl2qce9n6xzPpTCeTxkNumqWLBdTalLNTosuDz187ODSRgP/+PhC4OMYwkMXDAxz600A8WklW293wJre8a46VmsyZkoZZHTNM2rJ5dGLZcyUMrhiprhjyaVs6TZoNe4NuaNr6HYPnXnx4zwPPQrJhWPQS9mU79XfhTXNQ392yctDl5FNJZBNSZjIpQwD35BVw5AXLeteb7g7LQJbmyv6mfvO419/7nu2OIUfIigqGBiYdtmKiYdea6tGEYqXhz5dzEQqPVh5dK6M6w9NuDoCbgcvD53JD3ldHzckF/3x9iwX7TFRZLnwRrGxLJcup6hKUbuY39AcCm+DrmAipxnniXzKnoeuB0VzKQkJomnoG5zWuYCWh249Rj8ub7ZAKbC4GS7NVFSKDij/9OQivnF6qd+H0TMopbi0ET8Pfd+4Pgme07tjtdbGTCljnIBRauibDQXnVuu48cgEihlpVyUXJqcATENPIpEgKKQlI5uGefTcLJcIeqLLnGHJpYypbzu5XG6i06WYzKfw3HKNW0m72VSMGMB4Lo1yQ0FH7aLd6RpXJIQQFHRph3VatG5igLnJhLkiW9IN+Xy5GfhYwJ17HyXCoG+B3//6Gdxx77l+H0bPKDcUw8gMWytZRe3i43/3lK0vC6AZ9L0lzaBzs1xqbczYPPTo1s308xsOT6CQTnKDtFvBasRZlku3S9FQVBT0AKH1SmBDN262wqJUjzV0n34u59e0q8PXXT2LdqeLuXV3pgvrRQNoOvpmU0FdNjstGq+jr3ujIWM8l0LSoWlvZQNf2KpBV7tIiaDo4LFSbQ2dYfPj8Uub+O1/Ou15/5wlVSysXjgonF6o4s7vPI9vPmMfe1hrdzA7pkkuzuyKlqKi2upoGnqE6XuMR+fKIAR4waHx3ZFcdCOeTiaM/7c6KigF8pYUPpbpU24qIMQcNAEg0tgBb1iyX8fFi7p+ftu1swD4sstmw/TQNclFtvVCZxQySSPLxSm3WI8pSGrqdimWq5pBvxzCoFNKtW6LIig6WChqF6s1OTaT4AHgK48v4A/vOeupE7OAKDB8HvqGMcXG9FrZpThrUuU0oMybny6mzSBZRLnJAPDYXBlXzBQxlk1pHqTMr14NS7mhICUR7B/P2oKDgOmtWjeOzYaMsWzKNhot0rRF/TuUkdweetXDQ8+mEnj5lXsAAGeW3Zku5aZseOgTuRTqsmqsPe8w6NWW5qFbr0gYRuwg4Hu+3pChqNpnxPR9P9hjhYY+YMRtig2gzZPUfvI9w2H20I0pNtaxZI45k87KTPYZz5QySEkEhESjJQOa5/boXBk3HJ4AoBkcr+rVsGw2tarPiZwZHDQHPZgpfNYslwmHcTM89AgLi6zGbSzr7aFfWKvj6FQBpWwKBydy3Fz0ckMxYgBsLcxzLmaskou27iAPPWgjswZCL28GG3TemqNEGPSQLFfZnMk4GXS9UZWHQb+00cB4TvMeh20jY575hsVDZ1JDMZO0GTYGa8w1XcyAEBLpOLb5chNrdRnX6wZ9N3qDs74sY5b0PRZsZBq6dSPbsBhDRs819IxmhHlOxYW1hlHSf9Vs0SW5tBQV7U7X1ND1tTCDzjYx7XW0GAWv0yIQPijKDPqhyRwul4OzXBT9+Xo1sUgY9JAs6Z3w4lJgA5geupcRmVtv4vBULvKxZFHAAn5WD51tXIWM1qiq5sissHrogNl5MArY5sFaDDBvcieB0Y2GjIl8ChP5tBEUZZJLzkNy8c72iE5y4QdF7Q3Ful2KC+sNHJvWSvpPzZZwbqWOjkUCY5+tmeWi/bykG/RC2i651PQ8dF8NPcig63bgxUcnMV9uctMtbWsWHvpgsqx/kHHy0Jkhr7T47UvnNho4PJlHNiUZJeXDAkvJsxbbsPUWs0luyTnT0PcUNIMe5fQeJuU4hz3sJDBabigYz6UxnksakpN1cg/76Su5ROmhq/qaJXdQ1OmhL1ZakDtdHJliHnoJsto1KkcBS+sCloeeY5KLdq4WMvYsl9VaGy2l66oSBcJXyC5utiAlCK4/NAG508WaY5iIa82c3PsoEQY9JMux1NC9JZduV8tBPzyVj3wSfBQw74156oB7EjwvKDqRTxlGNsorE2ejKl6v8q2y2VQwmU8Z6XuUUsPjz9skF1b6r3h66FE4Ll6l/4B73Rf0lEXWdOvkbBEAcMYiu5Qdw56dGnrBERRl32FnHxfAUvofwkOfKWZwWN9ogjJdeJk9USIMekhMyWW4DJsfzKDz9MuVWhtyp4tDkznNUx22oCgny4UZcDY42GlEWJUoI8qNzGnceL3Kt0pZT+GbyKWhdilq7Y7pobOgaFozbNpkJreGnpQSSCZIzyQXKUGQT0sup4KV/DMN/cq9mkF/ZtHMdClb+rgApqfOM+jWFEaehx5WclmqtDA7njUGoATlohuZPcKgDxbMQ1e71KbjDTMVHw2dFXEYksuQbWQbuodu7TpYc3rosttDny5aqyalyPLQnZ5bYYceektR0VRUTOTThoHbbCqctEXt56Jevu6UXAB9I4tg3WzNGUfVJK9B14X1BlISwQHdcObTSRyeyuHZZdNDZ60L2HpL2SQIMZ0v1uqAvQbD2QsdCJ+HvrDZwv4x06AHeeiKKoKifaHdUX0DHEsVs+IwytzkXtHVPTiAb0RYyb8RFI3QQ1e71PAkdwvmmTdk1fA2DQ9dH/bg9AqdHnqkk+ANz83ZQGp777Oz6yCgeezsfbUWFgHm58s16KlogsFeAcJSNunKQ7+wVsfhybwtR/7k3pJdcmnaJZdEgmA8l0KXahtYwvK3Vm+dl+Vipmv6v/9Lmy3sG89iLJdEIS0Fe+giKNp7KKV4zW9/E3/x3Yuej1m2zHuMQ2BUK2LR/s8LijIP/dBkPrITnPFfv/QEXvirX8O7P/UgPnv/eSPbZCeUm4qhB1snwQNmlovTeC5X20ZbAACRbmRuycXeOGurGIMbLB56pakYa8ylzCwXwCyKYTKFla3EDiothdtjhQdPcgGAIqfj4vlVM2WRcdVsCc+v1g2vt9xQjEHTDLZ2a8oiYM9J326laK3dQbXdwexYFoQQHJzMBRYXiaBoH5DVLhY2Wzi/Wufer6haNHuvns4WBx3degLxgqJzGw3MlDLIpiRkk4lIC4sWNlsoZJK4tNHEf/nSk/iXd9y/o+dTuxSbTQVHHGPJau0Okgktv7yUSUJWu8YJV2930JBV7B2zaOgRbmTMYLITnWnc25VcrAFC5rGWmwqaiopsKmF4uoaHXvbx0EPGDhS1i1f/1j347P3nQx2j3OkimSA2rxvQGnTVLE4FpRQX1xs4qgdEGVfvK0FRqVFgtNnUgrqEmM/HgrzWDBftd23dCQKMZTmSS4hgMMtB3683dzswkQssLvLaxKJCGHRocwsBeF72M4+RpVDFofOg1aDzgqJz600c1qf2ZFJSpFclcqeLK/cW8Y2PvBo/desRm7y1HSpNBZSaGRKsuKiuDz1g3ffYbYAZI2GbNhBtUNTQk/U0wYQeHNy2h26VXCwaurWNLMDx0D3khzDf8cXNFjYaCk57TBNy4tUX3Kmhr9Vl1Nodl4f+iqumQQhw11Nax9NyU7H1cgfM4qKCy0PXfp/Mp21SDCMlEeMYvWDa/OyYZtAPTgQXF8lCQ+89LHDkpV+yk52lKrF82mGm2nIHC63MbTSM9UbtoctqVy+1J9hTyKDW7oS+jOfBjNvxaeahm1Ns2IntDEIySc0quWhjyaJNW7Reihc4gdqwbFqKbJhB1zR0FXmLt8o8V9bn3pm2CLD8++B1M1luK10HuQY9a68JYBkuxxwe+nQxg5ccm8I/PbkIQG/M5Th+Lw/dMOgcuQVAqMpg5qHvs3jo63XZN/4jslz6gGnQ+R8M25mZxzpsRTY8mFeeTSVckktHl6AOGR56tHnoito1PJjSLpTAM4/8+LSW6mYbeuCYYlNzeuhjPfLQFY/5mtsMim5YxsnlUhLSUoLrobN1MyM8xjHomZDBYNbrZyHsoAePUWzFjD0oynLQnR46ALzhun04vVjF+dW6rTEXg0lI1iCo9XdeDjojqJCMVYnus3joAHy9dCG59AEmuXh5R8x7O2R46MNv0Fkg9MB4zhUUXdhsQe1SHJ7U1htlCTygfemZB8P0zapH9WoYmLd6TPfQNwyDrtoqJrXb/CSX6NYtq5pxs2di+EsuT17eNFq3Oik3tU6L+bQEQojRz6WpqEbZv/Ya2roXN1sYyyZdejagb+AhnBbWjXOh3AzVJdJLchnTpxax5zi3UoeUIDg06Tbot//QPgDasJkypxcNM/BOyaVgeOjuDYwRtJEtbrYwnksZ7ycbJO6XuiiyXPoAu2RinrqT5WobCaIZPyBeGvqBiZzLG2aelyG5pKKVXHgeut+cySCYt7p/XCuK4kkubg+9hbSUsHl8UWe5OE/yQtp7YHK1peBtf3Q/Pvblp7j3s7J/FiCc0Acme3nonS71lB/CbmTse1KXVVSawZ9X20dyodQ8/04vVnF8usB97MGJHF54aBxffXIRmw3F5aGPB0guvAwXRlpK+AdFKy3DOwdg5Mj7SU4KR1qLEmHQATSUYMllppQxduZha1TFgxnM/eNZlxFZ0C8h2SVlJimhE2FBlaJSi0H37r4Xlg0jhS+FSY85k86875WqNnrOmjERVnoAgLVaG/c+uxL8QJ12R3Wn7/kMufjio5fRkFX887MrhpGworXONY0bK/9n80QZmaSZ8cLTz9ljwnzHL1lS9kK1kvWUXOyf+TNLFVy9r+T5PLdftw/fv1hGtd1xZekwj92ZtiglCK7cW8TV+8Y8nzcoq2lRz0FnzJYykBLE30Nn3RaFh947mgFB0aWKlp8ctt/DoPHcchUPnluz3VZtaTm8M6UMqi37YIV1veHQHr1qMhMiR3cnWL1V00PfieQig+jpaZP5tCvLBTA9ONbljxl0K0xDDyMnfPq+8/jpP/1u6AIpnnHzmlpEKcXnHryITDKBWruDh86vux5Tbii2wQ2sJ7rToBNCjFa64x56ctjYwdx6A1fpJfkLIQ06Lzho7bhYa3cwt97ENfu9De8bdNkFcG9K7PeiQ0MHgK9/+NV478uOeT6v5qF7b2RODz0pJbBvLOvroRsVwcJD7x2BGnq1jdmx3syZjILf+/oZ/NJfP2a7rdbuoJRNopRNQe1SW6B3rS4jJZkFG1m9KCWqYLC865KLdinOKgeteehFV1BU++yXK22bfg5oHhul5tRyjlqVAAAgAElEQVQZP+Y3mujScFNsAN24pdwGnRcUfezSJp5eqODDt51EWkq4xuoBbM2mgTY99I5tcg9grt3bQw9OW2wpKparbdx8fAoAMB+iN7iXhs4GRVdbHSPH/NSst4d+xUzR2EicGjrz2PMOySUMWlYTf93axLI2Zi0eOgAcmMj6fuaisKgPMMmlIatcb2y50sJMKRt6TNWgsVZrY7nStq2t2mIG3e0Rb+hTXZj8EOVYMkA7WdJ6HnBpF4Ki2pgx7USfzKdRbspa50HZLyjasmW4ANjSGDqW6XEpZApfm+OhFz2Cop978AJyKQnvvOUIbjkxhW+cXnY9ZrNhl1zGcilsNrRK0UKaX2TDG8UGsKwm/8+ayS0vOjKJZIJgIcS6/dIWAW3DPb1YAQBcvd/boAOml+7MQzeyXNJuDz0IP4ltudoGpWZREeNgQHERS8nl5b5HgTDoAJq6Z652qcv7ZlWis2MZy5iq6A16vd3B737tmdA5vn6UGwrana5NK6+2FJQyKdOgOwo7rP0umCcZlYeucCSXio+Hvlxp4X/efcYzV33TMgl+Ip/Chr5+tUsNY5aSEsgkE6i3O5A7XWw0FFsOOmDpDR4iMMokh0tb8NBdQdFMEk1Fta2r0lLwd48t4MeuP4BSNoXXnNqL55ZrRg44o9y052RP5FOotjt6lgs/48NLcklLwZILC4ge3ZPH7Fg2VOqil4Zesoyhe2axilImacRvvHjriw7h2v1juMahiR+cyOPFRydx45GJwONxkvZpSmbkoI85PfQcFvWsMB5Kp9uzoiJAGHQA9uwWp4fEqkRnx7KRe6qMzYaCn/rUg/gf33gOd+lFFDuBachrNbOVbMXhoVtz0TcasqGfA0A2GW0w2Cq5ZPUcaj/J5S8evIjfuetZPHW5wr3fOgh4Ip/GZkOxdVpksPznlZo7ZREIP/SAUmoYtNCSi+rWk41ArUX6+9L359FUVLzzliMAgNddvRcAcM8zppfe7qhoyKota8Wa/eH00AMllxB1B5fWzUyoAxPZwK6DgH+lKKA5FacXqji1r2QLTvM4Nl3AP3zolbYgJaBNZvrCv3oZXnhoewbdy0N3Voky9pYyUFRqNEdz4nVVEhXCoMPU0AF36uKSUUGYMTy2KCWX5WoLb7/jfjwxvwlgZwU2gGZsWNYHm8gDMMklxZ3puO7hoUeRrkkptWW5AHrlYNtbcnlAD/A+tbDJvV8LEDLJJQVZ7Robs3PoQb3dcY2eYxgd+AI+b3YFBJgVmEG0Fb6HDtidis9/dw7X7h/DCw+NAwCOTxdwbE8e91hkF2cbWcDeo8WpobOAMK+PC6CtO6hN9KWNJtLJBGaKGewfD+5pAjDj5ta2S5bv4NOLlUC5JSqcaYt3P72EX/ni4/jG6SWc16tXnZJLkETodVUSFcKgw+GhOwKjyxYPPewg2e3SUlS8/Y8fwIW1Bu786ZdonuoODXpTUY0vqd2gKyjpo9gA+0zH9bqMPQV7X3B2fLsNCzhajVspm/T00FuKiu/PlQEAT3p46OWG2eODGS0mhRQz9iKbervDLfu3HlPQBm6VG8JKZG2OcXMa9Jai4qmFCt7wQ/tsHutrr96L+86uGY4Ia3XgTFs0ntdTQ/fOcgH8YwdzGw0cmsghkSCG7BA4X9PDuLEN5sxSFdVWB6d8UgujxNmz6LMPXMCfP3AR7/v0w/itrz6DdDLh2gSDgvheVyVRIQw6nJKLo6WqxUNPSloOb1Qe+rmVOp5freNjP3YdXnnVDIpZ77zksDDvHABWLJKLMyjKNGtF7WqjzCwGPRvpnEl3FoCfQX9srgy5owWaeJKLrMcKmLFiWRDMc7Z66CW9KRSv7B8IHwxm+vnJ2eKWNHS35MJSKbXXYzLG4Sm7nvzaU3vR7nSNKxVjWLIty8X8f95DcnEGFBnGun2uyObWm0bl9IGJLBSVYrXu31St7WHcklICuZRkpGNe45ODHiXO2MFKtY1XXjWNz7zvZrzrliP4hVedcElBzEP3mss7cJILIeROQsgyIeQJy22/SgiZJ4Q8qv97U7SHGS1NxTQeTgO6VNGqRPfogw+0Dz3ahk3TJb1jHGcIw1bZsAyxXdUNF6XUkrZo19CZcZjieOhRGHSFFV5I5olSyqQ8L2EffH4dhABvesF+PL1QcXmFTMtkGjoz7EzbtksukmHQCYHtqgQIv27mod90bAor1XaoKxleYZFzUDTz9lmFMuOWE1PIpSR8jXUddMzWBOweurPIphCooQevWxsgrh3X/vHgniYAIHdUzyZVxWwSZ1c0WeNkvwx60m3QD07k8OqTM/j1H38BPvz6U66/CeWhD5jk8mkAb+Dc/nuU0hv0f/+wu4fVWxqyarzpzsKQ5apWJcqq66JsVOUcV1XMpHasoZctHvqa7kE1ZC2TQtPQ7SXwrKhoiuOhRyO5uCvp/Dz0B59fw6nZEl52xR7UZRUXndkeunEbNzx0p+Ti1NBVrFRb2FPQrsCspEN4qoA5Cf7Gw1ogLmyAMMMpLALMz4I9zwFHxkcmKeFHr9+PL3zvEubLzWDJxaMMntc6V3t+/yuTaktBuaEYrSGYrhyUuujnrbJc9IMTOW6/8l6QsXTXVLsUa3XZFVdxMhZQ2TxwHjql9F4A7tK0GNGQVWOWpFNyYVWijIxP8cFOcRYhMElgJ7AMl5REsFrV/s++fKVs0rjcZR6xYdDzvfHQeZV0Jc4EG0B7fx65sIFbT+zBtfu1IKFTR7eW/QMWg152Sy6sDzevqAiwaslBkksLe0sZo19+GNmFV1hUdGjo8xtNJAhcmRwA8KEfPglQ4PfvetbiofOzXHIpu4f+Y9cfwH9+49XeeeiOz7vaUvCWP/wOvn9xA4DZlIs1bzO6DgakLvp5q8zTvaZPAVHAnoe+XpehdmmgQQ+qbB5ED92Lf0MI+YEuyUx6PYgQ8gFCyMOEkIdXVsL3uoiCWruDH/mf3zIySBhNWcW0/sG5PXT7yR7UYnMnyA5vtZjdPYN+fLpgBEXZl4/pf9bXMQy6bVhy9B66MyjK0yQfny+jpXRx64kpXDVbRDJBXJkuZUsbWcDUlZnkUky7s1yWOWX/QPjsnoXNJvaPZw1NOUxglFdY5AyKzpdbmB3LcvOYD07k8O6XHsUXvncJD53fQDJBbMHPdDLhGgzNODyVx8+/+grP1ECnhn52pY5H58r43bueBWDGI1h75Yl8CtlUwvfKpKN20aXeXQdZcdGpPsktgHluU0rNzKeiv0EvxiQo+r8AXAHgBgALAH7H64GU0jsopTdRSm+amZnZ5svtDhfXGnhivoJH9SwJRkPuGMOBnaXXrGqSkUlGN73H6aEXMsld0NA1w3jFTNEw6BWLh85+stvWGxwPPYSmul1YlovVaLF2qk59/IFz2oXizcf3IJuScOXeoiswWnak8KWTCRTSkuG5W41bMZNEQ1axWGl5eOjh1r242cL+8ZzRrClM6iLvRHe2I7hcbvoW2HzwtVeikE7irqeWMJFPuww008idGnoQaYfkwmIv3zqziqcuVzBnDBDXNjBCCA6M53z7uQS1kWVr92ueFTVpKQFKtU6UrDYhyENPOa5wnVg7ifaCbb0SpXSJUqpSSrsAPgng5t09rGhgXp9zN23KKibzaRDi9tA3m4pNm9zKAN2t4vRWdzLwgLHRkFHKJDE7lsVqjUku2vswxgy6ZeNY1x8zWXB76FGsm9fropRNgVJ3CumDz6/j5GzR2GCv3T+GpxYcBr3pPn4mRWSSCZtOzozISrXtynAB3IaNBysq2jeeRVJKYP+4f28PhlZYZPecs6kEEsQeFHXq51amCml84FUn9DW65ZMxj1ayQTgLqljsRUoQfPJb5zC33kAhLdkkmwMB49iCepqwegi/LotRY01T9apN4OEX8/HK7ImKbb0SIWS/5dcfB/CE12MHCZYB4dxNG4qKQkZCIW2fBN/uqGgqqk2PjFRycWroAQU2YSg3ZEwUUpgpaaPdWopq0dDdkstGQ0Ypm7R5FabkErxuSile94lv4i8evBDq+Jwyk3Zc7stYRe3ikfPruOX4HuO2aw+MYanStuXXbzS0QQ9W+YENNXB24LPq6c4cdMCioft83pWmVl7PAoOHJnOBGnpH1doQOE90NuuUXZ0sbPobdAB43yuOY7qYcWXoAKaRz3KKefxgV2Rm/YK2Sb79JYfxd49dxsMX1nF4Km+7Itg/nvX30AMm90zqss3x6QL3/l6QicCgD1xQlBDyeQD3AzhFCLlECHk/gN8ihDxOCPkBgNcC+MWIj3NXqDT5HnpD1qa6FDKSzUNnG8B43u6tRp7lon8BCukkWkp3R33IN/SqSRb0Xa21DeNtSC6WNME1R1ERYJ23GOyhr9TaOLdaxyPnN0Idn5nZY0lb5GQOPDG/ibqs4pYTU8Zt1+otVq2yS7kh2wY9AKaO7h5LZho6v6Co3+fNKiRZ6t7BiXyghu4nP7Ce6Cu1NhSVGlNxvChkkvjs+2/Gx958neu+8VwK+bS05cZQziuytZqMQlrCv37NFaAAnpivGPo5Y/9EDsvVtufm1w4w6D/3qhP47PtvcWUa9ZK0RWJbqbZRzCRDyVXFbMo7D52TzRQlgUdLKX0H5+ZPRXAskcPz0NUuhdzpIp9Kah66pciIV1KdTkqefRt2itNDZwGXelvFeH57X4pyQ8ZEPm3ECFZrMj8oqhvPjbrMnWST8WlcZIVlQMyFLIFnBt2an1zkZA5876IW92DtWgHNQweApxYqeNVJLT7j7AsOeM+ZtHrsPMkljIbuHBx8aDKHxUrLNxjmNziYDYpmm8LBCfeVgxOv3uGzY1nfCT1e8CSX6VIGhybz+NEX7scXH73sGg93cCILSrVWGUxbtyJzPmfnsTr7pPQam+RS4wfKeYz5eOjKoHnocYIF/qyZI8wjz6cl5B3tSw0P3TGWLLKgKCuDt6QtAkB1B7LLhm7gDINebaPa6oAQsyTcesnI89ABNs0lzBSbhv4zfMUkYA+K8jpAXi43UUhLNmlkIp/GwYmczUO3ts5lsN+LHvnYAF9yYVcNfgadFRUxyeXgZA6Umoaeh5+3ynqie+Wgb4V//8Mn8emf2Xp4ywiCK2bLCPad+Dlds79C70fOYFcoXl0Xe90XfDsYBl1VtZbZARkujJJPNposui1GB5NcrK1Zm3oqXi4tIZ+2l9qbJdW9CYo6dUZnocl2YAaOdU9cq2sGvZhJGrJEKZNETdZ024262yACWsAujIfODPlipRXqfXIWUwFmsNbq9SxWWlwP7hpHYNTax4URNAke4GulYaSmxU0tV5xJNkyK8Mt08TNurCc6C6wGtZH1Y6qQxpUOwxsGnuTCKqWvOzCOf/zQK/G2Fx+y/c0B/UrCK3UxSEMfBKxXJlvx0P0qm4clbbGnnF6s2LrLbReehs4aHOXTkpHGxuB56H49k3eKU082JZftGfSO2kW1pc1dtEoulZZiq8ZjQ3rrcgfrddmWg84IPThYr9ykNLgUHDCvSlKOLBfALrksV9wDKABNdjm3UjMbVXElF76Gzjz0UjZpTGVyEiQ1Xd5sYW8pa2i/hyaCi4vY+5jhvGZBdyoul5vGRKle45RcVmuyEYMBtE3U+X4Z5f8egdGgtMVBwDrvgDeS0IuhCooOAn/xwEV8+C8f3fHzmGmLpqFoWAx6Pi3ZUuV4JdWZpBTpbM0EgWEcjD7R28xFLxt9TdLIpiSUMkms6JILkzUA04AuVVqQ1a4tB52RSSZCFRbNbTSQ1INwziEMPHh6Mi/LxTnPkXHj4Ql0KfDZB84D8JJc9FiBR08TXkCUsdXBwfvGs0gQ/8lFzPPle+ja5ft8ubUj73wnWA1bt0uxXm9jT8HfuBUyWl+g5Qq/QdcwSC4seFltdVBtdbZg0FNoyKoreaHb1VpDD0ulaM9gPTd2yibHQ2cGPZdOGt6R8/FWL0nz2KLLQ09x8qS3K7k4mzZNlzJYrbWN1rnO17mwphlgXiAtG2DYGJc2mrhB72kSJjDKk1xyKQlSghgbL6UUS5U2V3J5zakZvOG6ffiNfzyNrz+1hHanG1pyYe8BTz9nOHtkO9FSC82/TycTmB3LhpJcPIOibS0o2jeDztpEKyrKTQVdCtvAEy/8WlUMg+TCjo3JXVvR0AH3eap0e7/mwX13LRQzmle802BkpWkGRdl8TXapnktpQdGGZeOoNBWMZZNGYy7Af+7gTnEWIexUctlwdE6cLqZ1g96xbVLsC8kaXfEMehgPXe1SXC438eJjk0hJJFRglJe2SAixXcaWGwrkTpdr0Akh+MRPXo8rZor4t5//PgB3n+8Jj6BoJqm1Q+ZJOcZjfOZrGkVFY3bDe2gyF2pwsJdBr+mSy04CojvBiB3og5EBGJKdH7m0ZBsWYyUobXEQYFlN83rfn61ILoD7SrofVyWD++5aYLmgzirOrcIkF7VLDc/cmuVS1FPGmLEvN2SXt8fy0HnDpHeKNizZ7aFvV3JhrXOZgdtTyGCtJnMkl93x0BcrLSgqxdGpAg5O5LYkuThPdKtBX6ryx38xipkkPvmem4xNwamhT3po6IQQXL2vhBccHPc8Pr/YQaXVQUNWuYODw2jo/Dx0yRhpFpSDHiUsdsAMehgPPZ9Oep6jQWmLgwD7PNhntxXJBXD3RO/HVcngvrsWdio9MDabitGwiBkLZ5ZLl5on3GZTsQ0NALQPh1KzB8lu4oyIs7TC7a57wyW5pD0kF+3+IA89KGtlzpgzmcOhybzR88MPmSO5APbMATPX2/sEOzZdwP94x42YyKdcmR37xrI4PJXj5mt/5d+9Ej/7yhOez+tXGcyOa78jV/zQZB6LlZZnQZjfiW7ddPrloQNm7IDNoQ3joWsxKP53xPRWt1a12kuckotfbMUKLysL6E8geCgMutmFbvvataJ20ZBVI62MGQtrULSQsRvQsmV6PINdlkUhuzg1dNbadqeSC/NQp4sZbDQUfUC0W3K5oM9N9JZcAibBr7MufHkcnsoZg4T9UDr23HvrMbH0UhZo89O6AeA1p/bi+//lNly5194PJJeW8K3/+Dqj+GgrWHtkO1kwqkTtxzU7loHapUbnSiemt8rJcrEY9DBFRVHBNvA15qGHKFDK+0guw6ShX9poghD+ecDDq+Oi13c7Sgb33bXgNLTbgaUsskATMxaGQU+ZZb5MR99sunOazaEHETSq4qQ47aSF7kZDRloy26gyL0sbbmHx0PX/z200kZKIq+cJwCQX/zWzE+HARBaHJvNYq8uBm5GsqkgmiKs83Sq5LLIxgD5aNyNoWvxW8Wv1sGBcOdg9aWaUnQPHGUaWi0fpP+PghLvislewda/VZSSI9zAMK76Si8+aBwUmBy1VW9hTSIduQ+A1KJr10U8JD92Os/H/dmAGnJUssze/qX8Bc2nJCJqx1MXNBs9DZ9VkEczX7FCX9FDM8HNc1S7Fd59fx2999TTuO7vKfb5yXesUyYyc9bLZ6qGzdD6508VUwd2GFQjXw2Zuo4F9Y1lkkpJR/h3U10RR3Wtmx8c+o6VKC1OFNNejjZpMUvLMQ1/YbIEQ96U520C9DHoYySWZIKE13Chg616tyZgqZGyJAV7k05L3mocoD53ScBITwysoyhveEjVba5TcJ3YjKGp46IbkYnroyQTRBwKYr0OpFphyGfSQQw+2A9dDz7gHRf/O157B5x68iDX9kv6eZ1bwjx96pev5nDnZ1uKQMYuHnkgQI//ZcxJ8SgrMcrm03jSm2LB5k3PrDZyc9W6JygY+O7EFRT36lfcCr9gBpRRfe3IRp2ZLrg0p6Pvql+XCnIr9E9lQRjQqWHbPaq1t+9744WvQhyAP3XpsW9lMvaYW+X3OUTG4764FZ+P/7bDpkFyYjME6LQJWaUdFXVbR6VLXIF0W1IlqYHLaYdyKjtzebpfi//3mWRyeyuMP3nkj/sPtp/D0QgXPLlVdz1du2Hu5W70Op6zCfvfKZsiGyO6Z22jgkD6hnl0JBWW6eDUvYv0xWA46bwxbL/BKU/3WmVWcXqzifa847rovyEP3z3LRPi/nYOheow1D72Kt1g6V4QIA+Yyf5OJOTx00tmvQM0kJ6WTCraGz3kzCoNthhnZnkotm0J1B0aasGiegqaF3uGX/QLge2duF56EXHJLLekObdfjjNx7Ej7zwAH7ypsOQEgRf/P686/lcHnqJL7lov2tr9/PQKfWWmtodbfIP89Cni2nkUlJgpovXzMVSNgW1S9FUtOedDQiIRkXGo4fNHfeew95SBm++4YDrvlxYg85ZN/uu96uoiGFkudTlwCpRRj6lpVwqnO9IW/9u73aMYzdJJIjxmWxV7hrLJm3N5AB+47moGRKDHpy2eGGtjg9+7nu4uMb3CJmB3j+eQ4JYJBdFNQy5odXLqtE61zkJJswUm+3CG1dVyiZt7QicjfdnShm8/MppfOnRy66RbRsNxRjuAGhpkNmUOTzDCguMemUzBPUGXyi3QKm5YRJCcGgyOBddUbvcoBE7vo2GgtVaG7N989DdeehPzG/i28+t4n2vOM7PVNmR5KL9bT9z0AGzq6jWmCuch+63kfW6L/h2Yed3UEaVE95gcxYUFR66g0wygWSC+HroX370Mr7ygwX8n390H55ZdMsPrEp0PJeyBRqbcge5FPPQ2ReyY4wyG+ulh87xVouOuaK8SSpvueEA5stNPHLRHCpBKTV6oTMIIYa35TTozGPn9UIH3C1VnbAyf2sv7MNT+cBqUb+gKAA8v1IHpVoqYD9Ic9ol33HvORQzSbzzliPcvwkjuaQlvrc6nkvhX73mCvzY9W7Pv5dkkglUmgpq7U7oAKGZ3eM+T3vddXC7sGPcqoeuxXw8CouEh26HEOIbcAGAx+c3sbeUASHA2++43zUIutJSkJYSyKYSKFkmjDQskov1SoAFUZ2FRVEOTPaSXKxXJrxp5K+/bh+yqYRNdqm1O+h0qatqkskuLsklE85D9wqMssEWVoN+aDIX2M+l7Sm5aMdzZlnbnPsmuehBURY7uLTRwFceX8A7bj5s61hpJe9j2AB/40YIwX96w9W4yieQ3AsySclIF91KUBTw9tCHwqAzyWULWS4Av+NiP9odDP47rOMMDjp5fH4Tt57Yg7/6+ZdhLJvCuz75AJYqZvvWzaaCsVzS1SfEGhTNJLUhvY22ak6Pd0ouUnSSC89DL2WTUFRqvB5vGnkxk8Trr92Hrzy+YHgFRi93hyY+U0wbf2OF/e7loWcDNrK5jQZSErF1RDw8mUe11THkKx5ekgvLwnluuQYAfQ2KdvVJ8ADw2fsvgAD4mZe7g6EMdsXnncKnDnQJPKDFDlR9zWE1dGPdnOSFXreR3S4si23LHjqnJzoLioosFw4FTvoeY7XWxsJmCy88NI4je/L43Z+8HnVZxQ8ubRqP0RptacbZennUUkwPnQ3prctmUNSZ5WKkLUaR5eKRtgjAkF1Wqm0U0pKrL8lbbjyAckPBvc+uADDL/p1BzplSBiVHwzHA9Ii9quOcQw+cXNrQmklZn/ewnvHi56Vr/Wt4aYva+35GN+hhioqiIO2IHTx5uYLrDo77luVLCa25lWejKmXwjZvVCIXV0AMll2HQ0LcZFC1yPHQRFPXBKT1YeXxeM9w/pDdZOrpHmxw+bzEkmofODHrK5qFbB8EW0knNQ28qSCaIYewZpocejYbu/PCdAWGvxvuvvGoGU4U0/vLhOQDWsn/7hvSzrzyBT7ztetffF0MadK/y/7n1hpHhwgiTuuh1Kc42mLPLNUgJgumQXuJuY7R60D/v+XLTNSCZB3MMeAyDt2oN9obV0I2gKEeWGxrJJZlAOpmw1WmEgSe59KM6dvDfYR1egQ3jCd0Tv04fGjxdTCOTTNgCcpVWx2LQ+ZILAOQzEmq6h26tsmQwDz1MUPRLj87jVb91T+gAqqJSbw89wKCnpATefetRfO2pJfzgUtnotOiUXK6YKeL26/a5/t7a74WHKbl4eegNl6FjerpfYJSX2QOY616ry9hbymx5cv1uYb0y6XYp5jfCGfRcyr/IZtAll/R2PHRH6wwrw7CJAdq6Z4qZLadXlrIp1NodQ6YCRHMuX/JpybM51w/mN3FipmBcphNCcHAyZys7r+q9zQG75GLNcgGYh67pvs4MFyDcJHjG3/9gARfXG77DDqzwPHSjeT5rVFVteV4O/uwrj2OqkMZvfvW0RXIJN8LsLTcexJ+85yZPg24YNoeHrqhd/K9vnsVqTTaujBjjuRRK2aT/sAePLJdCOgl2TvVzGry1Mni11oasdnEoRI54IePfG3zQjRv7vPN6F9IwWLPEnHgFvweNYibparYWBmZbrCqCova+OddQlP4DMHqV83hifhM3H5+y3XZo0p4yZy3jZ5ILpVTPQ7cY9IzWAlRR3VWiQLCWzOh2KR46vw5A6zN+YsZ/WC+l1DPLBTD7y6xU23jFldPc5yhlU/g3r70SH//7p9BWuiDEXRjlxXguhR++dtbzfnMjM9f9yIUN/PLfPI5nlqq4/bpZvPNmdxrfGCc/14rcUblfeNaOoNrq9C1lEbBXBrNWC4cmg5tm5dJJ31ayg27c2Pc8rHcOmJJL00NycabKDiK/+mPXbWvWgbX8n51z7U7vq2MH+1tlwSsoygKiziEFhyweOqVUG4xskVw6Xa1XC6WwSS4FvWNcuSlzjSE7EYNklGeWqkamyXm9La0f5m7uLv0HtEKolqKiEjDr8F23HsHBiRwevrCBsWwqdMe4ILKOYPBqrY13fPIBVFoK7nj3i/HH777JlREEaBukX7opT2ZisCA2b5Zor7DWHbDvU5iin3xKMhq/OdEkl8HtCw6Y6blhM1wAU3LhXUkPg8wEaJKks/1yGMyOi+ZnzjbuXlbHDv47rOM1V9QZEGUcnMhhvS6jIXfQVDSP2+qhA8CS3mc7n7Jq6Nrr8BpzAZrnmJJIoI6m6YEAABvYSURBVOTy4Lk1AFrXvAse1atWvPQ267zCVU7KopNMUsKHbzsJILzcEgZ2grM89POrdcidLv6fn3gBXs/R5Bm5dJIbJGNoGjr/C2/M/BwEyaWjGtJRmLL8QsZbImx31KGRXMLmoAPapk8IuBvZsGjo24XXcbEfgeCheYe95oo+fmkThJgBUQYLXM1vNI0qUebxMb1rWR9tZs9y0QZKbDYUzx7QmaQU6KE/+Pw6Dk7kcHK2ZAyO8EPxSHEyh3t0uFWiPN5y40Fcva+0qxNvnKX/rOhkf0ATKT9PFfAOigLmSdJXDd0SM7m00cRkPuVKGeWRSye50gN7rkE3bobksgUPnRCCfIo/tWgYZKadwOuJLqu937gHX9TSyadNw5ZOmob28flNHJ8uuCofmUHX8qO128ZyZlAUMD10m+Si67ZNReUGRYHgcWyUar3KX31qBk1Z5bYicOLloedTEgjRgqLMoAf1mZASBJ//uVuh7uLc06yj9N8YCxdgbPNpCYsV78IiP+NWGgDJxdq7R8twCTd0opCWfOdrDrr8wDay6VJ4Dx3Qr8iGuFJ0u/A8dKVDe76JDc077DVX9In5Te6QX3biXSo3jTJ/t+TCPHSrhi4ZnhUvKArocyZ9+qE/t1zDWl3Grcf34OieAuY2GrZ0Jh5eRQiJBEExrXVy41WJejFZSG+pSX8QztL/xc0WcinJ2CS98JsED7gHY1sxPfR+DnowNfRLG43QXRBzaYmbvgcMSWFRauseOsDG0I2w5GKxT7LaRSrZ23TboXmHeWO9Vqr8gCig9WJISwlc2mgYfVmslaIAsKwbdHseummgvDJEvHpkMx54XstuueXEFI7tyUNRKS4HTO7xm4rOAsIr1faWZh3uJskEQYLYJZd949nAgE9QDx6v5lyAxaD3qewfsBdUhS0qAvR1Kyo3Y2I4PPStZ7kA3oOiNcllsAPBO6GU4UgufZCZBvtbZYE3V/QJPSDKM+iJBMGBiSzmN5qu3ubM2zeCog4NneFsncsI8tAfPLeGfWNZHJnK48ge7UohKDDKekhzi2z0YQ/L1Tam8umelhIzCCG2uaKLm61QnrPfnEm1S6F2vbNcrpwp4shU3mgc1g/YsV3ebKKldEO3tc2nk1C7lBs8H4Ysl0MTeaSlBE7t21rGh9eg6LhLLtmU1hHWKrlocmJvP+eh0dB5c0VZJ76r949x/4blohseulNyqXIkl1AeuuTpoVNK8cC5dbz8yj0ghOCYXmxzYb2OV4CfPw74t9pk+diKSvs8ZzJhlP4vVlp4ybGpgL/QJReP4KDfJgYA733ZMbznpcf6OhSBGd5zK1pgO6yGzr5TTVk14g+MYchyObInj9P/7Q1brtDNp931Il41FnHCbPpneuhe07iiZGjeYWtQlLFak5FNefddODiRw6WNJjb1LBd2Cc82h2UWFLWmLVq8dS8P3S8oem61jtVaG7cc3wNAC+ilk4nwHrrH0AMmufTToDMPvdulWK60Q2WfsCk2vKwgWfUvvCCE9K3kn8G05HMrWpOwsJKLUQbv1ddkCDI+tvPe8zx0PzkxTjiHXMickZJRMzTvMC8oulptY9qn78KhyRxWa20sV1sopCXDE5T0KsRlrodu/t8ry8VPcnnwnKmfA9pJcWQqj/Or/qmLfmPJWOvglWp7y32adxPmoa83ZMhqF/tCSC45i6fqpB9DdLcKO7azuoceVnIxGlU5gvgdtYsuHew17wRezGQYBkTvBs4GXf24Khmad5gZWltQtNbGHh8Dx06+04tVl3FmfcYBu1du/f92gqLfeW4Ve0sZnJg2+5oc25PHxcBRbGygrHtzKma1qUUrtf566No4NtVMWQwxyNiY06q4dfQgyWUQYEZoU+8F5DXUwonXsId+DD3oJbxB0XLM18xwSi4iKOoDb67oak02BjbwYHrn6YWKyzgz+YUQs6wdMK8EcinJM3Dl5aErahf3PruC157aa7tqODJVwPm1um+PCNOLcb+mdjXRhtzp9lly0SbBmwY9WHLhbcQMpaO9H4Ns0AkhhiE6GFI/BywS4YgZtzyny2Q/ug72A67kIjx0Pry5oqu1tm+uNfPQ67Lq8qxYYDSXkmzGl3lWfk2tvIKiD5/fQLXdwWuv3mu7/dh0Hi2li2W9MIiHqaFzPPRM0piY028PvaWoRpVomIIfFp/gSi76EF1e3GCQYPJIWP0csAdFrZh68mBnuWyXvB4Etw4sH1XJRQuK9vZzHpp32JgmpBv0bpdivS77GvTZUgZJPbDjLIBhHnrOkYHArgS8AqKAHhTlBLu++cwyUhLBK66yZ7OwtrJ+gVHfLBdL0LevBl330JcqLUgJEupYDMmFq6H3vr3odmDGN2xREeB9ZcKu7OLqreYzSVAKtCxJA3G/KmGMWWYVA5q81stOi8AQGXRAyxGv6dV35aYCtUt9Cx+SUgL7JzQv0q2h6x66YyIR86y8AqKALrlwsja+cXoZNx+fcs3rPKoPevDruij76MnWVMq9/dbQlS4WNluYKWZcY+x4GMFBTi66YlyK9zeTJYjteOg5YyNzSC5q76fY9BJe7CDucQNGSa8XYVcn/SggG6p32Oqhs86DQeXtzKtySy7aCeccMcekHa+yf+0x7uZcc+sNnFmu4bWn9roef3BSm7V5MYSHzvsCWAtrZor97TzY6qhY0qtEw+AlPQD+m9ggsS3JxWNQtF82UxzgDYoeFQ29qF+dsLjJQAZFCSF3EkKWCSFPWG6bIoTcRQg5o/+cjPYwNaxzGler4Qw6C4x6BUVzjmkshGhzRP00dJ6H/s1nlgHApZ8DmsE6NJnz9dB9K0V1g56WEoG9U6IkoweDFzdboRtmeWV7AGaHyUE3bmnDoG8hKOolubCNOzXYa94uRosOxR4cBIDMgH/OO4Vd9Vd0HX1QC4s+DeANjts+CuBuSulVAO7Wf48c61zRVX16zExANzjDQ3cYaOax51PuoMVH33gN3nXrUc/nZGmL1qyVe55ZwdE9eVu6opUjU/lwGrpHLxdA08/7WTXJCosWN8N76L6Dg32KqQYJ1gt+Kxp6WkpAShDPFL64GrccZwMfFQ39xIx27j99uQKAP1IyagJfjVJ6L4B1x81vBvAZ/f+fAfCWXT4uLtahAeE9dCa58IOiTskFAN55yxHccHjC8zkzjuk9LUXFfWdXXemKVo7t8U9d9PPQ2bFO91E/B7SNbLOpoNrubEFy0Y6d14GvHzMXt0NGSqCQlnwD5U5Yb3DPIpuYGjfeoOi4r5lxw+EJpJMJPPj8Grpdio5Pn6Ko2O6rzVJKFwBA/+nWGXQIIR8ghDxMCHl4ZWVlmy+nUUgnjTz01VobyQQJLPRgl8nOYRVGvjnHoAdhjKHTjfD9Z9fQUrpcuYVxdE8e1VbHGEvnxGyfy09bBPobEAU0D50Z4bCSS85DSwaG50TPpiUcmsxv+eoon3G30DUklxinLQL2YPCoaOjZlIQbDk/gwefX+7bmyF+NUnoHpfQmSulNMzMzO3oum4Zea2NPMR3Yb+Lm41P4b2++Dq86aU8lZHoXz0MPIuMY9vDPz64gm0rgluPezapYy1vW+dGJrFLP+YNWyaWfWAO2YacISQmCTDLB19CHJCj64dtO4uNvvm7Lf5fnjN8blk1su/hKLgP+Oe8Gtx6fwhPzm8ZA8YELinqwRAjZDwD6z+XdOyRv7Fku/jnoDClB8O6XHnN5RKbksvUgI9M/WYOusys1nJwtubrqWfGqHGT4VZWVskkkSH8n9wB2r3L/FnqU5z2m9wQ15xoUbjg8gVtO7Nny3/GGPcQ9bbHAqTuI+yZm5ZYTe9Cl2lU70PuePdt9tS8DeK/+//cC+NLuHI4/xYzZuW8toEo0CDPLZTseujnFBtDG3B0OyIDwy/YA/IclZ1MSPv0zN+PdPoHaXmBtkRBWQwdYT3QfySWmnls+7R4Uza7q4tqci1d30B4RyQUAXnRkEimJ4FtnNHl54IKihJDPA7gfwClCyCVCyPsB/AaA2wghZwDcpv8eOdaByas1ecvTVKz4ZbkEYR2Y3O1SfdakfwaEX08TILjvw6tOzmCyD5OKrDAPfTyX8r0aceI19ECJ+Yme40kuMV8zz3ExM3viGTewkktLuP7QBL59ZhVA7z/nQL2BUvoOj7v+xS4fSyDscq6mz9fcSSvZiXwKKYlgahubAvuQ5I7Wn0VWuzg0FeShs+g/X3LRPPTBPsnZRrYVuQXwHkM3LBr6dimkJSw4Rg/GXX5ISQmkpcTISi6A1jr74QsbAGIYFN1NmIe+VGlB7nR3KLmk8KUPvgJvfdGhLf8t81TbnS7mNrTc8sNBHrqhoXsMDh6CiS7MKw8bEGV4DYr2GowdF3KcjczMconnmgH2ebsLiwb9+71bsOE2QO/lxKEZQQeYssV5vUBnOqCoKIhrD/BH1wWRTppB0RU9H/5wgIfu19ME0KomB11LZkZoq8HZfNocJmJFVln73MEOim6XQjrpGr8X99J/QLsysTousqoimSChev/EgRcfnYSUIFC7tOdFc0P1rWL52Bf1EvqdeOg7IWORXObWtUvqoCrCQA19CDx0FgzeSkAU4HuqgF4a7ZGqGQe0oKi7UjTOawbcV2RxHxDtpJBJGoPre10RPFTvMpNcLujTf/YU+mXQTcnl0kYDe0uZwCBhNimBkOHW0Nkat2rQ8ylvySWu3jmgGbZ2pwvV0hu83VFjLbcA7kHRo2bQAXMEpdDQfWA69G5JLtvFGhSd22gEyi2ANls0l5I8NfRhGBy8fzyLZILgmv1bk6r8gqJxPtELnBa6o2DcnJ+3rA7+d3u3+eFrZpFMkC3Hm3bKUGroF9bqIASYyvfHoGcsGvrcehMvORau2aRXPjag6cm59GB/6Q9N5vHEx27fUsoioKXveaUtDvpVyU6wDshmlcmjYtBXa7Lxe3sE1uzkJcemtnWu7JShepeZ5FJuKJjKp5HskzFgX856W8XCZjOUhw5oG5JXUHQYPHQA2/qC5tPayD6WpsiQOzTWBp0XN2l3ej/0oNfkM0JyAbZ3ruyUoXqX2fAJADsqKtqN4wC0CURdisAqUUY+nXRVDjI0+SGeerJXlewwBIJ3Qi7lbvcwCsbNGTMZFmclDgzVu8zmigL9y3ABzKDo2ZUagPCTbLx6mgDx/tJbpQcrw5CquRN405rivokB7uyefoxiG1WG7l0u6CdJPw06y8w4u6ylT4aVXLyCg0C89WRecBDQ1xzTqxLAS3JRY9s6l5HP2PPvR+GqZFAYund5EDx0QrSWsIuVFqQECV0KX0gn/T30mH7peS1VAc1zi+smBpiSiyvLJcZrBjTJhTXRA+L93R40hu5dNgx6n1IWGda+JmGDs7zue4w4GzdDeuD0Bo+zceN56KNg3KwSG6UUcxuNHfVdEoRnqNIWAbNadLpPRUWMdFIC0AkdEAW0CTZOo8aQY5z94BUUVdSusUHHEWbY6iOW5WIdFF1tK1iqtPHioz2ZIz/yDN3ZxLyeQfHQwwZEAU1ycZaCM+KsoTPpwT3soYuJmK4Z4M9THQUP3bqBPzG/CQB4kTDoPWHovlkswNZPDR0wDXrYgCigneDOUnAA6KhddGl8u9F5eugdGmvJhTdPdRSKbPKWQdEPn99AIS3h6n3ba4Qn2BpD980ahKAoYBrfw1PhPXTeAF3AOopt6D6OUPhJLr3uRtdLpARBNpXgFBbFPMvF8j1/5MIGbjwyOTKdFvvN0J1NRX103FS/p/fo3tdWNXSA76kC8fXQvfLQ2zFvzgW4M5vkEWjOxT7v5WobpxcrQj/vIUOnob/txYdwZCrfl7JaK6wt5lYkF2PIhUNHb7PBwTE1bnnO4GBA89BHwbg12qNVWMS+5/edXUOXQhj0HjJ0Bv3ETBEnZor9PgxkUgmkk4ktpWN5Sw/x9tClBEE6meAXFsVUZmJYi8kopSOR5cK+5986s4IEAW48MtHnIxod4v3NipB8WsLhyRwSW9AGvTzVURjRxauSVdR4N+cC9A6beqpqp0tBabynFQGmQb+00cSpfWNGp0lB9Aydhz4ofOT1p1DzSEH0gmnodY6nCsQ3KAowLdm9kcV5zYC+kenfk1HYuAHTcQGAFx8V3nkvEQZ9m5ycLW35bwqWdC4rxokeY+OWS0toKuZGRikdCT05n06i3NDGFI7CgGgAyKYSIASgFLjp6FS/D2ekiPc3a8AITFuM8YnulFw6ei5+XAPBjHzarA42PfR4py0SQpDXkxZEQLS3CA+9h3j2BWeeW5w99JTk6mkCxFtmAuytZEdFcgG0KVWFTHJLldSCnSMMeg9hRVGeGnqMT3TnWDK25rgbt7xl/F67o/2Mu+QCADOlDE7OFkFIvK/ABg1h0HtIJplAgrgLbEZBQ9fmqTaM3+NeHcvIpyXU5Y6RsgjEfxMDgD/96ZcYBUaC3iEMeg8hhHDH0I1Clksu7R5LBsR7EwO0zKYu1QKi8ohclQDAvpAzAgS7S/y/WQMGbwzdKHhu+bRk5GMD8S+mYrDgYFNWsa5LTqMguQj6g/DQe0whk7T1xwYsxi3G3mrOkeUyClclgJmT/bY/vh/PLddACMSwB0FkCIPeY3Ipyd0XfBQ89FQScqeLjtpFUkpYslziHTQ7PlOAlCAYyybx0Tdejduv24fj04V+H5YgpgiD3mMKGfcYOtNbja9xM1I2FRVjUmIkcu8B4CXHpvDsr71RtI8V9IR4n00DSJ4zKHoUPHRnC11lBHLvGcKYC3pF/M+mAaOQcTepGoUUPufAZBY3iLuHLhD0EnE29Zhcit+kCoh5UDTFOk3qVZN6D/g4b2ICQa8RZ1OPKWQkbqVoMkG21Ip32Mg7JBe5E//MHoGg14izqcfk00lut8U46+eAu4+NWfof301MIOg18bYiA0ghLUFWu4ZBA0Zjck/OYdBHpTmXQNBLxNnUY5yGDRiNOZOswIb1RB+V5lwCQS8RZ1OPYR0X7ZPgaey1ZC/JRXjoAsHusaPCIkLIeQBVACqADqX0pt04qDjD64k+Ch66Mw+9LSQXgWDX2Y1K0ddSSld34XlGgjxnDJ3S6ca6ShQwm1Q589DjfmUiEPQScTb1mELaPSh6FDz0pJRAWkpwslzivW6BoJfs9GyiAL5GCHmEEPIB3gMIIR8ghDxMCHl4ZWVlhy83/OR1Db3p6Dw4CtJDztI6WO50kSCiLF4g2E12akVeTil9EYA3AvggIeRVzgdQSu+glN5EKb1pZmZmhy83/PA89HanOxLSQ8HSQndUNjGBoJfs6IyilF7Wfy4D+FsAN+/GQcUZI22xbffQR0F6KGSSWK9rQx5GQWYSCHrNts8oQkiBEFJi/wfwegBP7NaBxZVC2j0oWh4RD/3lV07jW2dWsFZra5vYCKxZIOglOzmjZgF8mxDyGIDvAvgKpfSru3NY8SWfcactjor88M5bjkBRKf76kUuQO6OxZoGgl2w7bZFSeg7A9bt4LCNBWkpAShBHYdFoyA8nZ0u46egkPv/di7jh8MRIrFkg6CXijOoxhBDk0/apRYpKR8ZbfectR3B+rYH7zq7FPvdeIOg1o2FFBoxCOmlLW2yPiIcOAG96wX6M51JYrrZHZhMTCHqFOKP6QN7RE10LEI6Gt5pNSfiJFx0EAGRGZBMTCHqFOKP6QD5tH0M3Kho64503HwEg+rgIBLvNbvRyEWyRfDqJetvuoY+ScbtqtoRXn5zBRD7V70MRCGKFMOh9oJCWsKYX2HS7FJ0uHSkPHQD+5L03QSKjITMJBL1itKzIgJDPmB66PKJ9wVNSItYzVAWCfjBaVmRAyKdMDZ0ZdBEgFAgEO0VYkT5QyCTFbE2BQLDrCCvSB/KWNrKiL7hAINgthBXpA/m0BEWlkDtd4aELBIJdQ1iRPsDG0DVlVXjoAoFg1xBWpA8UMuaQCzYseVQqRQUCQXSIPPQ+wDz0O7/9PE7OlgAID10gEOwcYdD7wE3HJnHz8Sl86jvPg1LtNqGhCwSCnSIMeh/YP57DX/78S7Faa+Pup5fw5OUKbjwy2e/DEggEQ44w6H1kupjB219ypN+HIRAIYoK4zhcIBIKYIAy6QCAQxARh0AUCgSAmCIMuEAgEMUEYdIFAIIgJwqALBAJBTBAGXSAQCGKCMOgCgUAQEwhltee9eDFCVgBc2OafTwNY3cXDGRZGcd2juGZgNNc9imsGtr7uo5TSmaAH9dSg7wRCyMOU0pv6fRy9ZhTXPYprBkZz3aO4ZiC6dQvJRSAQCGKCMOgCgUAQE4bJoN/R7wPoE6O47lFcMzCa6x7FNQMRrXtoNHSBQCAQ+DNMHrpAIBAIfBAGXSAQCGLCUBh0QsgbCCHPEEKeI4R8tN/HEwWEkMOEkHsIIU8TQp4khHxIv32KEHIXIeSM/jN2o40IIRIh5PuEkL/Xfx+FNU8QQv6aEHJa/8xfGvd1E0J+Uf9uP0EI+TwhJBvHNRNC7iSELBNCnrDc5rlOQsh/1m3bM4SQ23fy2gNv0AkhEoA/BPBGANcCeAch5Nr+HlUkdAB8hFJ6DYBbAXxQX+dHAdxNKb0KwN3673HjQwCetvw+Cmv+7wC+Sv//9s4mJKooDMPPR5akEVRQmAYaSEFBGRFREZEtyqJp6UJw0T5aBeGqfUSr2hglFbkoKWnVokU7+yMi+rUMtSyF6IcWKfS2OGdxESfCZrzO4XvgMvd+M8P9Hu69L3PPmWGk9cAmgn+y3mZWDxwDtkraCCwA2knT+RKwf1ptRs94jbcDG+J7zsXMmxXzPtCBbcCgpHeSJoFeoJBzTyVH0pikx3H9B+ECrye49sSX9QBH8umwPJhZA3AQ6M6UU3deCuwGLgBImpT0lcS9CX95udjMqoAa4CMJOku6B3yZVi7mWQB6Jf2SNAQMEjJvVlRCoNcDI5nt0VhLFjNrBFqAAWCVpDEIoQ+szK+zsnAWOAH8ztRSd14LTAAX41BTt5nVkrC3pA/AaWAYGAO+SbpDws7TKOZZ0nyrhEC3GWrJftfSzJYAN4Djkr7n3U85MbNDwLikR3n3MsdUAVuA85JagJ+kMdRQlDhmXACagNVArZl15NvVvKCk+VYJgT4KrMlsNxBu1ZLDzBYSwvyqpL5Y/mxmdfH5OmA8r/7KwE7gsJm9Jwyl7TWzK6TtDOGcHpU0ELevEwI+Ze99wJCkCUlTQB+wg7SdsxTzLGm+VUKgPwCazazJzBYRJhD6c+6p5JiZEcZUX0g6k3mqH+iM653ArbnurVxIOimpQVIj4bjeldRBws4Akj4BI2a2LpZageek7T0MbDezmniutxLmiVJ2zlLMsx9oN7NqM2sCmoH7s96LpHm/AG3Aa+At0JV3P2Vy3EW41XoKPIlLG7CCMCv+Jj4uz7vXMvnvAW7H9eSdgc3Aw3i8bwLLUvcGTgEvgWfAZaA6RWfgGmGeYIrwCfzo3zyBrphtr4AD/7Nv/+m/4zhOIlTCkIvjOI7zD3igO47jJIIHuuM4TiJ4oDuO4ySCB7rjOE4ieKA7juMkgge64zhOIvwB45jb74hF12cAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Sequence plot\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "  \n",
+    "# frequencies\n",
+    "DataSet = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n",
+    "\n",
+    "  \n",
+    "# plot title\n",
+    "plt.title('My sequence')\n",
+    "  \n",
+    "# function to show the plot\n",
+    "\n",
+    "plt.plot(DataSet)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +101,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..49bf054c0efa33fcc2b9a69f9f66db126031934a 100644
--- a/module3/exo2/exercice.ipynb
+++ b/module3/exo2/exercice.ipynb
@@ -1,5 +1,2306 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202126</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6434</td>\n",
+       "      <td>3844.0</td>\n",
+       "      <td>9024.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202125</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8033</td>\n",
+       "      <td>5587.0</td>\n",
+       "      <td>10479.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202124</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4855</td>\n",
+       "      <td>3011.0</td>\n",
+       "      <td>6699.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202123</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6710</td>\n",
+       "      <td>4455.0</td>\n",
+       "      <td>8965.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202122</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7879</td>\n",
+       "      <td>5495.0</td>\n",
+       "      <td>10263.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202121</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7827</td>\n",
+       "      <td>5403.0</td>\n",
+       "      <td>10251.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202120</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10278</td>\n",
+       "      <td>7540.0</td>\n",
+       "      <td>13016.0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202119</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9539</td>\n",
+       "      <td>6860.0</td>\n",
+       "      <td>12218.0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202118</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12135</td>\n",
+       "      <td>9165.0</td>\n",
+       "      <td>15105.0</td>\n",
+       "      <td>18</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202117</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12058</td>\n",
+       "      <td>8891.0</td>\n",
+       "      <td>15225.0</td>\n",
+       "      <td>18</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202116</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16505</td>\n",
+       "      <td>12735.0</td>\n",
+       "      <td>20275.0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202115</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19306</td>\n",
+       "      <td>15398.0</td>\n",
+       "      <td>23214.0</td>\n",
+       "      <td>29</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202114</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21073</td>\n",
+       "      <td>17099.0</td>\n",
+       "      <td>25047.0</td>\n",
+       "      <td>32</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202113</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26413</td>\n",
+       "      <td>22094.0</td>\n",
+       "      <td>30732.0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202112</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30658</td>\n",
+       "      <td>25919.0</td>\n",
+       "      <td>35397.0</td>\n",
+       "      <td>46</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202111</td>\n",
+       "      <td>3</td>\n",
+       "      <td>24988</td>\n",
+       "      <td>20718.0</td>\n",
+       "      <td>29258.0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202110</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19539</td>\n",
+       "      <td>15951.0</td>\n",
+       "      <td>23127.0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202109</td>\n",
+       "      <td>3</td>\n",
+       "      <td>17572</td>\n",
+       "      <td>13926.0</td>\n",
+       "      <td>21218.0</td>\n",
+       "      <td>27</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202108</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20882</td>\n",
+       "      <td>16907.0</td>\n",
+       "      <td>24857.0</td>\n",
+       "      <td>32</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202107</td>\n",
+       "      <td>3</td>\n",
+       "      <td>22393</td>\n",
+       "      <td>18303.0</td>\n",
+       "      <td>26483.0</td>\n",
+       "      <td>34</td>\n",
+       "      <td>28.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202106</td>\n",
+       "      <td>3</td>\n",
+       "      <td>23183</td>\n",
+       "      <td>19134.0</td>\n",
+       "      <td>27232.0</td>\n",
+       "      <td>35</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>41.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202105</td>\n",
+       "      <td>3</td>\n",
+       "      <td>22426</td>\n",
+       "      <td>18445.0</td>\n",
+       "      <td>26407.0</td>\n",
+       "      <td>34</td>\n",
+       "      <td>28.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202104</td>\n",
+       "      <td>3</td>\n",
+       "      <td>25804</td>\n",
+       "      <td>21491.0</td>\n",
+       "      <td>30117.0</td>\n",
+       "      <td>39</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202103</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21810</td>\n",
+       "      <td>17894.0</td>\n",
+       "      <td>25726.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202102</td>\n",
+       "      <td>3</td>\n",
+       "      <td>17320</td>\n",
+       "      <td>13906.0</td>\n",
+       "      <td>20734.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202101</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21799</td>\n",
+       "      <td>17778.0</td>\n",
+       "      <td>25820.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202053</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21220</td>\n",
+       "      <td>16498.0</td>\n",
+       "      <td>25942.0</td>\n",
+       "      <td>32</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202052</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16428</td>\n",
+       "      <td>12285.0</td>\n",
+       "      <td>20571.0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202051</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21619</td>\n",
+       "      <td>17370.0</td>\n",
+       "      <td>25868.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202050</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16845</td>\n",
+       "      <td>13220.0</td>\n",
+       "      <td>20470.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1884</th>\n",
+       "      <td>198521</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26096</td>\n",
+       "      <td>19621.0</td>\n",
+       "      <td>32571.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1885</th>\n",
+       "      <td>198520</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27896</td>\n",
+       "      <td>20885.0</td>\n",
+       "      <td>34907.0</td>\n",
+       "      <td>51</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1886</th>\n",
+       "      <td>198519</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43154</td>\n",
+       "      <td>32821.0</td>\n",
+       "      <td>53487.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1887</th>\n",
+       "      <td>198518</td>\n",
+       "      <td>3</td>\n",
+       "      <td>40555</td>\n",
+       "      <td>29935.0</td>\n",
+       "      <td>51175.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1888</th>\n",
+       "      <td>198517</td>\n",
+       "      <td>3</td>\n",
+       "      <td>34053</td>\n",
+       "      <td>24366.0</td>\n",
+       "      <td>43740.0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1889</th>\n",
+       "      <td>198516</td>\n",
+       "      <td>3</td>\n",
+       "      <td>50362</td>\n",
+       "      <td>36451.0</td>\n",
+       "      <td>64273.0</td>\n",
+       "      <td>91</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>116.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1890</th>\n",
+       "      <td>198515</td>\n",
+       "      <td>3</td>\n",
+       "      <td>63881</td>\n",
+       "      <td>45538.0</td>\n",
+       "      <td>82224.0</td>\n",
+       "      <td>116</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1891</th>\n",
+       "      <td>198514</td>\n",
+       "      <td>3</td>\n",
+       "      <td>134545</td>\n",
+       "      <td>114400.0</td>\n",
+       "      <td>154690.0</td>\n",
+       "      <td>244</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1892</th>\n",
+       "      <td>198513</td>\n",
+       "      <td>3</td>\n",
+       "      <td>197206</td>\n",
+       "      <td>176080.0</td>\n",
+       "      <td>218332.0</td>\n",
+       "      <td>357</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1893</th>\n",
+       "      <td>198512</td>\n",
+       "      <td>3</td>\n",
+       "      <td>245240</td>\n",
+       "      <td>223304.0</td>\n",
+       "      <td>267176.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>405.0</td>\n",
+       "      <td>485.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1894</th>\n",
+       "      <td>198511</td>\n",
+       "      <td>3</td>\n",
+       "      <td>276205</td>\n",
+       "      <td>252399.0</td>\n",
+       "      <td>300011.0</td>\n",
+       "      <td>501</td>\n",
+       "      <td>458.0</td>\n",
+       "      <td>544.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1895</th>\n",
+       "      <td>198510</td>\n",
+       "      <td>3</td>\n",
+       "      <td>353231</td>\n",
+       "      <td>326279.0</td>\n",
+       "      <td>380183.0</td>\n",
+       "      <td>640</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1896</th>\n",
+       "      <td>198509</td>\n",
+       "      <td>3</td>\n",
+       "      <td>369895</td>\n",
+       "      <td>341109.0</td>\n",
+       "      <td>398681.0</td>\n",
+       "      <td>670</td>\n",
+       "      <td>618.0</td>\n",
+       "      <td>722.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1897</th>\n",
+       "      <td>198508</td>\n",
+       "      <td>3</td>\n",
+       "      <td>389886</td>\n",
+       "      <td>359529.0</td>\n",
+       "      <td>420243.0</td>\n",
+       "      <td>707</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1898</th>\n",
+       "      <td>198507</td>\n",
+       "      <td>3</td>\n",
+       "      <td>471852</td>\n",
+       "      <td>432599.0</td>\n",
+       "      <td>511105.0</td>\n",
+       "      <td>855</td>\n",
+       "      <td>784.0</td>\n",
+       "      <td>926.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1899</th>\n",
+       "      <td>198506</td>\n",
+       "      <td>3</td>\n",
+       "      <td>565825</td>\n",
+       "      <td>518011.0</td>\n",
+       "      <td>613639.0</td>\n",
+       "      <td>1026</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1113.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1900</th>\n",
+       "      <td>198505</td>\n",
+       "      <td>3</td>\n",
+       "      <td>637302</td>\n",
+       "      <td>592795.0</td>\n",
+       "      <td>681809.0</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1236.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1901</th>\n",
+       "      <td>198504</td>\n",
+       "      <td>3</td>\n",
+       "      <td>424937</td>\n",
+       "      <td>390794.0</td>\n",
+       "      <td>459080.0</td>\n",
+       "      <td>770</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>832.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1902</th>\n",
+       "      <td>198503</td>\n",
+       "      <td>3</td>\n",
+       "      <td>213901</td>\n",
+       "      <td>174689.0</td>\n",
+       "      <td>253113.0</td>\n",
+       "      <td>388</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1903</th>\n",
+       "      <td>198502</td>\n",
+       "      <td>3</td>\n",
+       "      <td>97586</td>\n",
+       "      <td>80949.0</td>\n",
+       "      <td>114223.0</td>\n",
+       "      <td>177</td>\n",
+       "      <td>147.0</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1904</th>\n",
+       "      <td>198501</td>\n",
+       "      <td>3</td>\n",
+       "      <td>85489</td>\n",
+       "      <td>65918.0</td>\n",
+       "      <td>105060.0</td>\n",
+       "      <td>155</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1905</th>\n",
+       "      <td>198452</td>\n",
+       "      <td>3</td>\n",
+       "      <td>84830</td>\n",
+       "      <td>60602.0</td>\n",
+       "      <td>109058.0</td>\n",
+       "      <td>154</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1906</th>\n",
+       "      <td>198451</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101726</td>\n",
+       "      <td>80242.0</td>\n",
+       "      <td>123210.0</td>\n",
+       "      <td>185</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>224.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1907</th>\n",
+       "      <td>198450</td>\n",
+       "      <td>3</td>\n",
+       "      <td>123680</td>\n",
+       "      <td>101401.0</td>\n",
+       "      <td>145959.0</td>\n",
+       "      <td>225</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1908</th>\n",
+       "      <td>198449</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101073</td>\n",
+       "      <td>81684.0</td>\n",
+       "      <td>120462.0</td>\n",
+       "      <td>184</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1909</th>\n",
+       "      <td>198448</td>\n",
+       "      <td>3</td>\n",
+       "      <td>78620</td>\n",
+       "      <td>60634.0</td>\n",
+       "      <td>96606.0</td>\n",
+       "      <td>143</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>176.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1910</th>\n",
+       "      <td>198447</td>\n",
+       "      <td>3</td>\n",
+       "      <td>72029</td>\n",
+       "      <td>54274.0</td>\n",
+       "      <td>89784.0</td>\n",
+       "      <td>131</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>163.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1911</th>\n",
+       "      <td>198446</td>\n",
+       "      <td>3</td>\n",
+       "      <td>87330</td>\n",
+       "      <td>67686.0</td>\n",
+       "      <td>106974.0</td>\n",
+       "      <td>159</td>\n",
+       "      <td>123.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1912</th>\n",
+       "      <td>198445</td>\n",
+       "      <td>3</td>\n",
+       "      <td>135223</td>\n",
+       "      <td>101414.0</td>\n",
+       "      <td>169032.0</td>\n",
+       "      <td>246</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1913</th>\n",
+       "      <td>198444</td>\n",
+       "      <td>3</td>\n",
+       "      <td>68422</td>\n",
+       "      <td>20056.0</td>\n",
+       "      <td>116788.0</td>\n",
+       "      <td>125</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>213.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1914 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202126          3    6434    3844.0    9024.0      10         6.0   \n",
+       "1     202125          3    8033    5587.0   10479.0      12         8.0   \n",
+       "2     202124          3    4855    3011.0    6699.0       7         4.0   \n",
+       "3     202123          3    6710    4455.0    8965.0      10         7.0   \n",
+       "4     202122          3    7879    5495.0   10263.0      12         8.0   \n",
+       "5     202121          3    7827    5403.0   10251.0      12         8.0   \n",
+       "6     202120          3   10278    7540.0   13016.0      16        12.0   \n",
+       "7     202119          3    9539    6860.0   12218.0      14        10.0   \n",
+       "8     202118          3   12135    9165.0   15105.0      18        14.0   \n",
+       "9     202117          3   12058    8891.0   15225.0      18        13.0   \n",
+       "10    202116          3   16505   12735.0   20275.0      25        19.0   \n",
+       "11    202115          3   19306   15398.0   23214.0      29        23.0   \n",
+       "12    202114          3   21073   17099.0   25047.0      32        26.0   \n",
+       "13    202113          3   26413   22094.0   30732.0      40        33.0   \n",
+       "14    202112          3   30658   25919.0   35397.0      46        39.0   \n",
+       "15    202111          3   24988   20718.0   29258.0      38        32.0   \n",
+       "16    202110          3   19539   15951.0   23127.0      30        25.0   \n",
+       "17    202109          3   17572   13926.0   21218.0      27        21.0   \n",
+       "18    202108          3   20882   16907.0   24857.0      32        26.0   \n",
+       "19    202107          3   22393   18303.0   26483.0      34        28.0   \n",
+       "20    202106          3   23183   19134.0   27232.0      35        29.0   \n",
+       "21    202105          3   22426   18445.0   26407.0      34        28.0   \n",
+       "22    202104          3   25804   21491.0   30117.0      39        32.0   \n",
+       "23    202103          3   21810   17894.0   25726.0      33        27.0   \n",
+       "24    202102          3   17320   13906.0   20734.0      26        21.0   \n",
+       "25    202101          3   21799   17778.0   25820.0      33        27.0   \n",
+       "26    202053          3   21220   16498.0   25942.0      32        25.0   \n",
+       "27    202052          3   16428   12285.0   20571.0      25        19.0   \n",
+       "28    202051          3   21619   17370.0   25868.0      33        27.0   \n",
+       "29    202050          3   16845   13220.0   20470.0      26        20.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1884  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1885  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1886  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1887  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1888  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1889  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1890  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1891  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1892  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1893  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1894  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1895  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1896  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1897  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1898  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1899  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1900  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1901  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1902  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1903  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1904  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1905  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1906  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1907  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1908  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1909  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1910  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1911  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1912  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1913  198444          3   68422   20056.0  116788.0     125        37.0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          14.0        FR   France  \n",
+       "1          16.0        FR   France  \n",
+       "2          10.0        FR   France  \n",
+       "3          13.0        FR   France  \n",
+       "4          16.0        FR   France  \n",
+       "5          16.0        FR   France  \n",
+       "6          20.0        FR   France  \n",
+       "7          18.0        FR   France  \n",
+       "8          22.0        FR   France  \n",
+       "9          23.0        FR   France  \n",
+       "10         31.0        FR   France  \n",
+       "11         35.0        FR   France  \n",
+       "12         38.0        FR   France  \n",
+       "13         47.0        FR   France  \n",
+       "14         53.0        FR   France  \n",
+       "15         44.0        FR   France  \n",
+       "16         35.0        FR   France  \n",
+       "17         33.0        FR   France  \n",
+       "18         38.0        FR   France  \n",
+       "19         40.0        FR   France  \n",
+       "20         41.0        FR   France  \n",
+       "21         40.0        FR   France  \n",
+       "22         46.0        FR   France  \n",
+       "23         39.0        FR   France  \n",
+       "24         31.0        FR   France  \n",
+       "25         39.0        FR   France  \n",
+       "26         39.0        FR   France  \n",
+       "27         31.0        FR   France  \n",
+       "28         39.0        FR   France  \n",
+       "29         32.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1884       59.0        FR   France  \n",
+       "1885       64.0        FR   France  \n",
+       "1886       97.0        FR   France  \n",
+       "1887       93.0        FR   France  \n",
+       "1888       80.0        FR   France  \n",
+       "1889      116.0        FR   France  \n",
+       "1890      149.0        FR   France  \n",
+       "1891      281.0        FR   France  \n",
+       "1892      395.0        FR   France  \n",
+       "1893      485.0        FR   France  \n",
+       "1894      544.0        FR   France  \n",
+       "1895      689.0        FR   France  \n",
+       "1896      722.0        FR   France  \n",
+       "1897      762.0        FR   France  \n",
+       "1898      926.0        FR   France  \n",
+       "1899     1113.0        FR   France  \n",
+       "1900     1236.0        FR   France  \n",
+       "1901      832.0        FR   France  \n",
+       "1902      459.0        FR   France  \n",
+       "1903      207.0        FR   France  \n",
+       "1904      190.0        FR   France  \n",
+       "1905      198.0        FR   France  \n",
+       "1906      224.0        FR   France  \n",
+       "1907      266.0        FR   France  \n",
+       "1908      219.0        FR   France  \n",
+       "1909      176.0        FR   France  \n",
+       "1910      163.0        FR   France  \n",
+       "1911      195.0        FR   France  \n",
+       "1912      308.0        FR   France  \n",
+       "1913      213.0        FR   France  \n",
+       "\n",
+       "[1914 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1677</th>\n",
+       "      <td>198919</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator  inc  inc_low  inc_up  inc100  inc100_low  inc100_up  \\\n",
+       "1677  198919          3    0      NaN     NaN       0         NaN        NaN   \n",
+       "\n",
+       "     geo_insee geo_name  \n",
+       "1677        FR   France  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202126</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6434</td>\n",
+       "      <td>3844.0</td>\n",
+       "      <td>9024.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202125</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8033</td>\n",
+       "      <td>5587.0</td>\n",
+       "      <td>10479.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202124</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4855</td>\n",
+       "      <td>3011.0</td>\n",
+       "      <td>6699.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202123</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6710</td>\n",
+       "      <td>4455.0</td>\n",
+       "      <td>8965.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202122</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7879</td>\n",
+       "      <td>5495.0</td>\n",
+       "      <td>10263.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202121</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7827</td>\n",
+       "      <td>5403.0</td>\n",
+       "      <td>10251.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202120</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10278</td>\n",
+       "      <td>7540.0</td>\n",
+       "      <td>13016.0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202119</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9539</td>\n",
+       "      <td>6860.0</td>\n",
+       "      <td>12218.0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202118</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12135</td>\n",
+       "      <td>9165.0</td>\n",
+       "      <td>15105.0</td>\n",
+       "      <td>18</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202117</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12058</td>\n",
+       "      <td>8891.0</td>\n",
+       "      <td>15225.0</td>\n",
+       "      <td>18</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202116</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16505</td>\n",
+       "      <td>12735.0</td>\n",
+       "      <td>20275.0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202115</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19306</td>\n",
+       "      <td>15398.0</td>\n",
+       "      <td>23214.0</td>\n",
+       "      <td>29</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202114</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21073</td>\n",
+       "      <td>17099.0</td>\n",
+       "      <td>25047.0</td>\n",
+       "      <td>32</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202113</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26413</td>\n",
+       "      <td>22094.0</td>\n",
+       "      <td>30732.0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202112</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30658</td>\n",
+       "      <td>25919.0</td>\n",
+       "      <td>35397.0</td>\n",
+       "      <td>46</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202111</td>\n",
+       "      <td>3</td>\n",
+       "      <td>24988</td>\n",
+       "      <td>20718.0</td>\n",
+       "      <td>29258.0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202110</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19539</td>\n",
+       "      <td>15951.0</td>\n",
+       "      <td>23127.0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202109</td>\n",
+       "      <td>3</td>\n",
+       "      <td>17572</td>\n",
+       "      <td>13926.0</td>\n",
+       "      <td>21218.0</td>\n",
+       "      <td>27</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202108</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20882</td>\n",
+       "      <td>16907.0</td>\n",
+       "      <td>24857.0</td>\n",
+       "      <td>32</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202107</td>\n",
+       "      <td>3</td>\n",
+       "      <td>22393</td>\n",
+       "      <td>18303.0</td>\n",
+       "      <td>26483.0</td>\n",
+       "      <td>34</td>\n",
+       "      <td>28.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202106</td>\n",
+       "      <td>3</td>\n",
+       "      <td>23183</td>\n",
+       "      <td>19134.0</td>\n",
+       "      <td>27232.0</td>\n",
+       "      <td>35</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>41.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202105</td>\n",
+       "      <td>3</td>\n",
+       "      <td>22426</td>\n",
+       "      <td>18445.0</td>\n",
+       "      <td>26407.0</td>\n",
+       "      <td>34</td>\n",
+       "      <td>28.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202104</td>\n",
+       "      <td>3</td>\n",
+       "      <td>25804</td>\n",
+       "      <td>21491.0</td>\n",
+       "      <td>30117.0</td>\n",
+       "      <td>39</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202103</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21810</td>\n",
+       "      <td>17894.0</td>\n",
+       "      <td>25726.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202102</td>\n",
+       "      <td>3</td>\n",
+       "      <td>17320</td>\n",
+       "      <td>13906.0</td>\n",
+       "      <td>20734.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202101</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21799</td>\n",
+       "      <td>17778.0</td>\n",
+       "      <td>25820.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202053</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21220</td>\n",
+       "      <td>16498.0</td>\n",
+       "      <td>25942.0</td>\n",
+       "      <td>32</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202052</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16428</td>\n",
+       "      <td>12285.0</td>\n",
+       "      <td>20571.0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202051</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21619</td>\n",
+       "      <td>17370.0</td>\n",
+       "      <td>25868.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202050</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16845</td>\n",
+       "      <td>13220.0</td>\n",
+       "      <td>20470.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1884</th>\n",
+       "      <td>198521</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26096</td>\n",
+       "      <td>19621.0</td>\n",
+       "      <td>32571.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1885</th>\n",
+       "      <td>198520</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27896</td>\n",
+       "      <td>20885.0</td>\n",
+       "      <td>34907.0</td>\n",
+       "      <td>51</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1886</th>\n",
+       "      <td>198519</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43154</td>\n",
+       "      <td>32821.0</td>\n",
+       "      <td>53487.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1887</th>\n",
+       "      <td>198518</td>\n",
+       "      <td>3</td>\n",
+       "      <td>40555</td>\n",
+       "      <td>29935.0</td>\n",
+       "      <td>51175.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1888</th>\n",
+       "      <td>198517</td>\n",
+       "      <td>3</td>\n",
+       "      <td>34053</td>\n",
+       "      <td>24366.0</td>\n",
+       "      <td>43740.0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1889</th>\n",
+       "      <td>198516</td>\n",
+       "      <td>3</td>\n",
+       "      <td>50362</td>\n",
+       "      <td>36451.0</td>\n",
+       "      <td>64273.0</td>\n",
+       "      <td>91</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>116.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1890</th>\n",
+       "      <td>198515</td>\n",
+       "      <td>3</td>\n",
+       "      <td>63881</td>\n",
+       "      <td>45538.0</td>\n",
+       "      <td>82224.0</td>\n",
+       "      <td>116</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1891</th>\n",
+       "      <td>198514</td>\n",
+       "      <td>3</td>\n",
+       "      <td>134545</td>\n",
+       "      <td>114400.0</td>\n",
+       "      <td>154690.0</td>\n",
+       "      <td>244</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1892</th>\n",
+       "      <td>198513</td>\n",
+       "      <td>3</td>\n",
+       "      <td>197206</td>\n",
+       "      <td>176080.0</td>\n",
+       "      <td>218332.0</td>\n",
+       "      <td>357</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1893</th>\n",
+       "      <td>198512</td>\n",
+       "      <td>3</td>\n",
+       "      <td>245240</td>\n",
+       "      <td>223304.0</td>\n",
+       "      <td>267176.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>405.0</td>\n",
+       "      <td>485.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1894</th>\n",
+       "      <td>198511</td>\n",
+       "      <td>3</td>\n",
+       "      <td>276205</td>\n",
+       "      <td>252399.0</td>\n",
+       "      <td>300011.0</td>\n",
+       "      <td>501</td>\n",
+       "      <td>458.0</td>\n",
+       "      <td>544.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1895</th>\n",
+       "      <td>198510</td>\n",
+       "      <td>3</td>\n",
+       "      <td>353231</td>\n",
+       "      <td>326279.0</td>\n",
+       "      <td>380183.0</td>\n",
+       "      <td>640</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1896</th>\n",
+       "      <td>198509</td>\n",
+       "      <td>3</td>\n",
+       "      <td>369895</td>\n",
+       "      <td>341109.0</td>\n",
+       "      <td>398681.0</td>\n",
+       "      <td>670</td>\n",
+       "      <td>618.0</td>\n",
+       "      <td>722.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1897</th>\n",
+       "      <td>198508</td>\n",
+       "      <td>3</td>\n",
+       "      <td>389886</td>\n",
+       "      <td>359529.0</td>\n",
+       "      <td>420243.0</td>\n",
+       "      <td>707</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1898</th>\n",
+       "      <td>198507</td>\n",
+       "      <td>3</td>\n",
+       "      <td>471852</td>\n",
+       "      <td>432599.0</td>\n",
+       "      <td>511105.0</td>\n",
+       "      <td>855</td>\n",
+       "      <td>784.0</td>\n",
+       "      <td>926.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1899</th>\n",
+       "      <td>198506</td>\n",
+       "      <td>3</td>\n",
+       "      <td>565825</td>\n",
+       "      <td>518011.0</td>\n",
+       "      <td>613639.0</td>\n",
+       "      <td>1026</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1113.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1900</th>\n",
+       "      <td>198505</td>\n",
+       "      <td>3</td>\n",
+       "      <td>637302</td>\n",
+       "      <td>592795.0</td>\n",
+       "      <td>681809.0</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1236.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1901</th>\n",
+       "      <td>198504</td>\n",
+       "      <td>3</td>\n",
+       "      <td>424937</td>\n",
+       "      <td>390794.0</td>\n",
+       "      <td>459080.0</td>\n",
+       "      <td>770</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>832.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1902</th>\n",
+       "      <td>198503</td>\n",
+       "      <td>3</td>\n",
+       "      <td>213901</td>\n",
+       "      <td>174689.0</td>\n",
+       "      <td>253113.0</td>\n",
+       "      <td>388</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1903</th>\n",
+       "      <td>198502</td>\n",
+       "      <td>3</td>\n",
+       "      <td>97586</td>\n",
+       "      <td>80949.0</td>\n",
+       "      <td>114223.0</td>\n",
+       "      <td>177</td>\n",
+       "      <td>147.0</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1904</th>\n",
+       "      <td>198501</td>\n",
+       "      <td>3</td>\n",
+       "      <td>85489</td>\n",
+       "      <td>65918.0</td>\n",
+       "      <td>105060.0</td>\n",
+       "      <td>155</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1905</th>\n",
+       "      <td>198452</td>\n",
+       "      <td>3</td>\n",
+       "      <td>84830</td>\n",
+       "      <td>60602.0</td>\n",
+       "      <td>109058.0</td>\n",
+       "      <td>154</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1906</th>\n",
+       "      <td>198451</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101726</td>\n",
+       "      <td>80242.0</td>\n",
+       "      <td>123210.0</td>\n",
+       "      <td>185</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>224.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1907</th>\n",
+       "      <td>198450</td>\n",
+       "      <td>3</td>\n",
+       "      <td>123680</td>\n",
+       "      <td>101401.0</td>\n",
+       "      <td>145959.0</td>\n",
+       "      <td>225</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1908</th>\n",
+       "      <td>198449</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101073</td>\n",
+       "      <td>81684.0</td>\n",
+       "      <td>120462.0</td>\n",
+       "      <td>184</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1909</th>\n",
+       "      <td>198448</td>\n",
+       "      <td>3</td>\n",
+       "      <td>78620</td>\n",
+       "      <td>60634.0</td>\n",
+       "      <td>96606.0</td>\n",
+       "      <td>143</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>176.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1910</th>\n",
+       "      <td>198447</td>\n",
+       "      <td>3</td>\n",
+       "      <td>72029</td>\n",
+       "      <td>54274.0</td>\n",
+       "      <td>89784.0</td>\n",
+       "      <td>131</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>163.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1911</th>\n",
+       "      <td>198446</td>\n",
+       "      <td>3</td>\n",
+       "      <td>87330</td>\n",
+       "      <td>67686.0</td>\n",
+       "      <td>106974.0</td>\n",
+       "      <td>159</td>\n",
+       "      <td>123.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1912</th>\n",
+       "      <td>198445</td>\n",
+       "      <td>3</td>\n",
+       "      <td>135223</td>\n",
+       "      <td>101414.0</td>\n",
+       "      <td>169032.0</td>\n",
+       "      <td>246</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1913</th>\n",
+       "      <td>198444</td>\n",
+       "      <td>3</td>\n",
+       "      <td>68422</td>\n",
+       "      <td>20056.0</td>\n",
+       "      <td>116788.0</td>\n",
+       "      <td>125</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>213.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1913 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202126          3    6434    3844.0    9024.0      10         6.0   \n",
+       "1     202125          3    8033    5587.0   10479.0      12         8.0   \n",
+       "2     202124          3    4855    3011.0    6699.0       7         4.0   \n",
+       "3     202123          3    6710    4455.0    8965.0      10         7.0   \n",
+       "4     202122          3    7879    5495.0   10263.0      12         8.0   \n",
+       "5     202121          3    7827    5403.0   10251.0      12         8.0   \n",
+       "6     202120          3   10278    7540.0   13016.0      16        12.0   \n",
+       "7     202119          3    9539    6860.0   12218.0      14        10.0   \n",
+       "8     202118          3   12135    9165.0   15105.0      18        14.0   \n",
+       "9     202117          3   12058    8891.0   15225.0      18        13.0   \n",
+       "10    202116          3   16505   12735.0   20275.0      25        19.0   \n",
+       "11    202115          3   19306   15398.0   23214.0      29        23.0   \n",
+       "12    202114          3   21073   17099.0   25047.0      32        26.0   \n",
+       "13    202113          3   26413   22094.0   30732.0      40        33.0   \n",
+       "14    202112          3   30658   25919.0   35397.0      46        39.0   \n",
+       "15    202111          3   24988   20718.0   29258.0      38        32.0   \n",
+       "16    202110          3   19539   15951.0   23127.0      30        25.0   \n",
+       "17    202109          3   17572   13926.0   21218.0      27        21.0   \n",
+       "18    202108          3   20882   16907.0   24857.0      32        26.0   \n",
+       "19    202107          3   22393   18303.0   26483.0      34        28.0   \n",
+       "20    202106          3   23183   19134.0   27232.0      35        29.0   \n",
+       "21    202105          3   22426   18445.0   26407.0      34        28.0   \n",
+       "22    202104          3   25804   21491.0   30117.0      39        32.0   \n",
+       "23    202103          3   21810   17894.0   25726.0      33        27.0   \n",
+       "24    202102          3   17320   13906.0   20734.0      26        21.0   \n",
+       "25    202101          3   21799   17778.0   25820.0      33        27.0   \n",
+       "26    202053          3   21220   16498.0   25942.0      32        25.0   \n",
+       "27    202052          3   16428   12285.0   20571.0      25        19.0   \n",
+       "28    202051          3   21619   17370.0   25868.0      33        27.0   \n",
+       "29    202050          3   16845   13220.0   20470.0      26        20.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1884  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1885  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1886  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1887  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1888  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1889  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1890  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1891  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1892  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1893  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1894  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1895  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1896  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1897  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1898  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1899  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1900  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1901  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1902  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1903  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1904  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1905  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1906  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1907  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1908  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1909  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1910  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1911  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1912  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1913  198444          3   68422   20056.0  116788.0     125        37.0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          14.0        FR   France  \n",
+       "1          16.0        FR   France  \n",
+       "2          10.0        FR   France  \n",
+       "3          13.0        FR   France  \n",
+       "4          16.0        FR   France  \n",
+       "5          16.0        FR   France  \n",
+       "6          20.0        FR   France  \n",
+       "7          18.0        FR   France  \n",
+       "8          22.0        FR   France  \n",
+       "9          23.0        FR   France  \n",
+       "10         31.0        FR   France  \n",
+       "11         35.0        FR   France  \n",
+       "12         38.0        FR   France  \n",
+       "13         47.0        FR   France  \n",
+       "14         53.0        FR   France  \n",
+       "15         44.0        FR   France  \n",
+       "16         35.0        FR   France  \n",
+       "17         33.0        FR   France  \n",
+       "18         38.0        FR   France  \n",
+       "19         40.0        FR   France  \n",
+       "20         41.0        FR   France  \n",
+       "21         40.0        FR   France  \n",
+       "22         46.0        FR   France  \n",
+       "23         39.0        FR   France  \n",
+       "24         31.0        FR   France  \n",
+       "25         39.0        FR   France  \n",
+       "26         39.0        FR   France  \n",
+       "27         31.0        FR   France  \n",
+       "28         39.0        FR   France  \n",
+       "29         32.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1884       59.0        FR   France  \n",
+       "1885       64.0        FR   France  \n",
+       "1886       97.0        FR   France  \n",
+       "1887       93.0        FR   France  \n",
+       "1888       80.0        FR   France  \n",
+       "1889      116.0        FR   France  \n",
+       "1890      149.0        FR   France  \n",
+       "1891      281.0        FR   France  \n",
+       "1892      395.0        FR   France  \n",
+       "1893      485.0        FR   France  \n",
+       "1894      544.0        FR   France  \n",
+       "1895      689.0        FR   France  \n",
+       "1896      722.0        FR   France  \n",
+       "1897      762.0        FR   France  \n",
+       "1898      926.0        FR   France  \n",
+       "1899     1113.0        FR   France  \n",
+       "1900     1236.0        FR   France  \n",
+       "1901      832.0        FR   France  \n",
+       "1902      459.0        FR   France  \n",
+       "1903      207.0        FR   France  \n",
+       "1904      190.0        FR   France  \n",
+       "1905      198.0        FR   France  \n",
+       "1906      224.0        FR   France  \n",
+       "1907      266.0        FR   France  \n",
+       "1908      219.0        FR   France  \n",
+       "1909      176.0        FR   France  \n",
+       "1910      163.0        FR   France  \n",
+       "1911      195.0        FR   France  \n",
+       "1912      308.0        FR   France  \n",
+       "1913      213.0        FR   France  \n",
+       "\n",
+       "[1913 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = raw_data.dropna().copy()\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_week(year_and_week_int):\n",
+    "    year_and_week_str = str(year_and_week_int)\n",
+    "    year = int(year_and_week_str[:4])\n",
+    "    week = int(year_and_week_str[4:])\n",
+    "    w = isoweek.Week(year, week)\n",
+    "    return pd.Period(w.day(0), 'W')\n",
+    "\n",
+    "data['period'] = [convert_week(yw) for yw in data['week']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_data = data.set_index('period').sort_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n"
+     ]
+    }
+   ],
+   "source": [
+    "periods = sorted_data.index\n",
+    "for p1, p2 in zip(periods[:-1], periods[1:]):\n",
+    "    delta = p2.to_timestamp() - p1.end_time\n",
+    "    if delta > pd.Timedelta('1s'):\n",
+    "        print(p1, p2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0abd0ccba8>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0abaf595f8>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'][-200:].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    " first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n",
+    "                     for y in range(1985,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    " year = []\n",
+    "yearly_incidence = []\n",
+    "for week1, week2 in zip(first_august_week[:-1],\n",
+    "                        first_august_week[1:]):\n",
+    "    one_year = sorted_data['inc'][week1:week2-1]\n",
+    "    assert abs(len(one_year)-52) < 2\n",
+    "    yearly_incidence.append(one_year.sum())\n",
+    "    year.append(week2.year)\n",
+    "yearly_incidence = pd.Series(data=yearly_incidence, index=year)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0abaeb3048>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.plot(style='*')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2014    1600941\n",
+       "1991    1659249\n",
+       "1995    1840410\n",
+       "2020    2053781\n",
+       "2012    2175217\n",
+       "2003    2234584\n",
+       "2019    2254386\n",
+       "2006    2307352\n",
+       "2017    2321583\n",
+       "2001    2529279\n",
+       "1992    2574578\n",
+       "1993    2703886\n",
+       "2018    2705325\n",
+       "1988    2765617\n",
+       "2007    2780164\n",
+       "1987    2855570\n",
+       "2016    2856393\n",
+       "2011    2857040\n",
+       "2008    2973918\n",
+       "1998    3034904\n",
+       "2002    3125418\n",
+       "2009    3444020\n",
+       "1994    3514763\n",
+       "1996    3539413\n",
+       "2004    3567744\n",
+       "1997    3620066\n",
+       "2015    3654892\n",
+       "2000    3826372\n",
+       "2005    3835025\n",
+       "1999    3908112\n",
+       "2010    4111392\n",
+       "2013    4182691\n",
+       "1986    5115251\n",
+       "1990    5235827\n",
+       "1989    5466192\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "yearly_incidence.sort_values()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'geo_insee'"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "min(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +2317,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..1fd533de0c053d1872e2231958377ac10b33e051 100644
--- a/module3/exo3/exercice.ipynb
+++ b/module3/exo3/exercice.ipynb
@@ -1,5 +1,1510 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting arviz\n",
+      "  Downloading arviz-0.11.2-py3-none-any.whl (1.6 MB)\n",
+      "\u001b[K     |████████████████████████████████| 1.6 MB 21.0 MB/s eta 0:00:01\n",
+      "\u001b[?25hCollecting typing-extensions<4,>=3.7.4.3\n",
+      "  Downloading typing_extensions-3.10.0.0-py3-none-any.whl (26 kB)\n",
+      "Collecting xarray>=0.16.1\n",
+      "  Downloading xarray-0.16.2-py3-none-any.whl (736 kB)\n",
+      "\u001b[K     |████████████████████████████████| 736 kB 41.3 MB/s eta 0:00:01\n",
+      "\u001b[?25hCollecting matplotlib>=3.0\n",
+      "  Downloading matplotlib-3.3.4-cp36-cp36m-manylinux1_x86_64.whl (11.5 MB)\n",
+      "\u001b[K     |████████████████████████████████| 11.5 MB 45.8 MB/s eta 0:00:01\n",
+      "\u001b[?25hCollecting pandas>=0.23\n",
+      "  Downloading pandas-1.1.5-cp36-cp36m-manylinux1_x86_64.whl (9.5 MB)\n",
+      "\u001b[K     |████████████████████████████████| 9.5 MB 67.4 MB/s eta 0:00:01\n",
+      "\u001b[?25hRequirement already satisfied: setuptools>=38.4 in /opt/conda/lib/python3.6/site-packages (from arviz) (45.2.0.post20200209)\n",
+      "Requirement already satisfied: packaging in /opt/conda/lib/python3.6/site-packages (from arviz) (20.1)\n",
+      "Collecting netcdf4\n",
+      "  Downloading netCDF4-1.5.7-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.7 MB)\n",
+      "\u001b[K     |████████████████████████████████| 4.7 MB 34.4 MB/s eta 0:00:01    |▍                               | 51 kB 35.1 MB/s eta 0:00:01\n",
+      "\u001b[?25hRequirement already satisfied: numpy>=1.12 in /opt/conda/lib/python3.6/site-packages (from arviz) (1.15.2)\n",
+      "Requirement already satisfied: scipy>=0.19 in /opt/conda/lib/python3.6/site-packages (from arviz) (1.1.0)\n",
+      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.0->arviz) (2.4.6)\n",
+      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.0->arviz) (7.0.0)\n",
+      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.0->arviz) (0.10.0)\n",
+      "Requirement already satisfied: python-dateutil>=2.1 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.0->arviz) (2.8.1)\n",
+      "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.0->arviz) (1.1.0)\n",
+      "Requirement already satisfied: pytz>=2017.2 in /opt/conda/lib/python3.6/site-packages (from pandas>=0.23->arviz) (2019.3)\n",
+      "Requirement already satisfied: six in /opt/conda/lib/python3.6/site-packages (from packaging->arviz) (1.14.0)\n",
+      "Collecting cftime\n",
+      "  Downloading cftime-1.5.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (216 kB)\n",
+      "\u001b[K     |████████████████████████████████| 216 kB 70.9 MB/s eta 0:00:01\n",
+      "\u001b[31mERROR: pandas 1.1.5 has requirement numpy>=1.15.4, but you'll have numpy 1.15.2 which is incompatible.\u001b[0m\n",
+      "\u001b[?25hInstalling collected packages: typing-extensions, pandas, xarray, matplotlib, cftime, netcdf4, arviz\n",
+      "  Attempting uninstall: pandas\n",
+      "    Found existing installation: pandas 0.22.0\n",
+      "    Uninstalling pandas-0.22.0:\n",
+      "      Successfully uninstalled pandas-0.22.0\n",
+      "  Attempting uninstall: matplotlib\n",
+      "    Found existing installation: matplotlib 2.2.3\n",
+      "    Uninstalling matplotlib-2.2.3:\n",
+      "      Successfully uninstalled matplotlib-2.2.3\n",
+      "Successfully installed arviz-0.11.2 cftime-1.5.0 matplotlib-3.3.4 netcdf4-1.5.7 pandas-1.1.5 typing-extensions-3.10.0.0 xarray-0.16.2\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install arviz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting git+https://github.com/pymc-devs/pymc3\n",
+      "  Cloning https://github.com/pymc-devs/pymc3 to /tmp/pip-req-build-ygnbehco\n",
+      "  Running command git clone -q https://github.com/pymc-devs/pymc3 /tmp/pip-req-build-ygnbehco\n",
+      "  Running command git submodule update --init --recursive -q\n",
+      "  Installing build dependencies ... \u001b[?25ldone\n",
+      "\u001b[?25h  Getting requirements to build wheel ... \u001b[?25ldone\n",
+      "\u001b[?25h    Preparing wheel metadata ... \u001b[?25ldone\n",
+      "\u001b[31mERROR: Package 'pymc3' requires a different Python: 3.6.4 not in '>=3.7'\u001b[0m\n",
+      "\u001b[?25hNote: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install git+https://github.com/pymc-devs/pymc3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: bokeh in /opt/conda/lib/python3.6/site-packages (0.12.16)\n",
+      "Requirement already satisfied: six>=1.5.2 in /opt/conda/lib/python3.6/site-packages (from bokeh) (1.14.0)\n",
+      "Requirement already satisfied: PyYAML>=3.10 in /opt/conda/lib/python3.6/site-packages (from bokeh) (5.3)\n",
+      "Requirement already satisfied: python-dateutil>=2.1 in /opt/conda/lib/python3.6/site-packages (from bokeh) (2.8.1)\n",
+      "Requirement already satisfied: Jinja2>=2.7 in /opt/conda/lib/python3.6/site-packages (from bokeh) (2.11.0)\n",
+      "Requirement already satisfied: numpy>=1.7.1 in /opt/conda/lib/python3.6/site-packages (from bokeh) (1.15.2)\n",
+      "Requirement already satisfied: packaging>=16.8 in /opt/conda/lib/python3.6/site-packages (from bokeh) (20.1)\n",
+      "Requirement already satisfied: tornado>=4.3 in /opt/conda/lib/python3.6/site-packages (from bokeh) (6.0.3)\n",
+      "Requirement already satisfied: MarkupSafe>=0.23 in /opt/conda/lib/python3.6/site-packages (from Jinja2>=2.7->bokeh) (1.1.1)\n",
+      "Requirement already satisfied: pyparsing>=2.0.2 in /opt/conda/lib/python3.6/site-packages (from packaging>=16.8->bokeh) (2.4.6)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install bokeh"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting package metadata (current_repodata.json): - Killed\n",
+      "\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "conda create -n py35 python=3.5 anaconda"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting package metadata (current_repodata.json): \\ Killed\n",
+      "\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "conda install spyder"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting package metadata (current_repodata.json): | Killed\n",
+      "\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "conda install theano"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting package metadata (current_repodata.json): / Killed\n",
+      "\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "conda install tensorflow"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting package metadata (current_repodata.json): | Killed\n",
+      "\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "conda install keras"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting pymc3\n",
+      "  Downloading pymc3-3.10.0-py3-none-any.whl (1.9 MB)\n",
+      "\u001b[K     |████████████████████████████████| 1.9 MB 13.5 MB/s eta 0:00:01\n",
+      "\u001b[?25hRequirement already satisfied: pandas>=0.18.0 in /opt/conda/lib/python3.6/site-packages (from pymc3) (1.1.5)\n",
+      "Collecting theano-pymc==1.0.11\n",
+      "  Downloading Theano-PyMC-1.0.11.tar.gz (2.8 MB)\n",
+      "\u001b[K     |████████████████████████████████| 2.8 MB 54.3 MB/s eta 0:00:01\n",
+      "\u001b[?25hCollecting fastprogress>=0.2.0\n",
+      "  Downloading fastprogress-1.0.0-py3-none-any.whl (12 kB)\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4 in /opt/conda/lib/python3.6/site-packages (from pymc3) (3.10.0.0)\n",
+      "Requirement already satisfied: dill in /opt/conda/lib/python3.6/site-packages (from pymc3) (0.2.9)\n",
+      "Collecting contextvars; python_version < \"3.7\"\n",
+      "  Downloading contextvars-2.4.tar.gz (9.6 kB)\n",
+      "Requirement already satisfied: arviz>=0.9.0 in /opt/conda/lib/python3.6/site-packages (from pymc3) (0.11.2)\n",
+      "Requirement already satisfied: scipy>=0.18.1 in /opt/conda/lib/python3.6/site-packages (from pymc3) (1.1.0)\n",
+      "Requirement already satisfied: numpy>=1.13.0 in /opt/conda/lib/python3.6/site-packages (from pymc3) (1.15.2)\n",
+      "Collecting dataclasses; python_version < \"3.7\"\n",
+      "  Downloading dataclasses-0.8-py3-none-any.whl (19 kB)\n",
+      "Requirement already satisfied: patsy>=0.5.1 in /opt/conda/lib/python3.6/site-packages (from pymc3) (0.5.1)\n",
+      "Requirement already satisfied: pytz>=2017.2 in /opt/conda/lib/python3.6/site-packages (from pandas>=0.18.0->pymc3) (2019.3)\n",
+      "Requirement already satisfied: python-dateutil>=2.7.3 in /opt/conda/lib/python3.6/site-packages (from pandas>=0.18.0->pymc3) (2.8.1)\n",
+      "Collecting immutables>=0.9\n",
+      "  Downloading immutables-0.15-cp36-cp36m-manylinux1_x86_64.whl (100 kB)\n",
+      "\u001b[K     |████████████████████████████████| 100 kB 19.6 MB/s ta 0:00:01\n",
+      "\u001b[?25hRequirement already satisfied: setuptools>=38.4 in /opt/conda/lib/python3.6/site-packages (from arviz>=0.9.0->pymc3) (45.2.0.post20200209)\n",
+      "Requirement already satisfied: packaging in /opt/conda/lib/python3.6/site-packages (from arviz>=0.9.0->pymc3) (20.1)\n",
+      "Requirement already satisfied: netcdf4 in /opt/conda/lib/python3.6/site-packages (from arviz>=0.9.0->pymc3) (1.5.7)\n",
+      "Requirement already satisfied: matplotlib>=3.0 in /opt/conda/lib/python3.6/site-packages (from arviz>=0.9.0->pymc3) (3.3.4)\n",
+      "Requirement already satisfied: xarray>=0.16.1 in /opt/conda/lib/python3.6/site-packages (from arviz>=0.9.0->pymc3) (0.16.2)\n",
+      "Requirement already satisfied: six in /opt/conda/lib/python3.6/site-packages (from patsy>=0.5.1->pymc3) (1.14.0)\n",
+      "Requirement already satisfied: pyparsing>=2.0.2 in /opt/conda/lib/python3.6/site-packages (from packaging->arviz>=0.9.0->pymc3) (2.4.6)\n",
+      "Requirement already satisfied: cftime in /opt/conda/lib/python3.6/site-packages (from netcdf4->arviz>=0.9.0->pymc3) (1.5.0)\n",
+      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.0->arviz>=0.9.0->pymc3) (7.0.0)\n",
+      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.0->arviz>=0.9.0->pymc3) (0.10.0)\n",
+      "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.0->arviz>=0.9.0->pymc3) (1.1.0)\n",
+      "Building wheels for collected packages: theano-pymc, contextvars\n",
+      "  Building wheel for theano-pymc (setup.py) ... \u001b[?25ldone\n",
+      "\u001b[?25h  Created wheel for theano-pymc: filename=Theano_PyMC-1.0.11-py3-none-any.whl size=2572022 sha256=90d446d4df3d178ea00a08d0294bf165e0fa75a3412a4f0f1b1053cdd9b5ae59\n",
+      "  Stored in directory: /home/jovyan/.cache/pip/wheels/0c/3f/12/4300ed97dce181098755583aea62c4b59f6e5c43fe53a3f097\n",
+      "  Building wheel for contextvars (setup.py) ... \u001b[?25ldone\n",
+      "\u001b[?25h  Created wheel for contextvars: filename=contextvars-2.4-py3-none-any.whl size=7664 sha256=0b279e2f13ddef2e3289e2b4a86bb76a004675afc18ccb264ccd1e7186d58c23\n",
+      "  Stored in directory: /home/jovyan/.cache/pip/wheels/41/11/53/911724983aa48deb94792432e14e518447212dd6c5477d49d3\n",
+      "Successfully built theano-pymc contextvars\n",
+      "Installing collected packages: theano-pymc, fastprogress, immutables, contextvars, dataclasses, pymc3\n",
+      "Successfully installed contextvars-2.4 dataclasses-0.8 fastprogress-1.0.0 immutables-0.15 pymc3-3.10.0 theano-pymc-1.0.11\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install pymc3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting numpy==1.15.4\n",
+      "  Downloading numpy-1.15.4-cp36-cp36m-manylinux1_x86_64.whl (13.9 MB)\n",
+      "\u001b[K     |████████████████████████████████| 13.9 MB 24.9 MB/s eta 0:00:01\n",
+      "\u001b[?25hInstalling collected packages: numpy\n",
+      "  Attempting uninstall: numpy\n",
+      "    Found existing installation: numpy 1.15.2\n",
+      "    Uninstalling numpy-1.15.2:\n",
+      "      Successfully uninstalled numpy-1.15.2\n",
+      "Successfully installed numpy-1.15.4\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install numpy==1.15.4"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Yr</th>\n",
+       "      <th>Mn</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>CO2</th>\n",
+       "      <th>seasonally</th>\n",
+       "      <th>fit</th>\n",
+       "      <th>seasonally</th>\n",
+       "      <th>CO2</th>\n",
+       "      <th>seasonally</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>adjusted</td>\n",
+       "      <td></td>\n",
+       "      <td>adjusted fit</td>\n",
+       "      <td>filled</td>\n",
+       "      <td>adjusted filled</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>Excel</td>\n",
+       "      <td></td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>01</td>\n",
+       "      <td>21200</td>\n",
+       "      <td>1958.0411</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>02</td>\n",
+       "      <td>21231</td>\n",
+       "      <td>1958.1260</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>03</td>\n",
+       "      <td>21259</td>\n",
+       "      <td>1958.2027</td>\n",
+       "      <td>315.70</td>\n",
+       "      <td>314.43</td>\n",
+       "      <td>316.19</td>\n",
+       "      <td>314.90</td>\n",
+       "      <td>315.70</td>\n",
+       "      <td>314.43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>765</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>08</td>\n",
+       "      <td>44423</td>\n",
+       "      <td>2021.6219</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>766</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>09</td>\n",
+       "      <td>44454</td>\n",
+       "      <td>2021.7068</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>767</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>10</td>\n",
+       "      <td>44484</td>\n",
+       "      <td>2021.7890</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>768</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>11</td>\n",
+       "      <td>44515</td>\n",
+       "      <td>2021.8740</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>769</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>12</td>\n",
+       "      <td>44545</td>\n",
+       "      <td>2021.9562</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>770 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Yr   Mn      Date        Date        CO2  seasonally          fit  \\\n",
+       "0                                                  adjusted                \n",
+       "1                  Excel                  [ppm]      [ppm]         [ppm]   \n",
+       "2    1958   01     21200   1958.0411     -99.99      -99.99       -99.99   \n",
+       "3    1958   02     21231   1958.1260     -99.99      -99.99       -99.99   \n",
+       "4    1958   03     21259   1958.2027     315.70      314.43       316.19   \n",
+       "..    ...  ...       ...         ...        ...         ...          ...   \n",
+       "765  2021   08     44423   2021.6219     -99.99      -99.99       -99.99   \n",
+       "766  2021   09     44454   2021.7068     -99.99      -99.99       -99.99   \n",
+       "767  2021   10     44484   2021.7890     -99.99      -99.99       -99.99   \n",
+       "768  2021   11     44515   2021.8740     -99.99      -99.99       -99.99   \n",
+       "769  2021   12     44545   2021.9562     -99.99      -99.99       -99.99   \n",
+       "\n",
+       "       seasonally           CO2       seasonally  \n",
+       "0    adjusted fit        filled  adjusted filled  \n",
+       "1           [ppm]         [ppm]            [ppm]  \n",
+       "2          -99.99        -99.99           -99.99  \n",
+       "3          -99.99        -99.99           -99.99  \n",
+       "4          314.90        315.70           314.43  \n",
+       "..            ...           ...              ...  \n",
+       "765        -99.99        -99.99           -99.99  \n",
+       "766        -99.99        -99.99           -99.99  \n",
+       "767        -99.99        -99.99           -99.99  \n",
+       "768        -99.99        -99.99           -99.99  \n",
+       "769        -99.99        -99.99           -99.99  \n",
+       "\n",
+       "[770 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_url = \"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/monthly/monthly_in_situ_co2_mlo.csv\"\n",
+    "data_monthly= pd.read_csv(data_url,skiprows=54)\n",
+    "data_monthly"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Yr</th>\n",
+       "      <th>Mn</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>CO2</th>\n",
+       "      <th>seasonally</th>\n",
+       "      <th>fit</th>\n",
+       "      <th>seasonally</th>\n",
+       "      <th>CO2</th>\n",
+       "      <th>seasonally</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>Excel</td>\n",
+       "      <td></td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "      <td>[ppm]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>01</td>\n",
+       "      <td>21200</td>\n",
+       "      <td>1958.0411</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>02</td>\n",
+       "      <td>21231</td>\n",
+       "      <td>1958.1260</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>03</td>\n",
+       "      <td>21259</td>\n",
+       "      <td>1958.2027</td>\n",
+       "      <td>315.70</td>\n",
+       "      <td>314.43</td>\n",
+       "      <td>316.19</td>\n",
+       "      <td>314.90</td>\n",
+       "      <td>315.70</td>\n",
+       "      <td>314.43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>04</td>\n",
+       "      <td>21290</td>\n",
+       "      <td>1958.2877</td>\n",
+       "      <td>317.45</td>\n",
+       "      <td>315.16</td>\n",
+       "      <td>317.30</td>\n",
+       "      <td>314.98</td>\n",
+       "      <td>317.45</td>\n",
+       "      <td>315.16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>765</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>08</td>\n",
+       "      <td>44423</td>\n",
+       "      <td>2021.6219</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>766</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>09</td>\n",
+       "      <td>44454</td>\n",
+       "      <td>2021.7068</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>767</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>10</td>\n",
+       "      <td>44484</td>\n",
+       "      <td>2021.7890</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>768</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>11</td>\n",
+       "      <td>44515</td>\n",
+       "      <td>2021.8740</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>769</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>12</td>\n",
+       "      <td>44545</td>\n",
+       "      <td>2021.9562</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>769 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Yr   Mn      Date        Date        CO2  seasonally          fit  \\\n",
+       "1                  Excel                  [ppm]      [ppm]         [ppm]   \n",
+       "2    1958   01     21200   1958.0411     -99.99      -99.99       -99.99   \n",
+       "3    1958   02     21231   1958.1260     -99.99      -99.99       -99.99   \n",
+       "4    1958   03     21259   1958.2027     315.70      314.43       316.19   \n",
+       "5    1958   04     21290   1958.2877     317.45      315.16       317.30   \n",
+       "..    ...  ...       ...         ...        ...         ...          ...   \n",
+       "765  2021   08     44423   2021.6219     -99.99      -99.99       -99.99   \n",
+       "766  2021   09     44454   2021.7068     -99.99      -99.99       -99.99   \n",
+       "767  2021   10     44484   2021.7890     -99.99      -99.99       -99.99   \n",
+       "768  2021   11     44515   2021.8740     -99.99      -99.99       -99.99   \n",
+       "769  2021   12     44545   2021.9562     -99.99      -99.99       -99.99   \n",
+       "\n",
+       "      seasonally           CO2  seasonally  \n",
+       "1          [ppm]         [ppm]       [ppm]  \n",
+       "2         -99.99        -99.99      -99.99  \n",
+       "3         -99.99        -99.99      -99.99  \n",
+       "4         314.90        315.70      314.43  \n",
+       "5         314.98        317.45      315.16  \n",
+       "..           ...           ...         ...  \n",
+       "765       -99.99        -99.99      -99.99  \n",
+       "766       -99.99        -99.99      -99.99  \n",
+       "767       -99.99        -99.99      -99.99  \n",
+       "768       -99.99        -99.99      -99.99  \n",
+       "769       -99.99        -99.99      -99.99  \n",
+       "\n",
+       "[769 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_monthly = data_monthly.iloc[1:]\n",
+    "data_monthly"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Yr</th>\n",
+       "      <th>Mn</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>CO2</th>\n",
+       "      <th>seasonally</th>\n",
+       "      <th>fit</th>\n",
+       "      <th>seasonally</th>\n",
+       "      <th>CO2</th>\n",
+       "      <th>seasonally</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>02</td>\n",
+       "      <td>21231</td>\n",
+       "      <td>1958.1260</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>03</td>\n",
+       "      <td>21259</td>\n",
+       "      <td>1958.2027</td>\n",
+       "      <td>315.70</td>\n",
+       "      <td>314.43</td>\n",
+       "      <td>316.19</td>\n",
+       "      <td>314.90</td>\n",
+       "      <td>315.70</td>\n",
+       "      <td>314.43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>04</td>\n",
+       "      <td>21290</td>\n",
+       "      <td>1958.2877</td>\n",
+       "      <td>317.45</td>\n",
+       "      <td>315.16</td>\n",
+       "      <td>317.30</td>\n",
+       "      <td>314.98</td>\n",
+       "      <td>317.45</td>\n",
+       "      <td>315.16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>05</td>\n",
+       "      <td>21320</td>\n",
+       "      <td>1958.3699</td>\n",
+       "      <td>317.51</td>\n",
+       "      <td>314.71</td>\n",
+       "      <td>317.86</td>\n",
+       "      <td>315.06</td>\n",
+       "      <td>317.51</td>\n",
+       "      <td>314.71</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>06</td>\n",
+       "      <td>21351</td>\n",
+       "      <td>1958.4548</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>317.24</td>\n",
+       "      <td>315.14</td>\n",
+       "      <td>317.24</td>\n",
+       "      <td>315.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>765</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>08</td>\n",
+       "      <td>44423</td>\n",
+       "      <td>2021.6219</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>766</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>09</td>\n",
+       "      <td>44454</td>\n",
+       "      <td>2021.7068</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>767</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>10</td>\n",
+       "      <td>44484</td>\n",
+       "      <td>2021.7890</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>768</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>11</td>\n",
+       "      <td>44515</td>\n",
+       "      <td>2021.8740</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>769</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>12</td>\n",
+       "      <td>44545</td>\n",
+       "      <td>2021.9562</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>767 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Yr   Mn      Date        Date        CO2 seasonally          fit  \\\n",
+       "3    1958   02     21231   1958.1260     -99.99     -99.99       -99.99   \n",
+       "4    1958   03     21259   1958.2027     315.70     314.43       316.19   \n",
+       "5    1958   04     21290   1958.2877     317.45     315.16       317.30   \n",
+       "6    1958   05     21320   1958.3699     317.51     314.71       317.86   \n",
+       "7    1958   06     21351   1958.4548     -99.99     -99.99       317.24   \n",
+       "..    ...  ...       ...         ...        ...        ...          ...   \n",
+       "765  2021   08     44423   2021.6219     -99.99     -99.99       -99.99   \n",
+       "766  2021   09     44454   2021.7068     -99.99     -99.99       -99.99   \n",
+       "767  2021   10     44484   2021.7890     -99.99     -99.99       -99.99   \n",
+       "768  2021   11     44515   2021.8740     -99.99     -99.99       -99.99   \n",
+       "769  2021   12     44545   2021.9562     -99.99     -99.99       -99.99   \n",
+       "\n",
+       "      seasonally          CO2  seasonally  \n",
+       "3         -99.99       -99.99      -99.99  \n",
+       "4         314.90       315.70      314.43  \n",
+       "5         314.98       317.45      315.16  \n",
+       "6         315.06       317.51      314.71  \n",
+       "7         315.14       317.24      315.14  \n",
+       "..           ...          ...         ...  \n",
+       "765       -99.99       -99.99      -99.99  \n",
+       "766       -99.99       -99.99      -99.99  \n",
+       "767       -99.99       -99.99      -99.99  \n",
+       "768       -99.99       -99.99      -99.99  \n",
+       "769       -99.99       -99.99      -99.99  \n",
+       "\n",
+       "[767 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = data_monthly.iloc[1:]\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# replace '-99.99' values with 'nan'\n",
+    "from numpy import nan\n",
+    "data.replace(to_replace=-99.99, value=np.nan, inplace=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# fix column names\n",
+    "cols = [\n",
+    "    \"year\",\n",
+    "    \"month\",\n",
+    "    \"--\",\n",
+    "    \"--\",\n",
+    "    \"CO2\",\n",
+    "    \"seasonaly_adjusted\",\n",
+    "    \"fit\",\n",
+    "    \"seasonally_adjusted_fit\",\n",
+    "    \"CO2_filled\",\n",
+    "    \"seasonally_adjusted_filled\",\n",
+    "]\n",
+    "data.columns = cols\n",
+    "cols.remove(\"--\")\n",
+    "cols.remove(\"--\")\n",
+    "data= data[cols]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  \"\"\"\n"
+     ]
+    }
+   ],
+   "source": [
+    "# drop rows with nan\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "data.dropna()\n",
+    "data.dropna(inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  \n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>CO2</th>\n",
+       "      <th>seasonaly_adjusted</th>\n",
+       "      <th>fit</th>\n",
+       "      <th>seasonally_adjusted_fit</th>\n",
+       "      <th>CO2_filled</th>\n",
+       "      <th>seasonally_adjusted_filled</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1958-02-15</th>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-03-15</th>\n",
+       "      <td>315.70</td>\n",
+       "      <td>314.43</td>\n",
+       "      <td>316.19</td>\n",
+       "      <td>314.90</td>\n",
+       "      <td>315.70</td>\n",
+       "      <td>314.43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-04-15</th>\n",
+       "      <td>317.45</td>\n",
+       "      <td>315.16</td>\n",
+       "      <td>317.30</td>\n",
+       "      <td>314.98</td>\n",
+       "      <td>317.45</td>\n",
+       "      <td>315.16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-05-15</th>\n",
+       "      <td>317.51</td>\n",
+       "      <td>314.71</td>\n",
+       "      <td>317.86</td>\n",
+       "      <td>315.06</td>\n",
+       "      <td>317.51</td>\n",
+       "      <td>314.71</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-06-15</th>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>317.24</td>\n",
+       "      <td>315.14</td>\n",
+       "      <td>317.24</td>\n",
+       "      <td>315.14</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  CO2 seasonaly_adjusted          fit seasonally_adjusted_fit  \\\n",
+       "1958-02-15     -99.99             -99.99       -99.99                  -99.99   \n",
+       "1958-03-15     315.70             314.43       316.19                  314.90   \n",
+       "1958-04-15     317.45             315.16       317.30                  314.98   \n",
+       "1958-05-15     317.51             314.71       317.86                  315.06   \n",
+       "1958-06-15     -99.99             -99.99       317.24                  315.14   \n",
+       "\n",
+       "             CO2_filled seasonally_adjusted_filled  \n",
+       "1958-02-15       -99.99                     -99.99  \n",
+       "1958-03-15       315.70                     314.43  \n",
+       "1958-04-15       317.45                     315.16  \n",
+       "1958-05-15       317.51                     314.71  \n",
+       "1958-06-15       317.24                     315.14  "
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# fix time index\n",
+    "data[\"day\"] = 15\n",
+    "data.index = pd.to_datetime(data[[\"year\", \"month\", \"day\"]])\n",
+    "cols.remove(\"year\")\n",
+    "cols.remove(\"month\")\n",
+    "data = data[cols]\n",
+    "\n",
+    "data.head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# function to convert datetimes to numbers that are useful to algorithms\n",
+    "#   this will be useful later when doing prediction\n",
+    "\n",
+    "def dates_to_idx(timelist):\n",
+    "    reference_time = pd.to_datetime(\"1958-03-15\")\n",
+    "    t = (timelist - reference_time) / pd.Timedelta(365, \"D\")\n",
+    "    return np.asarray(t)\n",
+    "\n",
+    "\n",
+    "t = dates_to_idx(data.index)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# split into training and test set\n",
+    "sep_idx = data.index.searchsorted(pd.to_datetime(\"2003-12-15\"))\n",
+    "data_early = data.iloc[: sep_idx + 1, :]\n",
+    "data_later = data.iloc[sep_idx:, :]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# make plot\n",
+    "#import matplotlib.pyplot as plt\n",
+    "from bokeh.plotting import figure, show\n",
+    "from bokeh.models import BoxAnnotation, Label, Legend, Span\n",
+    "from bokeh.io import output_notebook\n",
+    "from bokeh.palettes import brewer\n",
+    "\n",
+    "p = figure(\n",
+    "    x_axis_type=\"datetime\",\n",
+    "    title=\"Monthly CO2 Readings from Mauna Loa (1958-2021)\",\n",
+    "    plot_width=550,\n",
+    "    plot_height=350,\n",
+    ")\n",
+    "p.yaxis.axis_label = \"CO2 [ppm]\"\n",
+    "p.xaxis.axis_label = \"Date\"\n",
+    "predict_region = BoxAnnotation(\n",
+    "    left=pd.to_datetime(\"2003-12-15\"), fill_alpha=0.1, fill_color=\"firebrick\"\n",
+    ")\n",
+    "p.add_layout(predict_region)\n",
+    "ppm400 = Span(location=400, dimension=\"width\", line_color=\"red\", line_dash=\"dashed\", line_width=2)\n",
+    "p.add_layout(ppm400)\n",
+    "\n",
+    "p.line(data.index, data[\"CO2\"], line_width=2, line_color=\"black\", alpha=0.5)\n",
+    "p.circle(data.index, data[\"CO2\"], line_color=\"black\", alpha=0.1, size=2)\n",
+    "\n",
+    "train_label = Label(\n",
+    "    x=100,\n",
+    "    y=165,\n",
+    "    x_units=\"screen\",\n",
+    "    y_units=\"screen\",\n",
+    "    text=\"Training Set\",\n",
+    "    render_mode=\"css\",\n",
+    "    border_line_alpha=0.0,\n",
+    "    background_fill_alpha=0.0,\n",
+    ")\n",
+    "test_label = Label(\n",
+    "    x=585,\n",
+    "    y=80,\n",
+    "    x_units=\"screen\",\n",
+    "    y_units=\"screen\",\n",
+    "    text=\"Test Set\",\n",
+    "    render_mode=\"css\",\n",
+    "    border_line_alpha=0.0,\n",
+    "    background_fill_alpha=0.0,\n",
+    ")\n",
+    "\n",
+    "p.add_layout(train_label)\n",
+    "p.add_layout(test_label)\n",
+    "show(p)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting package metadata (current_repodata.json): - Killed\n",
+      "\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "conda install mkl-service"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[31mERROR: Could not find a version that satisfies the requirement pymc3==3.11.2 (from versions: 3.0rc1, 3.0rc2, 3.0rc4, 3.0rc5, 3.0rc6, 3.0, 3.1rc1, 3.1rc2, 3.1rc3, 3.1, 3.2rc1, 3.2, 3.3rc1, 3.3rc2, 3.3, 3.4rc1, 3.4rc2, 3.4.1, 3.5rc1, 3.5, 3.6, 3.7rc1, 3.7, 3.8, 3.9.0, 3.9.1, 3.9.2, 3.9.3, 3.10.0)\u001b[0m\n",
+      "\u001b[31mERROR: No matching distribution found for pymc3==3.11.2\u001b[0m\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install pymc3==3.11.2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "module 'arviz' has no attribute 'geweke'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-4-377bac9a3a1b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mpymc3\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpm\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0marviz\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0maz\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pymc3/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     62\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0msampling\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     63\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0msmc\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 64\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mstats\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     65\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mstep_methods\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     66\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mtests\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtest\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pymc3/stats/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     45\u001b[0m \u001b[0mcompare\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmap_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maz\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompare\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     46\u001b[0m \u001b[0mess\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmap_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maz\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mess\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 47\u001b[0;31m \u001b[0mgeweke\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmap_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maz\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgeweke\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     48\u001b[0m \u001b[0mhpd\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmap_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maz\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhpd\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m \u001b[0mloo\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmap_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maz\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloo\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mAttributeError\u001b[0m: module 'arviz' has no attribute 'geweke'"
+     ]
+    }
+   ],
+   "source": [
+    "import pymc3 as pm\n",
+    "import arviz as az\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "x = np.linspace(0, 150, 5000)\n",
+    "priors = [\n",
+    "    (\"ℓ_pdecay\", pm.Gamma.dist(alpha=10, beta=0.075)),\n",
+    "    (\"ℓ_psmooth\", pm.Gamma.dist(alpha=4, beta=3)),\n",
+    "    (\"period\", pm.Normal.dist(mu=1.0, sigma=0.05)),\n",
+    "    (\"ℓ_med\", pm.Gamma.dist(alpha=2, beta=0.75)),\n",
+    "    (\"α\", pm.Gamma.dist(alpha=5, beta=2)),\n",
+    "    (\"ℓ_trend\", pm.Gamma.dist(alpha=4, beta=0.1)),\n",
+    "    (\"ℓ_noise\", pm.Gamma.dist(alpha=2, beta=4)),\n",
+    "]\n",
+    "\n",
+    "colors = brewer[\"Paired\"][7]\n",
+    "\n",
+    "p = figure(\n",
+    "    title=\"Lengthscale and period priors\",\n",
+    "    plot_width=550,\n",
+    "    plot_height=350,\n",
+    "    x_range=(-1, 8),\n",
+    "    y_range=(0, 2),\n",
+    ")\n",
+    "p.yaxis.axis_label = \"Probability\"\n",
+    "p.xaxis.axis_label = \"Years\"\n",
+    "\n",
+    "for i, prior in enumerate(priors):\n",
+    "    p.line(\n",
+    "        x,\n",
+    "        np.exp(prior[1].logp(x).eval()),\n",
+    "        legend_label=prior[0],\n",
+    "        line_width=3,\n",
+    "        line_color=colors[i],\n",
+    "    )\n",
+    "show(p)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mkdir data-visualization\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/home/jovyan/work/module3/exo3/data-visualization\n"
+     ]
+    }
+   ],
+   "source": [
+    "cd data-visualization\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting plotnine\n",
+      "  Downloading plotnine-0.8.0-py3-none-any.whl (4.7 MB)\n",
+      "\u001b[K     |████████████████████████████████| 4.7 MB 16.0 MB/s eta 0:00:01\n",
+      "\u001b[?25hCollecting descartes>=1.1.0\n",
+      "  Downloading descartes-1.1.0-py3-none-any.whl (5.8 kB)\n",
+      "Collecting mizani>=0.7.3\n",
+      "  Downloading mizani-0.7.3-py3-none-any.whl (63 kB)\n",
+      "\u001b[K     |████████████████████████████████| 63 kB 4.5 MB/s  eta 0:00:01\n",
+      "\u001b[?25hCollecting scipy>=1.5.0\n",
+      "  Downloading scipy-1.5.4-cp36-cp36m-manylinux1_x86_64.whl (25.9 MB)\n",
+      "\u001b[K     |████████████████████████████████| 25.9 MB 54.9 MB/s eta 0:00:01     |██████████████████████▋         | 18.3 MB 54.9 MB/s eta 0:00:01\n",
+      "\u001b[?25hCollecting numpy>=1.19.0\n",
+      "  Downloading numpy-1.19.5-cp36-cp36m-manylinux2010_x86_64.whl (14.8 MB)\n",
+      "\u001b[K     |████████████████████████████████| 14.8 MB 14.5 MB/s eta 0:00:01     |██████████████████████▋         | 10.5 MB 14.5 MB/s eta 0:00:01\n",
+      "\u001b[?25hRequirement already satisfied: patsy>=0.5.1 in /opt/conda/lib/python3.6/site-packages (from plotnine) (0.5.1)\n",
+      "Requirement already satisfied: matplotlib>=3.1.1 in /opt/conda/lib/python3.6/site-packages (from plotnine) (3.3.4)\n",
+      "Requirement already satisfied: pandas>=1.1.0 in /opt/conda/lib/python3.6/site-packages (from plotnine) (1.1.5)\n",
+      "Collecting statsmodels>=0.12.1\n",
+      "  Downloading statsmodels-0.12.2-cp36-cp36m-manylinux1_x86_64.whl (9.5 MB)\n",
+      "\u001b[K     |████████████████████████████████| 9.5 MB 49.3 MB/s eta 0:00:01\n",
+      "\u001b[?25hCollecting palettable\n",
+      "  Downloading palettable-3.3.0-py2.py3-none-any.whl (111 kB)\n",
+      "\u001b[K     |████████████████████████████████| 111 kB 65.3 MB/s eta 0:00:01\n",
+      "\u001b[?25hRequirement already satisfied: six in /opt/conda/lib/python3.6/site-packages (from patsy>=0.5.1->plotnine) (1.14.0)\n",
+      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (0.10.0)\n",
+      "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (1.1.0)\n",
+      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (7.0.0)\n",
+      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (2.4.6)\n",
+      "Requirement already satisfied: python-dateutil>=2.1 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (2.8.1)\n",
+      "Requirement already satisfied: pytz>=2017.2 in /opt/conda/lib/python3.6/site-packages (from pandas>=1.1.0->plotnine) (2019.3)\n",
+      "Requirement already satisfied: setuptools in /opt/conda/lib/python3.6/site-packages (from kiwisolver>=1.0.1->matplotlib>=3.1.1->plotnine) (45.2.0.post20200209)\n",
+      "Installing collected packages: descartes, palettable, numpy, mizani, scipy, statsmodels, plotnine\n",
+      "  Attempting uninstall: numpy\n",
+      "    Found existing installation: numpy 1.15.4\n",
+      "    Uninstalling numpy-1.15.4:\n",
+      "      Successfully uninstalled numpy-1.15.4\n",
+      "  Attempting uninstall: scipy\n",
+      "    Found existing installation: scipy 1.1.0\n",
+      "    Uninstalling scipy-1.1.0:\n",
+      "      Successfully uninstalled scipy-1.1.0\n",
+      "  Attempting uninstall: statsmodels\n",
+      "    Found existing installation: statsmodels 0.9.0\n",
+      "    Uninstalling statsmodels-0.9.0:\n",
+      "      Successfully uninstalled statsmodels-0.9.0\n",
+      "Successfully installed descartes-1.1.0 mizani-0.7.3 numpy-1.19.5 palettable-3.3.0 plotnine-0.8.0 scipy-1.5.4 statsmodels-0.12.2\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install plotnine"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: pandas in /opt/conda/lib/python3.6/site-packages (1.1.5)\n",
+      "Requirement already satisfied: plotnine in /opt/conda/lib/python3.6/site-packages (0.8.0)\n",
+      "Requirement already satisfied: pytz>=2017.2 in /opt/conda/lib/python3.6/site-packages (from pandas) (2019.3)\n",
+      "Requirement already satisfied: python-dateutil>=2.7.3 in /opt/conda/lib/python3.6/site-packages (from pandas) (2.8.1)\n",
+      "Requirement already satisfied: numpy>=1.15.4 in /opt/conda/lib/python3.6/site-packages (from pandas) (1.19.5)\n",
+      "Requirement already satisfied: mizani>=0.7.3 in /opt/conda/lib/python3.6/site-packages (from plotnine) (0.7.3)\n",
+      "Requirement already satisfied: matplotlib>=3.1.1 in /opt/conda/lib/python3.6/site-packages (from plotnine) (3.3.4)\n",
+      "Requirement already satisfied: patsy>=0.5.1 in /opt/conda/lib/python3.6/site-packages (from plotnine) (0.5.1)\n",
+      "Requirement already satisfied: scipy>=1.5.0 in /opt/conda/lib/python3.6/site-packages (from plotnine) (1.5.4)\n",
+      "Requirement already satisfied: statsmodels>=0.12.1 in /opt/conda/lib/python3.6/site-packages (from plotnine) (0.12.2)\n",
+      "Requirement already satisfied: descartes>=1.1.0 in /opt/conda/lib/python3.6/site-packages (from plotnine) (1.1.0)\n",
+      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.14.0)\n",
+      "Requirement already satisfied: palettable in /opt/conda/lib/python3.6/site-packages (from mizani>=0.7.3->plotnine) (3.3.0)\n",
+      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (7.0.0)\n",
+      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (0.10.0)\n",
+      "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (1.1.0)\n",
+      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /opt/conda/lib/python3.6/site-packages (from matplotlib>=3.1.1->plotnine) (2.4.6)\n",
+      "Requirement already satisfied: setuptools in /opt/conda/lib/python3.6/site-packages (from kiwisolver>=1.0.1->matplotlib>=3.1.1->plotnine) (45.2.0.post20200209)\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install pandas plotnine"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "from plotnine.data import mpg\n",
+    "from plotnine import ggplot\n",
+    "from plotnine import ggplot, aes, labs\n",
+    "mpg = ggplot(data = data, aes(x = datetime, y = CO2)),\n",
+    "       labs(title = \"Evolution of CO2 concentration in Hawaii\",\n",
+    "       subtitle = \"(1958-2020)\",\n",
+    "       caption = \"Datafrom Scripps CO2 Program\",\n",
+    "       tag = \"Figure 1\",\n",
+    "       x = \"Date\",\n",
+    "       y = \"CO2 Concentration (ppm)\") + theme_bw() + geom_point(size = 0.5, color = \"grey50\")\n",
+    "\n",
+    "ggplot(mpg)"
+   ]
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +1521,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module3/exo3/monthly.csv b/module3/exo3/monthly.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fa9ffff47802471e1e9114c9a4f060de50759394
--- /dev/null
+++ b/module3/exo3/monthly.csv
@@ -0,0 +1,769 @@
+  Yr, Mn,    Date,      Date,CO2,seasonally adjusted,fit,seasonally adjusted fit,CO2 filled,seasonally adjusted filled
+1958,1,21200,1958.0411,-99.99,-99.99,-99.99,-99.99,-99.99,-99.99
+1958,2,21231,1958.126,-99.99,-99.99,-99.99,-99.99,-99.99,-99.99
+1958,3,21259,1958.2027,315.7,314.43,316.19,314.9,315.7,314.43
+1958,4,21290,1958.2877,317.45,315.16,317.3,314.98,317.45,315.16
+1958,5,21320,1958.3699,317.51,314.71,317.86,315.06,317.51,314.71
+1958,6,21351,1958.4548,-99.99,-99.99,317.24,315.14,317.24,315.14
+1958,7,21381,1958.537,315.86,315.19,315.86,315.22,315.86,315.19
+1958,8,21412,1958.6219,314.93,316.19,313.99,315.29,314.93,316.19
+1958,9,21443,1958.7068,313.21,316.09,312.45,315.35,313.21,316.09
+1958,10,21473,1958.789,-99.99,-99.99,312.43,315.41,312.43,315.41
+1958,11,21504,1958.874,313.33,315.2,313.61,315.46,313.33,315.2
+1958,12,21534,1958.9562,314.67,315.43,314.76,315.51,314.67,315.43
+1959,1,21565,1959.0411,315.58,315.54,315.62,315.57,315.58,315.54
+1959,2,21596,1959.126,316.49,315.85,316.27,315.63,316.49,315.85
+1959,3,21624,1959.2027,316.65,315.37,316.98,315.69,316.65,315.37
+1959,4,21655,1959.2877,317.72,315.41,318.09,315.77,317.72,315.41
+1959,5,21685,1959.3699,318.29,315.48,318.66,315.85,318.29,315.48
+1959,6,21716,1959.4548,318.15,316.02,318.05,315.94,318.15,316.02
+1959,7,21746,1959.537,316.54,315.87,316.67,316.03,316.54,315.87
+1959,8,21777,1959.6219,314.8,316.07,314.82,316.12,314.8,316.07
+1959,9,21808,1959.7068,313.84,316.73,313.31,316.22,313.84,316.73
+1959,10,21838,1959.789,313.33,316.33,313.32,316.31,313.33,316.33
+1959,11,21869,1959.874,314.81,316.69,314.53,316.39,314.81,316.69
+1959,12,21899,1959.9562,315.58,316.35,315.72,316.47,315.58,316.35
+1960,1,21930,1960.041,316.43,316.39,316.61,316.56,316.43,316.39
+1960,2,21961,1960.1257,316.98,316.35,317.28,316.64,316.98,316.35
+1960,3,21990,1960.2049,317.58,316.27,318.03,316.71,317.58,316.27
+1960,4,22021,1960.2896,319.03,316.7,319.15,316.79,319.03,316.7
+1960,5,22051,1960.3716,320.04,317.21,319.68,316.86,320.04,317.21
+1960,6,22082,1960.4563,319.58,317.47,319.02,316.93,319.58,317.47
+1960,7,22112,1960.5383,318.18,317.53,317.6,316.98,318.18,317.53
+1960,8,22143,1960.623,315.9,317.2,315.68,317.01,315.9,317.2
+1960,9,22174,1960.7077,314.17,317.08,314.12,317.05,314.17,317.08
+1960,10,22204,1960.7896,313.83,316.84,314.08,317.07,313.83,316.84
+1960,11,22235,1960.8743,315,316.88,315.25,317.11,315,316.88
+1960,12,22265,1960.9563,316.19,316.96,316.39,317.15,316.19,316.96
+1961,1,22296,1961.0411,316.89,316.85,317.25,317.2,316.89,316.85
+1961,2,22327,1961.126,317.7,317.07,317.91,317.26,317.7,317.07
+1961,3,22355,1961.2027,318.54,317.25,318.63,317.33,318.54,317.25
+1961,4,22386,1961.2877,319.48,317.15,319.75,317.41,319.48,317.15
+1961,5,22416,1961.3699,320.58,317.75,320.33,317.5,320.58,317.75
+1961,6,22447,1961.4548,319.77,317.63,319.71,317.59,319.77,317.63
+1961,7,22477,1961.537,318.56,317.89,318.33,317.68,318.56,317.89
+1961,8,22508,1961.6219,316.79,318.07,316.45,317.76,316.79,318.07
+1961,9,22539,1961.7068,314.99,317.9,314.92,317.85,314.99,317.9
+1961,10,22569,1961.789,315.31,318.33,314.91,317.92,315.31,318.33
+1961,11,22600,1961.874,316.1,318,316.12,317.99,316.1,318
+1961,12,22630,1961.9562,317.01,317.78,317.3,318.06,317.01,317.78
+1962,1,22661,1962.0411,317.94,317.9,318.18,318.13,317.94,317.9
+1962,2,22692,1962.126,318.55,317.91,318.84,318.19,318.55,317.91
+1962,3,22720,1962.2027,319.68,318.39,319.56,318.26,319.68,318.39
+1962,4,22751,1962.2877,320.57,318.24,320.67,318.32,320.57,318.24
+1962,5,22781,1962.3699,321.02,318.17,321.23,318.39,321.02,318.17
+1962,6,22812,1962.4548,320.62,318.47,320.58,318.45,320.62,318.47
+1962,7,22842,1962.537,319.61,318.93,319.16,318.5,319.61,318.93
+1962,8,22873,1962.6219,317.4,318.69,317.24,318.56,317.4,318.69
+1962,9,22904,1962.7068,316.25,319.17,315.66,318.6,316.25,319.17
+1962,10,22934,1962.789,315.42,318.45,315.62,318.64,315.42,318.45
+1962,11,22965,1962.874,316.69,318.59,316.8,318.68,316.69,318.59
+1962,12,22995,1962.9562,317.7,318.47,317.96,318.72,317.7,318.47
+1963,1,23026,1963.0411,318.74,318.7,318.82,318.76,318.74,318.7
+1963,2,23057,1963.126,319.07,318.43,319.46,318.81,319.07,318.43
+1963,3,23085,1963.2027,319.86,318.56,320.16,318.85,319.86,318.56
+1963,4,23116,1963.2877,321.38,319.05,321.26,318.91,321.38,319.05
+1963,5,23146,1963.3699,322.25,319.39,321.81,318.96,322.25,319.39
+1963,6,23177,1963.4548,321.48,319.32,321.15,319.01,321.48,319.32
+1963,7,23207,1963.537,319.74,319.06,319.71,319.06,319.74,319.06
+1963,8,23238,1963.6219,317.77,319.06,317.78,319.1,317.77,319.06
+1963,9,23269,1963.7068,316.21,319.14,316.19,319.14,316.21,319.14
+1963,10,23299,1963.789,315.99,319.02,316.16,319.18,315.99,319.02
+1963,11,23330,1963.874,317.07,318.97,317.34,319.23,317.07,318.97
+1963,12,23360,1963.9562,318.35,319.13,318.51,319.27,318.35,319.13
+1964,1,23391,1964.041,319.57,319.53,319.37,319.32,319.57,319.53
+1964,2,23422,1964.1257,-99.99,-99.99,320.02,319.37,320.02,319.37
+1964,3,23451,1964.2049,-99.99,-99.99,320.75,319.41,320.75,319.41
+1964,4,23482,1964.2896,-99.99,-99.99,321.84,319.45,321.84,319.45
+1964,5,23512,1964.3716,322.25,319.39,322.35,319.49,322.25,319.39
+1964,6,23543,1964.4563,321.89,319.75,321.65,319.53,321.89,319.75
+1964,7,23573,1964.5383,320.44,319.78,320.19,319.56,320.44,319.78
+1964,8,23604,1964.623,318.69,320.01,318.23,319.58,318.69,320.01
+1964,9,23635,1964.7077,316.71,319.66,316.63,319.6,316.71,319.66
+1964,10,23665,1964.7896,316.87,319.92,316.59,319.62,316.87,319.92
+1964,11,23696,1964.8743,317.68,319.59,317.75,319.64,317.68,319.59
+1964,12,23726,1964.9563,318.71,319.49,318.89,319.66,318.71,319.49
+1965,1,23757,1965.0411,319.44,319.4,319.74,319.68,319.44,319.4
+1965,2,23788,1965.126,320.44,319.8,320.38,319.72,320.44,319.8
+1965,3,23816,1965.2027,320.89,319.59,321.09,319.77,320.89,319.59
+1965,4,23847,1965.2877,322.14,319.78,322.2,319.83,322.14,319.78
+1965,5,23877,1965.3699,322.17,319.3,322.78,319.91,322.17,319.3
+1965,6,23908,1965.4548,321.87,319.7,322.15,320,321.87,319.7
+1965,7,23938,1965.537,321.21,320.52,320.76,320.1,321.21,320.52
+1965,8,23969,1965.6219,318.87,320.16,318.88,320.21,318.87,320.16
+1965,9,24000,1965.7068,317.82,320.77,317.35,320.32,317.82,320.77
+1965,10,24030,1965.789,317.3,320.36,317.38,320.43,317.3,320.36
+1965,11,24061,1965.874,318.87,320.78,318.65,320.55,318.87,320.78
+1965,12,24091,1965.9562,319.42,320.2,319.9,320.66,319.42,320.2
+1966,1,24122,1966.0411,320.62,320.58,320.84,320.78,320.62,320.58
+1966,2,24153,1966.126,321.6,320.95,321.56,320.9,321.6,320.95
+1966,3,24181,1966.2027,322.39,321.08,322.33,321.01,322.39,321.08
+1966,4,24212,1966.2877,323.7,321.34,323.5,321.12,323.7,321.34
+1966,5,24242,1966.3699,324.08,321.2,324.1,321.22,324.08,321.2
+1966,6,24273,1966.4548,323.75,321.57,323.48,321.32,323.75,321.57
+1966,7,24303,1966.537,322.38,321.69,322.06,321.4,322.38,321.69
+1966,8,24334,1966.6219,320.36,321.66,320.15,321.48,320.36,321.66
+1966,9,24365,1966.7068,318.64,321.6,318.57,321.55,318.64,321.6
+1966,10,24395,1966.789,318.1,321.18,318.56,321.62,318.1,321.18
+1966,11,24426,1966.874,319.78,321.71,319.78,321.68,319.78,321.71
+1966,12,24456,1966.9562,321.03,321.81,320.97,321.74,321.03,321.81
+1967,1,24487,1967.0411,322.33,322.29,321.86,321.8,322.33,322.29
+1967,2,24518,1967.126,322.5,321.85,322.52,321.86,322.5,321.85
+1967,3,24546,1967.2027,323.03,321.72,323.23,321.9,323.03,321.72
+1967,4,24577,1967.2877,324.42,322.05,324.35,321.96,324.42,322.05
+1967,5,24607,1967.3699,325,322.11,324.9,322.01,325,322.11
+1967,6,24638,1967.4548,324.09,321.9,324.24,322.07,324.09,321.9
+1967,7,24668,1967.537,322.54,321.85,322.8,322.14,322.54,321.85
+1967,8,24699,1967.6219,320.92,322.22,320.86,322.2,320.92,322.22
+1967,9,24730,1967.7068,319.25,322.23,319.28,322.27,319.25,322.23
+1967,10,24760,1967.789,319.39,322.47,319.28,322.35,319.39,322.47
+1967,11,24791,1967.874,320.73,322.66,320.51,322.42,320.73,322.66
+1967,12,24821,1967.9562,321.96,322.75,321.72,322.49,321.96,322.75
+1968,1,24852,1968.041,322.57,322.52,322.63,322.57,322.57,322.52
+1968,2,24883,1968.1257,323.15,322.5,323.31,322.65,323.15,322.5
+1968,3,24912,1968.2049,323.89,322.55,324.09,322.73,323.89,322.55
+1968,4,24943,1968.2896,325.02,322.62,325.24,322.83,325.02,322.62
+1968,5,24973,1968.3716,325.57,322.67,325.82,322.92,325.57,322.67
+1968,6,25004,1968.4563,325.36,323.18,325.18,323.03,325.36,323.18
+1968,7,25034,1968.5383,324.14,323.47,323.78,323.14,324.14,323.47
+1968,8,25065,1968.623,322.11,323.44,321.88,323.25,322.11,323.44
+1968,9,25096,1968.7077,320.33,323.32,320.36,323.37,320.33,323.32
+1968,10,25126,1968.7896,320.25,323.33,320.41,323.49,320.25,323.33
+1968,11,25157,1968.8743,321.32,323.26,321.7,323.62,321.32,323.26
+1968,12,25187,1968.9563,322.89,323.69,322.97,323.75,322.89,323.69
+1969,1,25218,1969.0411,324,323.96,323.94,323.89,324,323.96
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+2005,1,38367,2005.0411,378.29,378.24,378.47,378.4,378.29,378.24
+2005,2,38398,2005.126,379.56,378.82,379.36,378.62,379.56,378.82
+2005,3,38426,2005.2027,380.06,378.58,380.31,378.82,380.06,378.58
+2005,4,38457,2005.2877,382.02,379.34,381.73,379.04,382.02,379.34
+2005,5,38487,2005.3699,382.21,378.95,382.51,379.25,382.21,378.95
+2005,6,38518,2005.4548,382.05,379.58,381.92,379.48,382.05,379.58
+2005,7,38548,2005.537,380.63,379.85,380.44,379.69,380.63,379.85
+2005,8,38579,2005.6219,378.64,380.11,378.39,379.9,378.64,380.11
+2005,9,38610,2005.7068,376.38,379.74,376.74,380.11,376.38,379.74
+2005,10,38640,2005.789,376.77,380.24,376.85,380.31,376.77,380.24
+2005,11,38671,2005.874,378.27,380.45,378.36,380.51,378.27,380.45
+2005,12,38701,2005.9562,379.93,380.82,379.83,380.7,379.93,380.82
+2006,1,38732,2006.0411,381.33,381.28,380.94,380.88,381.33,381.28
+2006,2,38763,2006.126,381.98,381.25,381.8,381.05,381.98,381.25
+2006,3,38791,2006.2027,382.53,381.04,382.7,381.2,382.53,381.04
+2006,4,38822,2006.2877,384.33,381.65,384.06,381.36,384.33,381.65
+2006,5,38852,2006.3699,384.89,381.62,384.77,381.5,384.89,381.62
+2006,6,38883,2006.4548,383.99,381.52,384.1,381.65,383.99,381.52
+2006,7,38913,2006.537,382.25,381.46,382.54,381.79,382.25,381.46
+2006,8,38944,2006.6219,380.44,381.92,380.43,381.94,380.44,381.92
+2006,9,38975,2006.7068,378.77,382.13,378.71,382.09,378.77,382.13
+2006,10,39005,2006.789,379.03,382.51,378.76,382.24,379.03,382.51
+2006,11,39036,2006.874,380.11,382.3,380.23,382.39,380.11,382.3
+2006,12,39066,2006.9562,381.63,382.52,381.66,382.53,381.63,382.52
+2007,1,39097,2007.0411,382.55,382.5,382.75,382.68,382.55,382.5
+2007,2,39128,2007.126,383.68,382.94,383.59,382.84,383.68,382.94
+2007,3,39156,2007.2027,384.31,382.82,384.49,382.98,384.31,382.82
+2007,4,39187,2007.2877,386.2,383.51,385.85,383.14,386.2,383.51
+2007,5,39217,2007.3699,386.38,383.1,386.58,383.3,386.38,383.1
+2007,6,39248,2007.4548,385.84,383.36,385.92,383.46,385.84,383.36
+2007,7,39278,2007.537,384.42,383.63,384.37,383.62,384.42,383.63
+2007,8,39309,2007.6219,381.81,383.3,382.26,383.78,381.81,383.3
+2007,9,39340,2007.7068,380.83,384.2,380.56,383.95,380.83,384.2
+2007,10,39370,2007.789,380.83,384.33,380.62,384.1,380.83,384.33
+2007,11,39401,2007.874,382.32,384.51,382.09,384.26,382.32,384.51
+2007,12,39431,2007.9562,383.58,384.48,383.53,384.41,383.58,384.48
+2008,1,39462,2008.041,385.04,384.99,384.62,384.55,385.04,384.99
+2008,2,39493,2008.1257,385.81,385.07,385.45,384.7,385.81,385.07
+2008,3,39522,2008.2049,385.8,384.28,386.38,384.84,385.8,384.28
+2008,4,39553,2008.2896,386.74,384.01,387.73,384.99,386.74,384.01
+2008,5,39583,2008.3716,388.49,385.2,388.43,385.15,388.49,385.2
+2008,6,39614,2008.4563,388.02,385.56,387.76,385.32,388.02,385.56
+2008,7,39644,2008.5383,386.22,385.47,386.2,385.48,386.22,385.47
+2008,8,39675,2008.623,384.05,385.57,384.1,385.65,384.05,385.57
+2008,9,39706,2008.7077,383.05,386.45,382.41,385.82,383.05,386.45
+2008,10,39736,2008.7896,382.75,386.25,382.49,385.98,382.75,386.25
+2008,11,39767,2008.8743,383.98,386.17,383.97,386.14,383.98,386.17
+2008,12,39797,2008.9563,385.08,385.98,385.41,386.29,385.08,385.98
+2009,1,39828,2009.0411,386.63,386.57,386.51,386.44,386.63,386.57
+2009,2,39859,2009.126,387.1,386.36,387.35,386.6,387.1,386.36
+2009,3,39887,2009.2027,388.5,387,388.26,386.75,388.5,387
+2009,4,39918,2009.2877,389.54,386.84,389.64,386.91,389.54,386.84
+2009,5,39948,2009.3699,390.15,386.85,390.38,387.08,390.15,386.85
+2009,6,39979,2009.4548,389.6,387.1,389.74,387.27,389.6,387.1
+2009,7,40009,2009.537,388.05,387.26,388.21,387.45,388.05,387.26
+2009,8,40040,2009.6219,386.07,387.56,386.13,387.66,386.07,387.56
+2009,9,40071,2009.7068,384.64,388.03,384.46,387.87,384.64,388.03
+2009,10,40101,2009.789,384.32,387.84,384.58,388.08,384.32,387.84
+2009,11,40132,2009.874,386.05,388.25,386.13,388.31,386.05,388.25
+2009,12,40162,2009.9562,387.49,388.39,387.65,388.53,387.49,388.39
+2010,1,40193,2010.0411,388.55,388.5,388.83,388.76,388.55,388.5
+2010,2,40224,2010.126,390.08,389.33,389.75,388.99,390.08,389.33
+2010,3,40252,2010.2027,391.02,389.52,390.71,389.19,391.02,389.52
+2010,4,40283,2010.2877,392.39,389.68,392.13,389.4,392.39,389.68
+2010,5,40313,2010.3699,393.24,389.93,392.9,389.59,393.24,389.93
+2010,6,40344,2010.4548,392.26,389.75,392.26,389.78,392.26,389.75
+2010,7,40374,2010.537,390.35,389.55,390.71,389.95,390.35,389.55
+2010,8,40405,2010.6219,388.53,390.03,388.6,390.13,388.53,390.03
+2010,9,40436,2010.7068,386.85,390.25,386.87,390.3,386.85,390.25
+2010,10,40466,2010.789,387.18,390.71,386.94,390.45,387.18,390.71
+2010,11,40497,2010.874,388.69,390.9,388.42,390.6,388.69,390.9
+2010,12,40527,2010.9562,389.83,390.74,389.86,390.74,389.83,390.74
+2011,1,40558,2011.0411,391.33,391.28,390.94,390.88,391.33,391.28
+2011,2,40589,2011.126,391.96,391.21,391.77,391.01,391.96,391.21
+2011,3,40617,2011.2027,392.49,390.98,392.65,391.13,392.49,390.98
+2011,4,40648,2011.2877,393.41,390.69,394.01,391.27,393.41,390.69
+2011,5,40678,2011.3699,394.33,391.01,394.73,391.41,394.33,391.01
+2011,6,40709,2011.4548,393.74,391.23,394.06,391.57,393.74,391.23
+2011,7,40739,2011.537,392.64,391.85,392.5,391.74,392.64,391.85
+2011,8,40770,2011.6219,390.25,391.75,390.38,391.92,390.25,391.75
+2011,9,40801,2011.7068,389.05,392.46,388.67,392.1,389.05,392.46
+2011,10,40831,2011.789,388.98,392.52,388.76,392.28,388.98,392.52
+2011,11,40862,2011.874,390.3,392.51,390.27,392.47,390.3,392.51
+2011,12,40892,2011.9562,391.86,392.77,391.76,392.65,391.86,392.77
+2012,1,40923,2012.041,393.13,393.08,392.9,392.83,393.13,393.08
+2012,2,40954,2012.1257,393.42,392.67,393.78,393.03,393.42,392.67
+2012,3,40983,2012.2049,394.43,392.89,394.77,393.21,394.43,392.89
+2012,4,41014,2012.2896,396.51,393.75,396.19,393.41,396.51,393.75
+2012,5,41044,2012.3716,396.96,393.63,396.94,393.62,396.96,393.63
+2012,6,41075,2012.4563,395.97,393.48,396.31,393.84,395.97,393.48
+2012,7,41105,2012.5383,394.6,393.84,394.79,394.06,394.6,393.84
+2012,8,41136,2012.623,392.61,394.14,392.72,394.3,392.61,394.14
+2012,9,41167,2012.7077,391.2,394.63,391.09,394.54,391.2,394.63
+2012,10,41197,2012.7896,391.09,394.63,391.25,394.77,391.09,394.63
+2012,11,41228,2012.8743,393.03,395.24,392.83,395.02,393.03,395.24
+2012,12,41258,2012.9563,394.42,395.32,394.36,395.25,394.42,395.32
+2013,1,41289,2013.0411,395.69,395.64,395.55,395.48,395.69,395.64
+2013,2,41320,2013.126,396.94,396.19,396.47,395.71,396.94,396.19
+2013,3,41348,2013.2027,397.35,395.84,397.44,395.91,397.35,395.84
+2013,4,41379,2013.2877,398.44,395.71,398.88,396.12,398.44,395.71
+2013,5,41409,2013.3699,400.06,396.72,399.66,396.33,400.06,396.72
+2013,6,41440,2013.4548,398.95,396.43,399.03,396.53,398.95,396.43
+2013,7,41470,2013.537,397.45,396.66,397.48,396.72,397.45,396.66
+2013,8,41501,2013.6219,395.49,397,395.37,396.91,395.49,397
+2013,9,41532,2013.7068,393.48,396.91,393.65,397.1,393.48,396.91
+2013,10,41562,2013.789,393.77,397.33,393.74,397.28,393.77,397.33
+2013,11,41593,2013.874,395.27,397.5,395.26,397.46,395.27,397.5
+2013,12,41623,2013.9562,396.9,397.81,396.74,397.64,396.9,397.81
+2014,1,41654,2014.0411,398.01,397.96,397.87,397.81,398.01,397.96
+2014,2,41685,2014.126,398.18,397.43,398.74,397.98,398.18,397.43
+2014,3,41713,2014.2027,399.56,398.04,399.67,398.13,399.56,398.04
+2014,4,41744,2014.2877,401.44,398.69,401.06,398.3,401.44,398.69
+2014,5,41774,2014.3699,401.99,398.64,401.8,398.46,401.99,398.64
+2014,6,41805,2014.4548,401.41,398.88,401.13,398.62,401.41,398.88
+2014,7,41835,2014.537,399.17,398.37,399.54,398.77,399.17,398.37
+2014,8,41866,2014.6219,397.3,398.81,397.38,398.93,397.3,398.81
+2014,9,41897,2014.7068,395.49,398.93,395.64,399.1,395.49,398.93
+2014,10,41927,2014.789,395.74,399.3,395.7,399.26,395.74,399.3
+2014,11,41958,2014.874,397.32,399.55,397.21,399.43,397.32,399.55
+2014,12,41988,2014.9562,398.89,399.8,398.69,399.59,398.89,399.8
+2015,1,42019,2015.0411,399.94,399.89,399.83,399.76,399.94,399.89
+2015,2,42050,2015.126,400.39,399.64,400.71,399.94,400.39,399.64
+2015,3,42078,2015.2027,401.6,400.07,401.65,400.11,401.6,400.07
+2015,4,42109,2015.2877,403.53,400.77,403.07,400.3,403.53,400.77
+2015,5,42139,2015.3699,404.04,400.68,403.85,400.5,404.04,400.68
+2015,6,42170,2015.4548,402.81,400.27,403.23,400.72,402.81,400.27
+2015,7,42200,2015.537,401.54,400.73,401.72,400.95,401.54,400.73
+2015,8,42231,2015.6219,398.93,400.44,399.66,401.21,398.93,400.44
+2015,9,42262,2015.7068,397.43,400.88,398.03,401.5,397.43,400.88
+2015,10,42292,2015.789,398.21,401.79,398.23,401.79,398.21,401.79
+2015,11,42323,2015.874,400.17,402.41,399.89,402.11,400.17,402.41
+2015,12,42353,2015.9562,401.82,402.74,401.52,402.42,401.82,402.74
+2016,1,42384,2016.041,402.58,402.53,402.8,402.73,402.58,402.53
+2016,2,42415,2016.1257,404.09,403.33,403.81,403.04,404.09,403.33
+2016,3,42444,2016.2049,404.79,403.23,404.89,403.32,404.79,403.23
+2016,4,42475,2016.2896,407.5,404.71,406.4,403.6,407.5,404.71
+2016,5,42505,2016.3716,407.59,404.22,407.21,403.85,407.59,404.22
+2016,6,42536,2016.4563,406.94,404.42,406.59,404.09,406.94,404.42
+2016,7,42566,2016.5383,404.43,403.66,405.05,404.31,404.43,403.66
+2016,8,42597,2016.623,402.17,403.72,402.95,404.54,402.17,403.72
+2016,9,42628,2016.7077,400.94,404.42,401.26,404.76,400.94,404.42
+2016,10,42658,2016.7896,401.43,405.01,401.4,404.97,401.43,405.01
+2016,11,42689,2016.8743,403.57,405.81,402.96,405.18,403.57,405.81
+2016,12,42719,2016.9563,404.48,405.4,404.47,405.37,404.48,405.4
+2017,1,42750,2017.0411,406,405.95,405.63,405.56,406,405.95
+2017,2,42781,2017.126,406.57,405.81,406.52,405.74,406.57,405.81
+2017,3,42809,2017.2027,406.99,405.45,407.45,405.9,406.99,405.45
+2017,4,42840,2017.2877,408.88,406.11,408.86,406.07,408.88,406.11
+2017,5,42870,2017.3699,409.84,406.46,409.6,406.23,409.84,406.46
+2017,6,42901,2017.4548,409.05,406.5,408.92,406.39,409.05,406.5
+2017,7,42931,2017.537,407.13,406.32,407.31,406.54,407.13,406.32
+2017,8,42962,2017.6219,405.17,406.7,405.13,406.7,405.17,406.7
+2017,9,42993,2017.7068,403.2,406.67,403.36,406.85,403.2,406.67
+2017,10,43023,2017.789,403.57,407.17,403.42,407,403.57,407.17
+2017,11,43054,2017.874,405.1,407.36,404.92,407.15,405.1,407.36
+2017,12,43084,2017.9562,406.68,407.61,406.4,407.3,406.68,407.61
+2018,1,43115,2018.0411,407.98,407.93,407.52,407.45,407.98,407.93
+2018,2,43146,2018.126,408.28,407.51,408.38,407.61,408.28,407.51
+2018,3,43174,2018.2027,409.19,407.65,409.32,407.76,409.19,407.65
+2018,4,43205,2018.2877,410.24,407.46,410.74,407.94,410.24,407.46
+2018,5,43235,2018.3699,411.23,407.85,411.52,408.13,411.23,407.85
+2018,6,43266,2018.4548,410.81,408.25,410.9,408.36,410.81,408.25
+2018,7,43296,2018.537,408.83,408.02,409.36,408.59,408.83,408.02
+2018,8,43327,2018.6219,407.02,408.56,407.28,408.85,407.02,408.56
+2018,9,43358,2018.7068,405.52,409.01,405.62,409.12,405.52,409.01
+2018,10,43388,2018.789,405.93,409.54,405.79,409.39,405.93,409.54
+2018,11,43419,2018.874,408.05,410.31,407.43,409.66,408.05,410.31
+2018,12,43449,2018.9562,409.16,410.09,409.02,409.92,409.16,410.09
+2019,1,43480,2019.0411,410.85,410.8,410.25,410.18,410.85,410.8
+2019,2,43511,2019.126,411.59,410.83,411.2,410.43,411.59,410.83
+2019,3,43539,2019.2027,411.93,410.39,412.2,410.64,411.93,410.39
+2019,4,43570,2019.2877,413.46,410.68,413.67,410.86,413.46,410.68
+2019,5,43600,2019.3699,414.76,411.36,414.48,411.08,414.76,411.36
+2019,6,43631,2019.4548,413.89,411.32,413.85,411.3,413.89,411.32
+2019,7,43661,2019.537,411.78,410.97,412.29,411.51,411.78,410.97
+2019,8,43692,2019.6219,410.01,411.55,410.16,411.74,410.01,411.55
+2019,9,43723,2019.7068,408.48,411.98,408.45,411.96,408.48,411.98
+2019,10,43753,2019.789,408.37,411.99,408.57,412.18,408.37,411.99
+2019,11,43784,2019.874,410.22,412.49,410.16,412.4,410.22,412.49
+2019,12,43814,2019.9562,411.78,412.71,411.7,412.61,411.78,412.71
+2020,1,43845,2020.041,413.38,413.32,412.89,412.83,413.38,413.32
+2020,2,43876,2020.1257,414.03,413.26,413.81,413.03,414.03,413.26
+2020,3,43905,2020.2049,414.44,412.87,414.82,413.23,414.44,412.87
+2020,4,43936,2020.2896,416.11,413.29,416.27,413.43,416.11,413.29
+2020,5,43966,2020.3716,417.1,413.69,417.03,413.63,417.1,413.69
+2020,6,43997,2020.4563,416.23,413.68,416.36,413.83,416.23,413.68
+2020,7,44027,2020.5383,414.47,413.68,414.78,414.03,414.47,413.68
+2020,8,44058,2020.623,412.53,414.1,412.63,414.23,412.53,414.1
+2020,9,44089,2020.7077,411.19,414.7,410.9,414.44,411.19,414.7
+2020,10,44119,2020.7896,411.15,414.78,411.02,414.63,411.15,414.78
+2020,11,44150,2020.8743,412.88,415.15,412.58,414.82,412.88,415.15
+2020,12,44180,2020.9563,413.89,414.82,414.09,415,413.89,414.82
+2021,1,44211,2021.0411,415.17,415.11,415.24,415.17,415.17,415.11
+2021,2,44242,2021.126,416.47,415.7,416.13,415.35,416.47,415.7
+2021,3,44270,2021.2027,417.14,415.59,417.06,415.5,417.14,415.59
+2021,4,44301,2021.2877,418.24,415.44,418.48,415.66,418.24,415.44
+2021,5,44331,2021.3699,418.92,415.5,419.23,415.81,418.92,415.5
+2021,6,44362,2021.4548,418.73,416.14,-99.99,-99.99,418.73,416.14
+2021,7,44392,2021.537,-99.99,-99.99,-99.99,-99.99,-99.99,-99.99
+2021,8,44423,2021.6219,-99.99,-99.99,-99.99,-99.99,-99.99,-99.99
+2021,9,44454,2021.7068,-99.99,-99.99,-99.99,-99.99,-99.99,-99.99
+2021,10,44484,2021.789,-99.99,-99.99,-99.99,-99.99,-99.99,-99.99
+2021,11,44515,2021.874,-99.99,-99.99,-99.99,-99.99,-99.99,-99.99
+2021,12,44545,2021.9562,-99.99,-99.99,-99.99,-99.99,-99.99,-99.99
diff --git a/module3/exo3/monthly_in_situ_co2_mlo.csv b/module3/exo3/monthly_in_situ_co2_mlo.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c7a302bb2015491a30fe2b28a3d0c4022850613f
--- /dev/null
+++ b/module3/exo3/monthly_in_situ_co2_mlo.csv
@@ -0,0 +1,825 @@
+"-------------------------------------------------------------------------------------------"
+" Atmospheric CO2 concentrations (ppm) derived from in situ air measurements                "
+" at Mauna Loa, Observatory, Hawaii: Latitude 19.5°N Longitude 155.6°W Elevation 3397m      "
+"                                                                                           "
+" Source: R. F. Keeling, S. J. Walker, S. C. Piper and A. F. Bollenbacher                   "
+" Scripps CO2 Program ( http://scrippsco2.ucsd.edu )                                        "
+" Scripps Institution of Oceanography (SIO)                                                 "
+" University of California                                                                  "
+" La Jolla, California USA 92093-0244                                                       "
+"                                                                                           "
+" Status of data and correspondence:                                                        "
+"                                                                                           "
+" These data are subject to revision based on recalibration of standard gases. Questions    "
+" about the data should be directed to Dr. Ralph Keeling (rkeeling@ucsd.edu), Stephen Walker"
+" (sjwalker@ucsd.edu) and Stephen Piper (scpiper@ucsd.edu), Scripps CO2 Program.            "
+"                                                                                           "
+" Baseline data in this file through 01-Jul-2021 from archive dated 02-Jul-2021 09:04:47    "
+"                                                                                           "
+"-------------------------------------------------------------------------------------------"
+"                                                                                           "
+" Please cite as:                                                                           "
+"                                                                                           "
+" C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and       "
+" H. A. Meijer, Exchanges of atmospheric CO2 and 13CO2 with the terrestrial biosphere and   "
+" oceans from 1978 to 2000.  I. Global aspects, SIO Reference Series, No. 01-06, Scripps    "
+" Institution of Oceanography, San Diego, 88 pages, 2001.                                   "
+"                                                                                           "
+" If it is necessary to cite a peer-reviewed article, please cite as:                       "
+"                                                                                           "
+" C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and       "
+" H. A. Meijer, Atmospheric CO2 and 13CO2 exchange with the terrestrial biosphere and       "
+" oceans from 1978 to 2000: observations and carbon cycle implications, pages 83-113,       "
+" in "A History of Atmospheric CO2 and its effects on Plants, Animals, and Ecosystems",     "
+" editors, Ehleringer, J.R., T. E. Cerling, M. D. Dearing, Springer Verlag,                 "
+" New York, 2005.                                                                           "
+"                                                                                           "
+"-------------------------------------------------------------------------------------------"
+"                                                                                           "
+" The data file below contains 10 columns.  Columns 1-4 give the dates in several redundant "
+" formats. Column 5 below gives monthly Mauna Loa CO2 concentrations in micro-mol CO2 per   "
+" mole (ppm), reported on the 2012 SIO manometric mole fraction scale.  This is the        "
+" standard version of the data most often sought.  The monthly values have been adjusted    "
+" to 24:00 hours on the 15th of each month.  Column 6 gives the same data after a seasonal  "
+" adjustment to remove the quasi-regular seasonal cycle.  The adjustment involves           "
+" subtracting from the data a 4-harmonic fit with a linear gain factor.  Column 7 is a      "
+" smoothed version of the data generated from a stiff cubic spline function plus 4-harmonic "
+" functions with linear gain.  Column 8 is the same smoothed version with the seasonal      "
+" cycle removed.  Column 9 is identical to Column 5 except that the missing values from     "
+" Column 5 have been filled with values from Column 7.  Column 10 is identical to Column 6  "
+" except missing values have been filled with values from Column 8.  Missing values are     "
+" denoted by -99.99                                                                         "
+"                                                                                           "
+" CO2 concentrations are measured on the '12' calibration scale                             "
+"                                                                                           "
+  Yr, Mn,    Date,      Date,     CO2,seasonally,        fit,  seasonally,      CO2, seasonally
+    ,   ,        ,          ,        ,  adjusted,           ,adjusted fit,   filled,adjusted filled
+    ,   ,   Excel,          ,   [ppm],    [ppm] ,      [ppm],    [ppm],       [ppm],    [ppm]
+1958, 01,   21200, 1958.0411,   -99.99,   -99.99,     -99.99,   -99.99,     -99.99,   -99.99
+1958, 02,   21231, 1958.1260,   -99.99,   -99.99,     -99.99,   -99.99,     -99.99,   -99.99
+1958, 03,   21259, 1958.2027,   315.70,   314.43,     316.19,   314.90,     315.70,   314.43
+1958, 04,   21290, 1958.2877,   317.45,   315.16,     317.30,   314.98,     317.45,   315.16
+1958, 05,   21320, 1958.3699,   317.51,   314.71,     317.86,   315.06,     317.51,   314.71
+1958, 06,   21351, 1958.4548,   -99.99,   -99.99,     317.24,   315.14,     317.24,   315.14
+1958, 07,   21381, 1958.5370,   315.86,   315.19,     315.86,   315.22,     315.86,   315.19
+1958, 08,   21412, 1958.6219,   314.93,   316.19,     313.99,   315.29,     314.93,   316.19
+1958, 09,   21443, 1958.7068,   313.21,   316.09,     312.45,   315.35,     313.21,   316.09
+1958, 10,   21473, 1958.7890,   -99.99,   -99.99,     312.43,   315.41,     312.43,   315.41
+1958, 11,   21504, 1958.8740,   313.33,   315.20,     313.61,   315.46,     313.33,   315.20
+1958, 12,   21534, 1958.9562,   314.67,   315.43,     314.76,   315.51,     314.67,   315.43
+1959, 01,   21565, 1959.0411,   315.58,   315.54,     315.62,   315.57,     315.58,   315.54
+1959, 02,   21596, 1959.1260,   316.49,   315.85,     316.27,   315.63,     316.49,   315.85
+1959, 03,   21624, 1959.2027,   316.65,   315.37,     316.98,   315.69,     316.65,   315.37
+1959, 04,   21655, 1959.2877,   317.72,   315.41,     318.09,   315.77,     317.72,   315.41
+1959, 05,   21685, 1959.3699,   318.29,   315.48,     318.66,   315.85,     318.29,   315.48
+1959, 06,   21716, 1959.4548,   318.15,   316.02,     318.05,   315.94,     318.15,   316.02
+1959, 07,   21746, 1959.5370,   316.54,   315.87,     316.67,   316.03,     316.54,   315.87
+1959, 08,   21777, 1959.6219,   314.80,   316.07,     314.82,   316.12,     314.80,   316.07
+1959, 09,   21808, 1959.7068,   313.84,   316.73,     313.31,   316.22,     313.84,   316.73
+1959, 10,   21838, 1959.7890,   313.33,   316.33,     313.32,   316.31,     313.33,   316.33
+1959, 11,   21869, 1959.8740,   314.81,   316.69,     314.53,   316.39,     314.81,   316.69
+1959, 12,   21899, 1959.9562,   315.58,   316.35,     315.72,   316.47,     315.58,   316.35
+1960, 01,   21930, 1960.0410,   316.43,   316.39,     316.61,   316.56,     316.43,   316.39
+1960, 02,   21961, 1960.1257,   316.98,   316.35,     317.28,   316.64,     316.98,   316.35
+1960, 03,   21990, 1960.2049,   317.58,   316.27,     318.03,   316.71,     317.58,   316.27
+1960, 04,   22021, 1960.2896,   319.03,   316.70,     319.15,   316.79,     319.03,   316.70
+1960, 05,   22051, 1960.3716,   320.04,   317.21,     319.68,   316.86,     320.04,   317.21
+1960, 06,   22082, 1960.4563,   319.58,   317.47,     319.02,   316.93,     319.58,   317.47
+1960, 07,   22112, 1960.5383,   318.18,   317.53,     317.60,   316.98,     318.18,   317.53
+1960, 08,   22143, 1960.6230,   315.90,   317.20,     315.68,   317.01,     315.90,   317.20
+1960, 09,   22174, 1960.7077,   314.17,   317.08,     314.12,   317.05,     314.17,   317.08
+1960, 10,   22204, 1960.7896,   313.83,   316.84,     314.08,   317.07,     313.83,   316.84
+1960, 11,   22235, 1960.8743,   315.00,   316.88,     315.25,   317.11,     315.00,   316.88
+1960, 12,   22265, 1960.9563,   316.19,   316.96,     316.39,   317.15,     316.19,   316.96
+1961, 01,   22296, 1961.0411,   316.89,   316.85,     317.25,   317.20,     316.89,   316.85
+1961, 02,   22327, 1961.1260,   317.70,   317.07,     317.91,   317.26,     317.70,   317.07
+1961, 03,   22355, 1961.2027,   318.54,   317.25,     318.63,   317.33,     318.54,   317.25
+1961, 04,   22386, 1961.2877,   319.48,   317.15,     319.75,   317.41,     319.48,   317.15
+1961, 05,   22416, 1961.3699,   320.58,   317.75,     320.33,   317.50,     320.58,   317.75
+1961, 06,   22447, 1961.4548,   319.77,   317.63,     319.71,   317.59,     319.77,   317.63
+1961, 07,   22477, 1961.5370,   318.56,   317.89,     318.33,   317.68,     318.56,   317.89
+1961, 08,   22508, 1961.6219,   316.79,   318.07,     316.45,   317.76,     316.79,   318.07
+1961, 09,   22539, 1961.7068,   314.99,   317.90,     314.92,   317.85,     314.99,   317.90
+1961, 10,   22569, 1961.7890,   315.31,   318.33,     314.91,   317.92,     315.31,   318.33
+1961, 11,   22600, 1961.8740,   316.10,   318.00,     316.12,   317.99,     316.10,   318.00
+1961, 12,   22630, 1961.9562,   317.01,   317.78,     317.30,   318.06,     317.01,   317.78
+1962, 01,   22661, 1962.0411,   317.94,   317.90,     318.18,   318.13,     317.94,   317.90
+1962, 02,   22692, 1962.1260,   318.55,   317.91,     318.84,   318.19,     318.55,   317.91
+1962, 03,   22720, 1962.2027,   319.68,   318.39,     319.56,   318.26,     319.68,   318.39
+1962, 04,   22751, 1962.2877,   320.57,   318.24,     320.67,   318.32,     320.57,   318.24
+1962, 05,   22781, 1962.3699,   321.02,   318.17,     321.23,   318.39,     321.02,   318.17
+1962, 06,   22812, 1962.4548,   320.62,   318.47,     320.58,   318.45,     320.62,   318.47
+1962, 07,   22842, 1962.5370,   319.61,   318.93,     319.16,   318.50,     319.61,   318.93
+1962, 08,   22873, 1962.6219,   317.40,   318.69,     317.24,   318.56,     317.40,   318.69
+1962, 09,   22904, 1962.7068,   316.25,   319.17,     315.66,   318.60,     316.25,   319.17
+1962, 10,   22934, 1962.7890,   315.42,   318.45,     315.62,   318.64,     315.42,   318.45
+1962, 11,   22965, 1962.8740,   316.69,   318.59,     316.80,   318.68,     316.69,   318.59
+1962, 12,   22995, 1962.9562,   317.70,   318.47,     317.96,   318.72,     317.70,   318.47
+1963, 01,   23026, 1963.0411,   318.74,   318.70,     318.82,   318.76,     318.74,   318.70
+1963, 02,   23057, 1963.1260,   319.07,   318.43,     319.46,   318.81,     319.07,   318.43
+1963, 03,   23085, 1963.2027,   319.86,   318.56,     320.16,   318.85,     319.86,   318.56
+1963, 04,   23116, 1963.2877,   321.38,   319.05,     321.26,   318.91,     321.38,   319.05
+1963, 05,   23146, 1963.3699,   322.25,   319.39,     321.81,   318.96,     322.25,   319.39
+1963, 06,   23177, 1963.4548,   321.48,   319.32,     321.15,   319.01,     321.48,   319.32
+1963, 07,   23207, 1963.5370,   319.74,   319.06,     319.71,   319.06,     319.74,   319.06
+1963, 08,   23238, 1963.6219,   317.77,   319.06,     317.78,   319.10,     317.77,   319.06
+1963, 09,   23269, 1963.7068,   316.21,   319.14,     316.19,   319.14,     316.21,   319.14
+1963, 10,   23299, 1963.7890,   315.99,   319.02,     316.16,   319.18,     315.99,   319.02
+1963, 11,   23330, 1963.8740,   317.07,   318.97,     317.34,   319.23,     317.07,   318.97
+1963, 12,   23360, 1963.9562,   318.35,   319.13,     318.51,   319.27,     318.35,   319.13
+1964, 01,   23391, 1964.0410,   319.57,   319.53,     319.37,   319.32,     319.57,   319.53
+1964, 02,   23422, 1964.1257,   -99.99,   -99.99,     320.02,   319.37,     320.02,   319.37
+1964, 03,   23451, 1964.2049,   -99.99,   -99.99,     320.75,   319.41,     320.75,   319.41
+1964, 04,   23482, 1964.2896,   -99.99,   -99.99,     321.84,   319.45,     321.84,   319.45
+1964, 05,   23512, 1964.3716,   322.25,   319.39,     322.35,   319.49,     322.25,   319.39
+1964, 06,   23543, 1964.4563,   321.89,   319.75,     321.65,   319.53,     321.89,   319.75
+1964, 07,   23573, 1964.5383,   320.44,   319.78,     320.19,   319.56,     320.44,   319.78
+1964, 08,   23604, 1964.6230,   318.69,   320.01,     318.23,   319.58,     318.69,   320.01
+1964, 09,   23635, 1964.7077,   316.71,   319.66,     316.63,   319.60,     316.71,   319.66
+1964, 10,   23665, 1964.7896,   316.87,   319.92,     316.59,   319.62,     316.87,   319.92
+1964, 11,   23696, 1964.8743,   317.68,   319.59,     317.75,   319.64,     317.68,   319.59
+1964, 12,   23726, 1964.9563,   318.71,   319.49,     318.89,   319.66,     318.71,   319.49
+1965, 01,   23757, 1965.0411,   319.44,   319.40,     319.74,   319.68,     319.44,   319.40
+1965, 02,   23788, 1965.1260,   320.44,   319.80,     320.38,   319.72,     320.44,   319.80
+1965, 03,   23816, 1965.2027,   320.89,   319.59,     321.09,   319.77,     320.89,   319.59
+1965, 04,   23847, 1965.2877,   322.14,   319.78,     322.20,   319.83,     322.14,   319.78
+1965, 05,   23877, 1965.3699,   322.17,   319.30,     322.78,   319.91,     322.17,   319.30
+1965, 06,   23908, 1965.4548,   321.87,   319.70,     322.15,   320.00,     321.87,   319.70
+1965, 07,   23938, 1965.5370,   321.21,   320.52,     320.76,   320.10,     321.21,   320.52
+1965, 08,   23969, 1965.6219,   318.87,   320.16,     318.88,   320.21,     318.87,   320.16
+1965, 09,   24000, 1965.7068,   317.82,   320.77,     317.35,   320.32,     317.82,   320.77
+1965, 10,   24030, 1965.7890,   317.30,   320.36,     317.38,   320.43,     317.30,   320.36
+1965, 11,   24061, 1965.8740,   318.87,   320.78,     318.65,   320.55,     318.87,   320.78
+1965, 12,   24091, 1965.9562,   319.42,   320.20,     319.90,   320.66,     319.42,   320.20
+1966, 01,   24122, 1966.0411,   320.62,   320.58,     320.84,   320.78,     320.62,   320.58
+1966, 02,   24153, 1966.1260,   321.60,   320.95,     321.56,   320.90,     321.60,   320.95
+1966, 03,   24181, 1966.2027,   322.39,   321.08,     322.33,   321.01,     322.39,   321.08
+1966, 04,   24212, 1966.2877,   323.70,   321.34,     323.50,   321.12,     323.70,   321.34
+1966, 05,   24242, 1966.3699,   324.08,   321.20,     324.10,   321.22,     324.08,   321.20
+1966, 06,   24273, 1966.4548,   323.75,   321.57,     323.48,   321.32,     323.75,   321.57
+1966, 07,   24303, 1966.5370,   322.38,   321.69,     322.06,   321.40,     322.38,   321.69
+1966, 08,   24334, 1966.6219,   320.36,   321.66,     320.15,   321.48,     320.36,   321.66
+1966, 09,   24365, 1966.7068,   318.64,   321.60,     318.57,   321.55,     318.64,   321.60
+1966, 10,   24395, 1966.7890,   318.10,   321.18,     318.56,   321.62,     318.10,   321.18
+1966, 11,   24426, 1966.8740,   319.78,   321.71,     319.78,   321.68,     319.78,   321.71
+1966, 12,   24456, 1966.9562,   321.03,   321.81,     320.97,   321.74,     321.03,   321.81
+1967, 01,   24487, 1967.0411,   322.33,   322.29,     321.86,   321.80,     322.33,   322.29
+1967, 02,   24518, 1967.1260,   322.50,   321.85,     322.52,   321.86,     322.50,   321.85
+1967, 03,   24546, 1967.2027,   323.03,   321.72,     323.23,   321.90,     323.03,   321.72
+1967, 04,   24577, 1967.2877,   324.42,   322.05,     324.35,   321.96,     324.42,   322.05
+1967, 05,   24607, 1967.3699,   325.00,   322.11,     324.90,   322.01,     325.00,   322.11
+1967, 06,   24638, 1967.4548,   324.09,   321.90,     324.24,   322.07,     324.09,   321.90
+1967, 07,   24668, 1967.5370,   322.54,   321.85,     322.80,   322.14,     322.54,   321.85
+1967, 08,   24699, 1967.6219,   320.92,   322.22,     320.86,   322.20,     320.92,   322.22
+1967, 09,   24730, 1967.7068,   319.25,   322.23,     319.28,   322.27,     319.25,   322.23
+1967, 10,   24760, 1967.7890,   319.39,   322.47,     319.28,   322.35,     319.39,   322.47
+1967, 11,   24791, 1967.8740,   320.73,   322.66,     320.51,   322.42,     320.73,   322.66
+1967, 12,   24821, 1967.9562,   321.96,   322.75,     321.72,   322.49,     321.96,   322.75
+1968, 01,   24852, 1968.0410,   322.57,   322.52,     322.63,   322.57,     322.57,   322.52
+1968, 02,   24883, 1968.1257,   323.15,   322.50,     323.31,   322.65,     323.15,   322.50
+1968, 03,   24912, 1968.2049,   323.89,   322.55,     324.09,   322.73,     323.89,   322.55
+1968, 04,   24943, 1968.2896,   325.02,   322.62,     325.24,   322.83,     325.02,   322.62
+1968, 05,   24973, 1968.3716,   325.57,   322.67,     325.82,   322.92,     325.57,   322.67
+1968, 06,   25004, 1968.4563,   325.36,   323.18,     325.18,   323.03,     325.36,   323.18
+1968, 07,   25034, 1968.5383,   324.14,   323.47,     323.78,   323.14,     324.14,   323.47
+1968, 08,   25065, 1968.6230,   322.11,   323.44,     321.88,   323.25,     322.11,   323.44
+1968, 09,   25096, 1968.7077,   320.33,   323.32,     320.36,   323.37,     320.33,   323.32
+1968, 10,   25126, 1968.7896,   320.25,   323.33,     320.41,   323.49,     320.25,   323.33
+1968, 11,   25157, 1968.8743,   321.32,   323.26,     321.70,   323.62,     321.32,   323.26
+1968, 12,   25187, 1968.9563,   322.89,   323.69,     322.97,   323.75,     322.89,   323.69
+1969, 01,   25218, 1969.0411,   324.00,   323.96,     323.94,   323.89,     324.00,   323.96
+1969, 02,   25249, 1969.1260,   324.42,   323.76,     324.69,   324.03,     324.42,   323.76
+1969, 03,   25277, 1969.2027,   325.63,   324.31,     325.50,   324.16,     325.63,   324.31
+1969, 04,   25308, 1969.2877,   326.66,   324.28,     326.71,   324.30,     326.66,   324.28
+1969, 05,   25338, 1969.3699,   327.38,   324.47,     327.35,   324.44,     327.38,   324.47
+1969, 06,   25369, 1969.4548,   326.71,   324.51,     326.75,   324.57,     326.71,   324.51
+1969, 07,   25399, 1969.5370,   325.88,   325.19,     325.36,   324.69,     325.88,   325.19
+1969, 08,   25430, 1969.6219,   323.66,   324.98,     323.45,   324.80,     323.66,   324.98
+1969, 09,   25461, 1969.7068,   322.38,   325.37,     321.89,   324.90,     322.38,   325.37
+1969, 10,   25491, 1969.7890,   321.78,   324.88,     321.90,   324.99,     321.78,   324.88
+1969, 11,   25522, 1969.8740,   322.85,   324.80,     323.16,   325.08,     322.85,   324.80
+1969, 12,   25552, 1969.9562,   324.12,   324.91,     324.38,   325.16,     324.12,   324.91
+1970, 01,   25583, 1970.0411,   325.06,   325.02,     325.30,   325.24,     325.06,   325.02
+1970, 02,   25614, 1970.1260,   325.98,   325.33,     325.99,   325.32,     325.98,   325.33
+1970, 03,   25642, 1970.2027,   326.93,   325.60,     326.74,   325.40,     326.93,   325.60
+1970, 04,   25673, 1970.2877,   328.13,   325.74,     327.89,   325.48,     328.13,   325.74
+1970, 05,   25703, 1970.3699,   328.08,   325.16,     328.47,   325.55,     328.08,   325.16
+1970, 06,   25734, 1970.4548,   327.67,   325.46,     327.82,   325.63,     327.67,   325.46
+1970, 07,   25764, 1970.5370,   326.34,   325.64,     326.37,   325.70,     326.34,   325.64
+1970, 08,   25795, 1970.6219,   324.69,   326.00,     324.42,   325.77,     324.69,   326.00
+1970, 09,   25826, 1970.7068,   323.10,   326.10,     322.81,   325.83,     323.10,   326.10
+1970, 10,   25856, 1970.7890,   323.06,   326.18,     322.78,   325.89,     323.06,   326.18
+1970, 11,   25887, 1970.8740,   324.01,   325.96,     324.00,   325.93,     324.01,   325.96
+1970, 12,   25917, 1970.9562,   325.13,   325.93,     325.19,   325.97,     325.13,   325.93
+1971, 01,   25948, 1971.0411,   326.17,   326.13,     326.06,   326.01,     326.17,   326.13
+1971, 02,   25979, 1971.1260,   326.68,   326.02,     326.72,   326.05,     326.68,   326.02
+1971, 03,   26007, 1971.2027,   327.18,   325.85,     327.43,   326.09,     327.18,   325.85
+1971, 04,   26038, 1971.2877,   327.79,   325.38,     328.55,   326.14,     327.79,   325.38
+1971, 05,   26068, 1971.3699,   328.93,   326.00,     329.12,   326.19,     328.93,   326.00
+1971, 06,   26099, 1971.4548,   328.57,   326.36,     328.46,   326.26,     328.57,   326.36
+1971, 07,   26129, 1971.5370,   327.36,   326.66,     327.00,   326.33,     327.36,   326.66
+1971, 08,   26160, 1971.6219,   325.43,   326.75,     325.05,   326.40,     325.43,   326.75
+1971, 09,   26191, 1971.7068,   323.36,   326.37,     323.44,   326.47,     323.36,   326.37
+1971, 10,   26221, 1971.7890,   323.56,   326.69,     323.43,   326.54,     323.56,   326.69
+1971, 11,   26252, 1971.8740,   324.80,   326.75,     324.69,   326.62,     324.80,   326.75
+1971, 12,   26282, 1971.9562,   326.01,   326.81,     325.91,   326.70,     326.01,   326.81
+1972, 01,   26313, 1972.0410,   326.77,   326.73,     326.84,   326.78,     326.77,   326.73
+1972, 02,   26344, 1972.1257,   327.63,   326.97,     327.55,   326.88,     327.63,   326.97
+1972, 03,   26373, 1972.2049,   327.75,   326.39,     328.35,   326.98,     327.75,   326.39
+1972, 04,   26404, 1972.2896,   329.72,   327.29,     329.55,   327.10,     329.72,   327.29
+1972, 05,   26434, 1972.3716,   330.07,   327.13,     330.16,   327.23,     330.07,   327.13
+1972, 06,   26465, 1972.4563,   329.09,   326.88,     329.56,   327.38,     329.09,   326.88
+1972, 07,   26495, 1972.5383,   328.04,   327.37,     328.18,   327.54,     328.04,   327.37
+1972, 08,   26526, 1972.6230,   326.32,   327.67,     326.33,   327.72,     326.32,   327.67
+1972, 09,   26557, 1972.7077,   324.84,   327.87,     324.86,   327.91,     324.84,   327.87
+1972, 10,   26587, 1972.7896,   325.20,   328.33,     324.99,   328.10,     325.20,   328.33
+1972, 11,   26618, 1972.8743,   326.50,   328.46,     326.37,   328.31,     326.50,   328.46
+1972, 12,   26648, 1972.9563,   327.55,   328.36,     327.72,   328.51,     327.55,   328.36
+1973, 01,   26679, 1973.0411,   328.55,   328.50,     328.77,   328.72,     328.55,   328.50
+1973, 02,   26710, 1973.1260,   329.56,   328.90,     329.60,   328.93,     329.56,   328.90
+1973, 03,   26738, 1973.2027,   330.30,   328.96,     330.46,   329.11,     330.30,   328.96
+1973, 04,   26769, 1973.2877,   331.50,   329.09,     331.74,   329.30,     331.50,   329.09
+1973, 05,   26799, 1973.3699,   332.48,   329.53,     332.43,   329.48,     332.48,   329.53
+1973, 06,   26830, 1973.4548,   332.07,   329.84,     331.85,   329.64,     332.07,   329.84
+1973, 07,   26860, 1973.5370,   330.87,   330.17,     330.45,   329.77,     330.87,   330.17
+1973, 08,   26891, 1973.6219,   329.31,   330.64,     328.52,   329.88,     329.31,   330.64
+1973, 09,   26922, 1973.7068,   327.52,   330.55,     326.91,   329.96,     327.52,   330.55
+1973, 10,   26952, 1973.7890,   327.19,   330.33,     326.88,   330.02,     327.19,   330.33
+1973, 11,   26983, 1973.8740,   328.17,   330.13,     328.10,   330.05,     328.17,   330.13
+1973, 12,   27013, 1973.9562,   328.65,   329.45,     329.28,   330.07,     328.65,   329.45
+1974, 01,   27044, 1974.0411,   329.36,   329.31,     330.15,   330.10,     329.36,   329.31
+1974, 02,   27075, 1974.1260,   330.71,   330.05,     330.80,   330.12,     330.71,   330.05
+1974, 03,   27103, 1974.2027,   331.49,   330.14,     331.51,   330.15,     331.49,   330.14
+1974, 04,   27134, 1974.2877,   332.65,   330.23,     332.63,   330.19,     332.65,   330.23
+1974, 05,   27164, 1974.3699,   333.10,   330.14,     333.18,   330.22,     333.10,   330.14
+1974, 06,   27195, 1974.4548,   332.26,   330.02,     332.49,   330.27,     332.26,   330.02
+1974, 07,   27225, 1974.5370,   331.18,   330.48,     331.00,   330.32,     331.18,   330.48
+1974, 08,   27256, 1974.6219,   329.40,   330.74,     329.00,   330.37,     329.40,   330.74
+1974, 09,   27287, 1974.7068,   327.44,   330.49,     327.36,   330.42,     327.44,   330.49
+1974, 10,   27317, 1974.7890,   327.38,   330.54,     327.33,   330.47,     327.38,   330.54
+1974, 11,   27348, 1974.8740,   328.46,   330.44,     328.57,   330.53,     328.46,   330.44
+1974, 12,   27378, 1974.9562,   329.58,   330.39,     329.80,   330.59,     329.58,   330.39
+1975, 01,   27409, 1975.0411,   330.41,   330.36,     330.72,   330.66,     330.41,   330.36
+1975, 02,   27440, 1975.1260,   331.41,   330.74,     331.42,   330.74,     331.41,   330.74
+1975, 03,   27468, 1975.2027,   332.05,   330.70,     332.19,   330.83,     332.05,   330.70
+1975, 04,   27499, 1975.2877,   333.32,   330.88,     333.37,   330.92,     333.32,   330.88
+1975, 05,   27529, 1975.3699,   333.98,   331.01,     333.98,   331.01,     333.98,   331.01
+1975, 06,   27560, 1975.4548,   333.61,   331.37,     333.34,   331.11,     333.61,   331.37
+1975, 07,   27590, 1975.5370,   331.91,   331.20,     331.89,   331.21,     331.91,   331.20
+1975, 08,   27621, 1975.6219,   330.06,   331.41,     329.93,   331.30,     330.06,   331.41
+1975, 09,   27652, 1975.7068,   328.57,   331.62,     328.33,   331.40,     328.57,   331.62
+1975, 10,   27682, 1975.7890,   328.35,   331.51,     328.33,   331.48,     328.35,   331.51
+1975, 11,   27713, 1975.8740,   329.50,   331.48,     329.61,   331.57,     329.50,   331.48
+1975, 12,   27743, 1975.9562,   330.77,   331.58,     330.85,   331.65,     330.77,   331.58
+1976, 01,   27774, 1976.0410,   331.76,   331.71,     331.78,   331.73,     331.76,   331.71
+1976, 02,   27805, 1976.1257,   332.58,   331.91,     332.49,   331.81,     332.58,   331.91
+1976, 03,   27834, 1976.2049,   333.50,   332.13,     333.27,   331.88,     333.50,   332.13
+1976, 04,   27865, 1976.2896,   334.59,   332.13,     334.44,   331.96,     334.59,   332.13
+1976, 05,   27895, 1976.3716,   334.89,   331.91,     335.01,   332.04,     334.89,   331.91
+1976, 06,   27926, 1976.4563,   334.34,   332.11,     334.33,   332.12,     334.34,   332.11
+1976, 07,   27956, 1976.5383,   333.06,   332.38,     332.86,   332.20,     333.06,   332.38
+1976, 08,   27987, 1976.6230,   330.95,   332.32,     330.89,   332.30,     330.95,   332.32
+1976, 09,   28018, 1976.7077,   329.31,   332.39,     329.31,   332.40,     329.31,   332.39
+1976, 10,   28048, 1976.7896,   328.95,   332.12,     329.35,   332.51,     328.95,   332.12
+1976, 11,   28079, 1976.8743,   330.32,   332.30,     330.68,   332.64,     330.32,   332.30
+1976, 12,   28109, 1976.9563,   331.69,   332.51,     331.99,   332.78,     331.69,   332.51
+1977, 01,   28140, 1977.0411,   332.94,   332.89,     333.00,   332.94,     332.94,   332.89
+1977, 02,   28171, 1977.1260,   333.43,   332.76,     333.80,   333.12,     333.43,   332.76
+1977, 03,   28199, 1977.2027,   334.71,   333.35,     334.65,   333.28,     334.71,   333.35
+1977, 04,   28230, 1977.2877,   336.08,   333.63,     335.93,   333.47,     336.08,   333.63
+1977, 05,   28260, 1977.3699,   336.76,   333.77,     336.63,   333.65,     336.76,   333.77
+1977, 06,   28291, 1977.4548,   336.28,   334.02,     336.07,   333.83,     336.28,   334.02
+1977, 07,   28321, 1977.5370,   334.93,   334.21,     334.68,   334.00,     334.93,   334.21
+1977, 08,   28352, 1977.6219,   332.76,   334.11,     332.78,   334.16,     332.76,   334.11
+1977, 09,   28383, 1977.7068,   331.60,   334.68,     331.23,   334.32,     331.60,   334.68
+1977, 10,   28413, 1977.7890,   331.17,   334.36,     331.29,   334.47,     331.17,   334.36
+1977, 11,   28444, 1977.8740,   332.41,   334.41,     332.64,   334.61,     332.41,   334.41
+1977, 12,   28474, 1977.9562,   333.86,   334.67,     333.95,   334.75,     333.86,   334.67
+1978, 01,   28505, 1978.0411,   334.98,   334.93,     334.94,   334.89,     334.98,   334.93
+1978, 02,   28536, 1978.1260,   335.40,   334.72,     335.70,   335.02,     335.40,   334.72
+1978, 03,   28564, 1978.2027,   336.65,   335.29,     336.52,   335.14,     336.65,   335.29
+1978, 04,   28595, 1978.2877,   337.77,   335.31,     337.74,   335.26,     337.77,   335.31
+1978, 05,   28625, 1978.3699,   338.02,   335.02,     338.38,   335.38,     338.02,   335.02
+1978, 06,   28656, 1978.4548,   337.91,   335.64,     337.75,   335.50,     337.91,   335.64
+1978, 07,   28686, 1978.5370,   336.55,   335.83,     336.29,   335.61,     336.55,   335.83
+1978, 08,   28717, 1978.6219,   334.69,   336.05,     334.32,   335.71,     334.69,   336.05
+1978, 09,   28748, 1978.7068,   332.77,   335.85,     332.71,   335.81,     332.77,   335.85
+1978, 10,   28778, 1978.7890,   332.56,   335.75,     332.72,   335.90,     332.56,   335.75
+1978, 11,   28809, 1978.8740,   333.93,   335.93,     334.02,   336.00,     333.93,   335.93
+1978, 12,   28839, 1978.9562,   334.96,   335.78,     335.29,   336.09,     334.96,   335.78
+1979, 01,   28870, 1979.0411,   336.24,   336.19,     336.26,   336.20,     336.24,   336.19
+1979, 02,   28901, 1979.1260,   336.77,   336.09,     337.00,   336.32,     336.77,   336.09
+1979, 03,   28929, 1979.2027,   337.97,   336.61,     337.81,   336.42,     337.97,   336.61
+1979, 04,   28960, 1979.2877,   338.89,   336.43,     339.03,   336.55,     338.89,   336.43
+1979, 05,   28990, 1979.3699,   339.48,   336.48,     339.68,   336.68,     339.48,   336.48
+1979, 06,   29021, 1979.4548,   339.30,   337.02,     339.07,   336.81,     339.30,   337.02
+1979, 07,   29051, 1979.5370,   337.74,   337.02,     337.64,   336.95,     337.74,   337.02
+1979, 08,   29082, 1979.6219,   336.10,   337.46,     335.70,   337.09,     336.10,   337.46
+1979, 09,   29113, 1979.7068,   333.93,   337.02,     334.12,   337.23,     333.93,   337.02
+1979, 10,   29143, 1979.7890,   333.87,   337.08,     334.19,   337.38,     333.87,   337.08
+1979, 11,   29174, 1979.8740,   335.30,   337.31,     335.55,   337.54,     335.30,   337.31
+1979, 12,   29204, 1979.9562,   336.74,   337.56,     336.89,   337.69,     336.74,   337.56
+1980, 01,   29235, 1980.0410,   338.03,   337.99,     337.92,   337.86,     338.03,   337.99
+1980, 02,   29266, 1980.1257,   338.37,   337.69,     338.72,   338.03,     338.37,   337.69
+1980, 03,   29295, 1980.2049,   340.09,   338.69,     339.60,   338.19,     340.09,   338.69
+1980, 04,   29326, 1980.2896,   340.78,   338.28,     340.86,   338.35,     340.78,   338.28
+1980, 05,   29356, 1980.3716,   341.48,   338.47,     341.51,   338.50,     341.48,   338.47
+1980, 06,   29387, 1980.4563,   341.18,   338.92,     340.89,   338.65,     341.18,   338.92
+1980, 07,   29417, 1980.5383,   339.57,   338.88,     339.44,   338.78,     339.57,   338.88
+1980, 08,   29448, 1980.6230,   337.61,   339.00,     337.49,   338.91,     337.61,   339.00
+1980, 09,   29479, 1980.7077,   335.90,   339.01,     335.90,   339.04,     335.90,   339.01
+1980, 10,   29509, 1980.7896,   336.03,   339.24,     335.95,   339.15,     336.03,   339.24
+1980, 11,   29540, 1980.8743,   337.12,   339.13,     337.27,   339.26,     337.12,   339.13
+1980, 12,   29570, 1980.9563,   338.23,   339.06,     338.55,   339.36,     338.23,   339.06
+1981, 01,   29601, 1981.0411,   339.25,   339.20,     339.52,   339.46,     339.25,   339.20
+1981, 02,   29632, 1981.1260,   340.50,   339.81,     340.26,   339.56,     340.50,   339.81
+1981, 03,   29660, 1981.2027,   341.40,   340.03,     341.04,   339.65,     341.40,   340.03
+1981, 04,   29691, 1981.2877,   342.52,   340.04,     342.24,   339.74,     342.52,   340.04
+1981, 05,   29721, 1981.3699,   342.93,   339.90,     342.85,   339.83,     342.93,   339.90
+1981, 06,   29752, 1981.4548,   342.27,   339.98,     342.18,   339.91,     342.27,   339.98
+1981, 07,   29782, 1981.5370,   340.51,   339.78,     340.69,   340.00,     340.51,   339.78
+1981, 08,   29813, 1981.6219,   338.45,   339.82,     338.68,   340.09,     338.45,   339.82
+1981, 09,   29844, 1981.7068,   336.71,   339.83,     337.05,   340.18,     336.71,   339.83
+1981, 10,   29874, 1981.7890,   336.88,   340.10,     337.07,   340.28,     336.88,   340.10
+1981, 11,   29905, 1981.8740,   338.38,   340.40,     338.39,   340.39,     338.38,   340.40
+1981, 12,   29935, 1981.9562,   339.63,   340.46,     339.69,   340.50,     339.63,   340.46
+1982, 01,   29966, 1982.0411,   340.77,   340.73,     340.67,   340.61,     340.77,   340.73
+1982, 02,   29997, 1982.1260,   341.63,   340.95,     341.41,   340.72,     341.63,   340.95
+1982, 03,   30025, 1982.2027,   342.72,   341.34,     342.20,   340.81,     342.72,   341.34
+1982, 04,   30056, 1982.2877,   343.59,   341.10,     343.41,   340.90,     343.59,   341.10
+1982, 05,   30086, 1982.3699,   344.16,   341.12,     344.02,   340.98,     344.16,   341.12
+1982, 06,   30117, 1982.4548,   343.37,   341.07,     343.34,   341.06,     343.37,   341.07
+1982, 07,   30147, 1982.5370,   342.07,   341.35,     341.83,   341.14,     342.07,   341.35
+1982, 08,   30178, 1982.6219,   339.83,   341.20,     339.81,   341.22,     339.83,   341.20
+1982, 09,   30209, 1982.7068,   338.00,   341.12,     338.16,   341.30,     338.00,   341.12
+1982, 10,   30239, 1982.7890,   337.88,   341.12,     338.17,   341.40,     337.88,   341.12
+1982, 11,   30270, 1982.8740,   339.28,   341.31,     339.51,   341.51,     339.28,   341.31
+1982, 12,   30300, 1982.9562,   340.51,   341.34,     340.83,   341.64,     340.51,   341.34
+1983, 01,   30331, 1983.0411,   341.40,   341.35,     341.85,   341.79,     341.40,   341.35
+1983, 02,   30362, 1983.1260,   342.54,   341.86,     342.66,   341.97,     342.54,   341.86
+1983, 03,   30390, 1983.2027,   343.12,   341.73,     343.53,   342.13,     343.12,   341.73
+1983, 04,   30421, 1983.2877,   344.96,   342.46,     344.84,   342.33,     344.96,   342.46
+1983, 05,   30451, 1983.3699,   345.78,   342.73,     345.56,   342.52,     345.78,   342.73
+1983, 06,   30482, 1983.4548,   345.34,   343.03,     344.99,   342.71,     345.34,   343.03
+1983, 07,   30512, 1983.5370,   344.00,   343.27,     343.59,   342.89,     344.00,   343.27
+1983, 08,   30543, 1983.6219,   342.40,   343.78,     341.65,   343.06,     342.40,   343.78
+1983, 09,   30574, 1983.7068,   339.88,   343.02,     340.08,   343.23,     339.88,   343.02
+1983, 10,   30604, 1983.7890,   340.00,   343.25,     340.14,   343.38,     340.00,   343.25
+1983, 11,   30635, 1983.8740,   341.16,   343.19,     341.52,   343.53,     341.16,   343.19
+1983, 12,   30665, 1983.9562,   342.99,   343.82,     342.86,   343.67,     342.99,   343.82
+1984, 01,   30696, 1984.0410,   343.82,   343.77,     343.87,   343.82,     343.82,   343.77
+1984, 02,   30727, 1984.1257,   344.62,   343.94,     344.65,   343.96,     344.62,   343.94
+1984, 03,   30756, 1984.2049,   345.39,   343.97,     345.51,   344.08,     345.39,   343.97
+1984, 04,   30787, 1984.2896,   347.15,   344.62,     346.76,   344.21,     347.15,   344.62
+1984, 05,   30817, 1984.3716,   347.52,   344.47,     347.39,   344.34,     347.52,   344.47
+1984, 06,   30848, 1984.4563,   346.88,   344.59,     346.73,   344.46,     346.88,   344.59
+1984, 07,   30878, 1984.5383,   345.47,   344.76,     345.24,   344.57,     345.47,   344.76
+1984, 08,   30909, 1984.6230,   343.34,   344.75,     343.24,   344.68,     343.34,   344.75
+1984, 09,   30940, 1984.7077,   341.13,   344.29,     341.63,   344.80,     341.13,   344.29
+1984, 10,   30970, 1984.7896,   341.40,   344.65,     341.67,   344.91,     341.40,   344.65
+1984, 11,   31001, 1984.8743,   343.02,   345.06,     343.02,   345.03,     343.02,   345.06
+1984, 12,   31031, 1984.9563,   344.25,   345.08,     344.34,   345.15,     344.25,   345.08
+1985, 01,   31062, 1985.0411,   344.99,   344.95,     345.34,   345.28,     344.99,   344.95
+1985, 02,   31093, 1985.1260,   346.01,   345.32,     346.11,   345.40,     346.01,   345.32
+1985, 03,   31121, 1985.2027,   347.43,   346.04,     346.92,   345.51,     347.43,   346.04
+1985, 04,   31152, 1985.2877,   348.34,   345.83,     348.16,   345.63,     348.34,   345.83
+1985, 05,   31182, 1985.3699,   348.92,   345.86,     348.79,   345.73,     348.92,   345.86
+1985, 06,   31213, 1985.4548,   348.24,   345.92,     348.12,   345.82,     348.24,   345.92
+1985, 07,   31243, 1985.5370,   346.53,   345.80,     346.62,   345.91,     346.53,   345.80
+1985, 08,   31274, 1985.6219,   344.64,   346.03,     344.58,   346.00,     344.64,   346.03
+1985, 09,   31305, 1985.7068,   343.06,   346.21,     342.91,   346.08,     343.06,   346.21
+1985, 10,   31335, 1985.7890,   342.77,   346.04,     342.91,   346.17,     342.77,   346.04
+1985, 11,   31366, 1985.8740,   344.21,   346.26,     344.23,   346.26,     344.21,   346.26
+1985, 12,   31396, 1985.9562,   345.53,   346.37,     345.53,   346.35,     345.53,   346.37
+1986, 01,   31427, 1986.0411,   346.28,   346.23,     346.51,   346.45,     346.28,   346.23
+1986, 02,   31458, 1986.1260,   346.93,   346.24,     347.26,   346.56,     346.93,   346.24
+1986, 03,   31486, 1986.2027,   347.83,   346.43,     348.08,   346.67,     347.83,   346.43
+1986, 04,   31517, 1986.2877,   349.53,   347.01,     349.33,   346.79,     349.53,   347.01
+1986, 05,   31547, 1986.3699,   350.19,   347.12,     349.99,   346.92,     350.19,   347.12
+1986, 06,   31578, 1986.4548,   349.53,   347.20,     349.35,   347.05,     349.53,   347.20
+1986, 07,   31608, 1986.5370,   347.92,   347.18,     347.88,   347.17,     347.92,   347.18
+1986, 08,   31639, 1986.6219,   345.88,   347.27,     345.88,   347.30,     345.88,   347.27
+1986, 09,   31670, 1986.7068,   344.83,   348.00,     344.25,   347.43,     344.83,   348.00
+1986, 10,   31700, 1986.7890,   344.15,   347.43,     344.29,   347.55,     344.15,   347.43
+1986, 11,   31731, 1986.8740,   345.64,   347.69,     345.65,   347.69,     345.64,   347.69
+1986, 12,   31761, 1986.9562,   346.88,   347.72,     346.99,   347.82,     346.88,   347.72
+1987, 01,   31792, 1987.0411,   348.00,   347.95,     348.02,   347.96,     348.00,   347.95
+1987, 02,   31823, 1987.1260,   348.47,   347.77,     348.82,   348.11,     348.47,   347.77
+1987, 03,   31851, 1987.2027,   349.40,   348.00,     349.68,   348.26,     349.40,   348.00
+1987, 04,   31882, 1987.2877,   350.97,   348.44,     350.98,   348.44,     350.97,   348.44
+1987, 05,   31912, 1987.3699,   351.84,   348.75,     351.69,   348.61,     351.84,   348.75
+1987, 06,   31943, 1987.4548,   351.25,   348.91,     351.11,   348.80,     351.25,   348.91
+1987, 07,   31973, 1987.5370,   349.50,   348.76,     349.69,   348.98,     349.50,   348.76
+1987, 08,   32004, 1987.6219,   348.09,   349.48,     347.75,   349.18,     348.09,   349.48
+1987, 09,   32035, 1987.7068,   346.44,   349.61,     346.18,   349.37,     346.44,   349.61
+1987, 10,   32065, 1987.7890,   346.09,   349.38,     346.29,   349.56,     346.09,   349.38
+1987, 11,   32096, 1987.8740,   347.54,   349.60,     347.73,   349.77,     347.54,   349.60
+1987, 12,   32126, 1987.9562,   348.69,   349.54,     349.14,   349.97,     348.69,   349.54
+1988, 01,   32157, 1988.0410,   350.16,   350.12,     350.23,   350.17,     350.16,   350.12
+1988, 02,   32188, 1988.1257,   351.47,   350.77,     351.09,   350.38,     351.47,   350.77
+1988, 03,   32217, 1988.2049,   351.96,   350.52,     352.02,   350.58,     351.96,   350.52
+1988, 04,   32248, 1988.2896,   353.33,   350.77,     353.36,   350.78,     353.33,   350.77
+1988, 05,   32278, 1988.3716,   353.97,   350.88,     354.06,   350.97,     353.97,   350.88
+1988, 06,   32309, 1988.4563,   353.55,   351.23,     353.45,   351.15,     353.55,   351.23
+1988, 07,   32339, 1988.5383,   352.14,   351.43,     352.01,   351.33,     352.14,   351.43
+1988, 08,   32370, 1988.6230,   350.19,   351.62,     350.03,   351.50,     350.19,   351.62
+1988, 09,   32401, 1988.7077,   348.50,   351.69,     348.44,   351.65,     348.50,   351.69
+1988, 10,   32431, 1988.7896,   348.66,   351.95,     348.51,   351.79,     348.66,   351.95
+1988, 11,   32462, 1988.8743,   349.85,   351.91,     349.89,   351.93,     349.85,   351.91
+1988, 12,   32492, 1988.9563,   351.12,   351.97,     351.23,   352.05,     351.12,   351.97
+1989, 01,   32523, 1989.0411,   352.55,   352.50,     352.23,   352.17,     352.55,   352.50
+1989, 02,   32554, 1989.1260,   352.86,   352.16,     352.99,   352.28,     352.86,   352.16
+1989, 03,   32582, 1989.2027,   353.48,   352.07,     353.81,   352.38,     353.48,   352.07
+1989, 04,   32613, 1989.2877,   355.22,   352.67,     355.05,   352.49,     355.22,   352.67
+1989, 05,   32643, 1989.3699,   355.47,   352.37,     355.69,   352.59,     355.47,   352.37
+1989, 06,   32674, 1989.4548,   354.92,   352.57,     355.02,   352.69,     354.92,   352.57
+1989, 07,   32704, 1989.5370,   353.70,   352.95,     353.50,   352.79,     353.70,   352.95
+1989, 08,   32735, 1989.6219,   351.47,   352.87,     351.45,   352.88,     351.47,   352.87
+1989, 09,   32766, 1989.7068,   349.61,   352.80,     349.77,   352.98,     349.61,   352.80
+1989, 10,   32796, 1989.7890,   349.79,   353.10,     349.78,   353.08,     349.79,   353.10
+1989, 11,   32827, 1989.8740,   351.10,   353.17,     351.13,   353.18,     351.10,   353.17
+1989, 12,   32857, 1989.9562,   352.32,   353.17,     352.45,   353.28,     352.32,   353.17
+1990, 01,   32888, 1990.0411,   353.46,   353.42,     353.44,   353.38,     353.46,   353.42
+1990, 02,   32919, 1990.1260,   354.50,   353.80,     354.20,   353.48,     354.50,   353.80
+1990, 03,   32947, 1990.2027,   355.19,   353.77,     355.01,   353.58,     355.19,   353.77
+1990, 04,   32978, 1990.2877,   356.00,   353.45,     356.25,   353.68,     356.00,   353.45
+1990, 05,   33008, 1990.3699,   356.96,   353.85,     356.90,   353.79,     356.96,   353.85
+1990, 06,   33039, 1990.4548,   356.04,   353.68,     356.24,   353.90,     356.04,   353.68
+1990, 07,   33069, 1990.5370,   354.62,   353.88,     354.73,   354.02,     354.62,   353.88
+1990, 08,   33100, 1990.6219,   352.71,   354.12,     352.71,   354.15,     352.71,   354.12
+1990, 09,   33131, 1990.7068,   350.77,   353.98,     351.07,   354.29,     350.77,   353.98
+1990, 10,   33161, 1990.7890,   350.99,   354.31,     351.13,   354.43,     350.99,   354.31
+1990, 11,   33192, 1990.8740,   352.64,   354.72,     352.53,   354.59,     352.64,   354.72
+1990, 12,   33222, 1990.9562,   354.02,   354.87,     353.90,   354.73,     354.02,   354.87
+1991, 01,   33253, 1991.0411,   354.53,   354.48,     354.94,   354.88,     354.53,   354.48
+1991, 02,   33284, 1991.1260,   355.55,   354.85,     355.73,   355.02,     355.55,   354.85
+1991, 03,   33312, 1991.2027,   356.96,   355.54,     356.57,   355.14,     356.96,   355.54
+1991, 04,   33343, 1991.2877,   358.40,   355.84,     357.83,   355.25,     358.40,   355.84
+1991, 05,   33373, 1991.3699,   359.14,   356.01,     358.47,   355.35,     359.14,   356.01
+1991, 06,   33404, 1991.4548,   358.04,   355.68,     357.77,   355.42,     358.04,   355.68
+1991, 07,   33434, 1991.5370,   355.98,   355.23,     356.20,   355.49,     355.98,   355.23
+1991, 08,   33465, 1991.6219,   353.81,   355.23,     354.10,   355.55,     353.81,   355.23
+1991, 09,   33496, 1991.7068,   351.95,   355.17,     352.37,   355.60,     351.95,   355.17
+1991, 10,   33526, 1991.7890,   352.02,   355.35,     352.34,   355.66,     352.02,   355.35
+1991, 11,   33557, 1991.8740,   353.55,   355.63,     353.66,   355.73,     353.55,   355.63
+1991, 12,   33587, 1991.9562,   354.79,   355.64,     354.96,   355.79,     354.79,   355.64
+1992, 01,   33618, 1992.0410,   355.79,   355.74,     355.92,   355.86,     355.79,   355.74
+1992, 02,   33649, 1992.1257,   356.52,   355.82,     356.65,   355.93,     356.52,   355.82
+1992, 03,   33678, 1992.2049,   357.61,   356.16,     357.46,   356.00,     357.61,   356.16
+1992, 04,   33709, 1992.2896,   358.95,   356.36,     358.67,   356.06,     358.95,   356.36
+1992, 05,   33739, 1992.3716,   359.46,   356.33,     359.24,   356.11,     359.46,   356.33
+1992, 06,   33770, 1992.4563,   359.05,   356.70,     358.49,   356.16,     359.05,   356.70
+1992, 07,   33800, 1992.5383,   356.82,   356.10,     356.88,   356.20,     356.82,   356.10
+1992, 08,   33831, 1992.6230,   354.80,   356.24,     354.75,   356.23,     354.80,   356.24
+1992, 09,   33862, 1992.7077,   352.81,   356.04,     353.01,   356.26,     352.81,   356.04
+1992, 10,   33892, 1992.7896,   353.11,   356.44,     352.97,   356.29,     353.11,   356.44
+1992, 11,   33923, 1992.8743,   353.96,   356.05,     354.26,   356.33,     353.96,   356.05
+1992, 12,   33953, 1992.9563,   355.20,   356.06,     355.53,   356.37,     355.20,   356.06
+1993, 01,   33984, 1993.0411,   356.50,   356.45,     356.48,   356.42,     356.50,   356.45
+1993, 02,   34015, 1993.1260,   356.97,   356.26,     357.20,   356.48,     356.97,   356.26
+1993, 03,   34043, 1993.2027,   358.18,   356.75,     357.99,   356.55,     358.18,   356.75
+1993, 04,   34074, 1993.2877,   359.26,   356.68,     359.22,   356.62,     359.26,   356.68
+1993, 05,   34104, 1993.3699,   360.08,   356.94,     359.85,   356.70,     360.08,   356.94
+1993, 06,   34135, 1993.4548,   359.40,   357.02,     359.16,   356.80,     359.40,   357.02
+1993, 07,   34165, 1993.5370,   357.38,   356.62,     357.62,   356.90,     357.38,   356.62
+1993, 08,   34196, 1993.6219,   355.33,   356.75,     355.55,   357.01,     355.33,   356.75
+1993, 09,   34227, 1993.7068,   353.50,   356.74,     353.89,   357.14,     353.50,   356.74
+1993, 10,   34257, 1993.7890,   353.80,   357.15,     353.94,   357.28,     353.80,   357.15
+1993, 11,   34288, 1993.8740,   355.15,   357.25,     355.35,   357.43,     355.15,   357.25
+1993, 12,   34318, 1993.9562,   356.62,   357.48,     356.75,   357.59,     356.62,   357.48
+1994, 01,   34349, 1994.0411,   358.19,   358.14,     357.82,   357.76,     358.19,   358.14
+1994, 02,   34380, 1994.1260,   358.73,   358.02,     358.65,   357.93,     358.73,   358.02
+1994, 03,   34408, 1994.2027,   359.79,   358.36,     359.53,   358.08,     359.79,   358.36
+1994, 04,   34439, 1994.2877,   361.09,   358.50,     360.86,   358.25,     361.09,   358.50
+1994, 05,   34469, 1994.3699,   361.52,   358.36,     361.57,   358.42,     361.52,   358.36
+1994, 06,   34500, 1994.4548,   360.77,   358.39,     360.95,   358.59,     360.77,   358.39
+1994, 07,   34530, 1994.5370,   359.38,   358.62,     359.47,   358.75,     359.38,   358.62
+1994, 08,   34561, 1994.6219,   357.31,   358.73,     357.46,   358.93,     357.31,   358.73
+1994, 09,   34592, 1994.7068,   355.68,   358.92,     355.84,   359.11,     355.68,   358.92
+1994, 10,   34622, 1994.7890,   355.83,   359.19,     355.93,   359.28,     355.83,   359.19
+1994, 11,   34653, 1994.8740,   357.42,   359.53,     357.38,   359.47,     357.42,   359.53
+1994, 12,   34683, 1994.9562,   358.88,   359.74,     358.80,   359.65,     358.88,   359.74
+1995, 01,   34714, 1995.0411,   359.81,   359.76,     359.89,   359.83,     359.81,   359.76
+1995, 02,   34745, 1995.1260,   360.84,   360.13,     360.74,   360.02,     360.84,   360.13
+1995, 03,   34773, 1995.2027,   361.48,   360.05,     361.63,   360.18,     361.48,   360.05
+1995, 04,   34804, 1995.2877,   363.30,   360.71,     362.96,   360.35,     363.30,   360.71
+1995, 05,   34834, 1995.3699,   363.65,   360.48,     363.68,   360.52,     363.65,   360.48
+1995, 06,   34865, 1995.4548,   363.11,   360.72,     363.06,   360.68,     363.11,   360.72
+1995, 07,   34895, 1995.5370,   361.75,   360.99,     361.57,   360.84,     361.75,   360.99
+1995, 08,   34926, 1995.6219,   359.31,   360.74,     359.54,   361.01,     359.31,   360.74
+1995, 09,   34957, 1995.7068,   357.91,   361.17,     357.90,   361.17,     357.91,   361.17
+1995, 10,   34987, 1995.7890,   357.62,   360.99,     357.97,   361.33,     357.62,   360.99
+1995, 11,   35018, 1995.8740,   359.42,   361.54,     359.40,   361.49,     359.42,   361.54
+1995, 12,   35048, 1995.9562,   360.56,   361.42,     360.80,   361.64,     360.56,   361.42
+1996, 01,   35079, 1996.0410,   361.91,   361.86,     361.86,   361.80,     361.91,   361.86
+1996, 02,   35110, 1996.1257,   363.11,   362.39,     362.67,   361.95,     363.11,   362.39
+1996, 03,   35139, 1996.2049,   363.88,   362.42,     363.56,   362.08,     363.88,   362.42
+1996, 04,   35170, 1996.2896,   364.58,   361.96,     364.85,   362.20,     364.58,   361.96
+1996, 05,   35200, 1996.3716,   365.29,   362.11,     365.49,   362.32,     365.29,   362.11
+1996, 06,   35231, 1996.4563,   364.84,   362.46,     364.78,   362.43,     364.84,   362.46
+1996, 07,   35261, 1996.5383,   363.52,   362.79,     363.22,   362.53,     363.52,   362.79
+1996, 08,   35292, 1996.6230,   361.35,   362.81,     361.12,   362.62,     361.35,   362.81
+1996, 09,   35323, 1996.7077,   359.32,   362.59,     359.42,   362.71,     359.32,   362.59
+1996, 10,   35353, 1996.7896,   359.48,   362.85,     359.42,   362.79,     359.48,   362.85
+1996, 11,   35384, 1996.8743,   360.64,   362.75,     360.78,   362.87,     360.64,   362.75
+1996, 12,   35414, 1996.9563,   362.21,   363.07,     362.10,   362.94,     362.21,   363.07
+1997, 01,   35445, 1997.0411,   363.06,   363.02,     363.09,   363.03,     363.06,   363.02
+1997, 02,   35476, 1997.1260,   363.87,   363.16,     363.84,   363.12,     363.87,   363.16
+1997, 03,   35504, 1997.2027,   364.44,   363.00,     364.66,   363.20,     364.44,   363.00
+1997, 04,   35535, 1997.2877,   366.23,   363.62,     365.94,   363.31,     366.23,   363.62
+1997, 05,   35565, 1997.3699,   366.68,   363.50,     366.61,   363.42,     366.68,   363.50
+1997, 06,   35596, 1997.4548,   365.52,   363.11,     365.95,   363.56,     365.52,   363.11
+1997, 07,   35626, 1997.5370,   364.36,   363.60,     364.44,   363.71,     364.36,   363.60
+1997, 08,   35657, 1997.6219,   362.39,   363.83,     362.41,   363.89,     362.39,   363.83
+1997, 09,   35688, 1997.7068,   360.08,   363.35,     360.80,   364.09,     360.08,   363.35
+1997, 10,   35718, 1997.7890,   360.67,   364.06,     360.93,   364.31,     360.67,   364.06
+1997, 11,   35749, 1997.8740,   362.32,   364.45,     362.45,   364.55,     362.32,   364.45
+1997, 12,   35779, 1997.9562,   364.17,   365.04,     363.95,   364.80,     364.17,   365.04
+1998, 01,   35810, 1998.0411,   365.22,   365.17,     365.13,   365.07,     365.22,   365.17
+1998, 02,   35841, 1998.1260,   366.04,   365.32,     366.08,   365.35,     366.04,   365.32
+1998, 03,   35869, 1998.2027,   367.20,   365.75,     367.07,   365.60,     367.20,   365.75
+1998, 04,   35900, 1998.2877,   368.50,   365.89,     368.51,   365.87,     368.50,   365.89
+1998, 05,   35930, 1998.3699,   369.19,   366.00,     369.33,   366.14,     369.19,   366.00
+1998, 06,   35961, 1998.4548,   368.77,   366.35,     368.80,   366.40,     368.77,   366.35
+1998, 07,   35991, 1998.5370,   367.53,   366.76,     367.38,   366.64,     367.53,   366.76
+1998, 08,   36022, 1998.6219,   365.68,   367.12,     365.40,   366.88,     365.68,   367.12
+1998, 09,   36053, 1998.7068,   363.80,   367.09,     363.80,   367.10,     363.80,   367.09
+1998, 10,   36083, 1998.7890,   364.13,   367.54,     363.90,   367.29,     364.13,   367.54
+1998, 11,   36114, 1998.8740,   365.36,   367.49,     365.36,   367.47,     365.36,   367.49
+1998, 12,   36144, 1998.9562,   366.87,   367.74,     366.76,   367.62,     366.87,   367.74
+1999, 01,   36175, 1999.0411,   368.05,   368.00,     367.81,   367.75,     368.05,   368.00
+1999, 02,   36206, 1999.1260,   368.77,   368.05,     368.60,   367.86,     368.77,   368.05
+1999, 03,   36234, 1999.2027,   369.49,   368.03,     369.42,   367.95,     369.49,   368.03
+1999, 04,   36265, 1999.2877,   371.04,   368.41,     370.68,   368.03,     371.04,   368.41
+1999, 05,   36295, 1999.3699,   370.90,   367.70,     371.30,   368.10,     370.90,   367.70
+1999, 06,   36326, 1999.4548,   370.25,   367.83,     370.57,   368.17,     370.25,   367.83
+1999, 07,   36356, 1999.5370,   369.17,   368.40,     368.97,   368.24,     369.17,   368.40
+1999, 08,   36387, 1999.6219,   366.83,   368.28,     366.83,   368.31,     366.83,   368.28
+1999, 09,   36418, 1999.7068,   364.54,   367.83,     365.07,   368.39,     364.54,   367.83
+1999, 10,   36448, 1999.7890,   365.04,   368.45,     365.07,   368.47,     365.04,   368.45
+1999, 11,   36479, 1999.8740,   366.58,   368.72,     366.44,   368.55,     366.58,   368.72
+1999, 12,   36509, 1999.9562,   367.92,   368.79,     367.78,   368.64,     367.92,   368.79
+2000, 01,   36540, 2000.0410,   369.05,   369.00,     368.79,   368.73,     369.05,   369.00
+2000, 02,   36571, 2000.1257,   369.37,   368.65,     369.56,   368.82,     369.37,   368.65
+2000, 03,   36600, 2000.2049,   370.42,   368.94,     370.42,   368.92,     370.42,   368.94
+2000, 04,   36631, 2000.2896,   371.57,   368.91,     371.71,   369.03,     371.57,   368.91
+2000, 05,   36661, 2000.3716,   371.74,   368.53,     372.35,   369.15,     371.74,   368.53
+2000, 06,   36692, 2000.4563,   371.60,   369.19,     371.66,   369.28,     371.60,   369.19
+2000, 07,   36722, 2000.5383,   370.02,   369.29,     370.12,   369.41,     370.02,   369.29
+2000, 08,   36753, 2000.6230,   368.03,   369.51,     368.04,   369.56,     368.03,   369.51
+2000, 09,   36784, 2000.7077,   366.53,   369.85,     366.37,   369.70,     366.53,   369.85
+2000, 10,   36814, 2000.7896,   366.64,   370.06,     366.44,   369.85,     366.64,   370.06
+2000, 11,   36845, 2000.8743,   368.20,   370.34,     367.87,   369.99,     368.20,   370.34
+2000, 12,   36875, 2000.9563,   369.44,   370.31,     369.26,   370.12,     369.44,   370.31
+2001, 01,   36906, 2001.0411,   370.20,   370.15,     370.31,   370.24,     370.20,   370.15
+2001, 02,   36937, 2001.1260,   371.41,   370.69,     371.10,   370.37,     371.41,   370.69
+2001, 03,   36965, 2001.2027,   372.04,   370.57,     371.95,   370.47,     372.04,   370.57
+2001, 04,   36996, 2001.2877,   372.78,   370.14,     373.25,   370.59,     372.78,   370.14
+2001, 05,   37026, 2001.3699,   373.94,   370.72,     373.93,   370.71,     373.94,   370.72
+2001, 06,   37057, 2001.4548,   373.23,   370.79,     373.26,   370.84,     373.23,   370.79
+2001, 07,   37087, 2001.5370,   371.54,   370.76,     371.71,   370.98,     371.54,   370.76
+2001, 08,   37118, 2001.6219,   369.47,   370.93,     369.63,   371.12,     369.47,   370.93
+2001, 09,   37149, 2001.7068,   367.88,   371.19,     367.94,   371.28,     367.88,   371.19
+2001, 10,   37179, 2001.7890,   368.01,   371.45,     368.01,   371.43,     368.01,   371.45
+2001, 11,   37210, 2001.8740,   369.60,   371.75,     369.47,   371.59,     369.60,   371.75
+2001, 12,   37240, 2001.9562,   371.16,   372.04,     370.90,   371.76,     371.16,   372.04
+2002, 01,   37271, 2002.0411,   372.36,   372.31,     371.99,   371.93,     372.36,   372.31
+2002, 02,   37302, 2002.1260,   373.00,   372.28,     372.84,   372.10,     373.00,   372.28
+2002, 03,   37330, 2002.2027,   373.44,   371.97,     373.75,   372.26,     373.44,   371.97
+2002, 04,   37361, 2002.2877,   374.77,   372.13,     375.12,   372.45,     374.77,   372.13
+2002, 05,   37391, 2002.3699,   375.48,   372.25,     375.87,   372.64,     375.48,   372.25
+2002, 06,   37422, 2002.4548,   375.33,   372.89,     375.28,   372.85,     375.33,   372.89
+2002, 07,   37452, 2002.5370,   373.95,   373.17,     373.81,   373.07,     373.95,   373.17
+2002, 08,   37483, 2002.6219,   371.41,   372.87,     371.80,   373.29,     371.41,   372.87
+2002, 09,   37514, 2002.7068,   370.63,   373.95,     370.19,   373.53,     370.63,   373.95
+2002, 10,   37544, 2002.7890,   370.18,   373.62,     370.33,   373.76,     370.18,   373.62
+2002, 11,   37575, 2002.8740,   372.01,   374.17,     371.86,   373.99,     372.01,   374.17
+2002, 12,   37605, 2002.9562,   373.71,   374.59,     373.35,   374.21,     373.71,   374.59
+2003, 01,   37636, 2003.0411,   374.61,   374.56,     374.50,   374.44,     374.61,   374.56
+2003, 02,   37667, 2003.1260,   375.55,   374.82,     375.40,   374.66,     375.55,   374.82
+2003, 03,   37695, 2003.2027,   376.04,   374.57,     376.34,   374.85,     376.04,   374.57
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+2003, 05,   37756, 2003.3699,   378.28,   375.04,     378.51,   375.27,     378.28,   375.04
+2003, 06,   37787, 2003.4548,   378.07,   375.62,     377.90,   375.47,     378.07,   375.62
+2003, 07,   37817, 2003.5370,   376.54,   375.77,     376.41,   375.66,     376.54,   375.77
+2003, 08,   37848, 2003.6219,   374.42,   375.88,     374.36,   375.86,     374.42,   375.88
+2003, 09,   37879, 2003.7068,   372.92,   376.25,     372.69,   376.04,     372.92,   376.25
+2003, 10,   37909, 2003.7890,   372.94,   376.39,     372.76,   376.20,     372.94,   376.39
+2003, 11,   37940, 2003.8740,   374.29,   376.45,     374.22,   376.36,     374.29,   376.45
+2003, 12,   37970, 2003.9562,   375.63,   376.51,     375.64,   376.51,     375.63,   376.51
+2004, 01,   38001, 2004.0410,   376.73,   376.68,     376.71,   376.65,     376.73,   376.68
+2004, 02,   38032, 2004.1257,   377.31,   376.58,     377.52,   376.78,     377.31,   376.58
+2004, 03,   38061, 2004.2049,   378.33,   376.83,     378.42,   376.90,     378.33,   376.83
+2004, 04,   38092, 2004.2896,   380.44,   377.75,     379.73,   377.02,     380.44,   377.75
+2004, 05,   38122, 2004.3716,   380.56,   377.31,     380.38,   377.14,     380.56,   377.31
+2004, 06,   38153, 2004.4563,   379.49,   377.06,     379.67,   377.25,     379.49,   377.06
+2004, 07,   38183, 2004.5383,   377.71,   376.96,     378.09,   377.38,     377.71,   376.96
+2004, 08,   38214, 2004.6230,   375.78,   377.27,     375.98,   377.51,     375.78,   377.27
+2004, 09,   38245, 2004.7077,   373.99,   377.35,     374.29,   377.66,     373.99,   377.35
+2004, 10,   38275, 2004.7896,   374.17,   377.63,     374.38,   377.83,     374.17,   377.63
+2004, 11,   38306, 2004.8743,   375.79,   377.96,     375.87,   378.01,     375.79,   377.96
+2004, 12,   38336, 2004.9563,   377.39,   378.28,     377.33,   378.20,     377.39,   378.28
+2005, 01,   38367, 2005.0411,   378.29,   378.24,     378.47,   378.40,     378.29,   378.24
+2005, 02,   38398, 2005.1260,   379.56,   378.82,     379.36,   378.62,     379.56,   378.82
+2005, 03,   38426, 2005.2027,   380.06,   378.58,     380.31,   378.82,     380.06,   378.58
+2005, 04,   38457, 2005.2877,   382.02,   379.34,     381.73,   379.04,     382.02,   379.34
+2005, 05,   38487, 2005.3699,   382.21,   378.95,     382.51,   379.25,     382.21,   378.95
+2005, 06,   38518, 2005.4548,   382.05,   379.58,     381.92,   379.48,     382.05,   379.58
+2005, 07,   38548, 2005.5370,   380.63,   379.85,     380.44,   379.69,     380.63,   379.85
+2005, 08,   38579, 2005.6219,   378.64,   380.11,     378.39,   379.90,     378.64,   380.11
+2005, 09,   38610, 2005.7068,   376.38,   379.74,     376.74,   380.11,     376.38,   379.74
+2005, 10,   38640, 2005.7890,   376.77,   380.24,     376.85,   380.31,     376.77,   380.24
+2005, 11,   38671, 2005.8740,   378.27,   380.45,     378.36,   380.51,     378.27,   380.45
+2005, 12,   38701, 2005.9562,   379.93,   380.82,     379.83,   380.70,     379.93,   380.82
+2006, 01,   38732, 2006.0411,   381.33,   381.28,     380.94,   380.88,     381.33,   381.28
+2006, 02,   38763, 2006.1260,   381.98,   381.25,     381.80,   381.05,     381.98,   381.25
+2006, 03,   38791, 2006.2027,   382.53,   381.04,     382.70,   381.20,     382.53,   381.04
+2006, 04,   38822, 2006.2877,   384.33,   381.65,     384.06,   381.36,     384.33,   381.65
+2006, 05,   38852, 2006.3699,   384.89,   381.62,     384.77,   381.50,     384.89,   381.62
+2006, 06,   38883, 2006.4548,   383.99,   381.52,     384.10,   381.65,     383.99,   381.52
+2006, 07,   38913, 2006.5370,   382.25,   381.46,     382.54,   381.79,     382.25,   381.46
+2006, 08,   38944, 2006.6219,   380.44,   381.92,     380.43,   381.94,     380.44,   381.92
+2006, 09,   38975, 2006.7068,   378.77,   382.13,     378.71,   382.09,     378.77,   382.13
+2006, 10,   39005, 2006.7890,   379.03,   382.51,     378.76,   382.24,     379.03,   382.51
+2006, 11,   39036, 2006.8740,   380.11,   382.30,     380.23,   382.39,     380.11,   382.30
+2006, 12,   39066, 2006.9562,   381.63,   382.52,     381.66,   382.53,     381.63,   382.52
+2007, 01,   39097, 2007.0411,   382.55,   382.50,     382.75,   382.68,     382.55,   382.50
+2007, 02,   39128, 2007.1260,   383.68,   382.94,     383.59,   382.84,     383.68,   382.94
+2007, 03,   39156, 2007.2027,   384.31,   382.82,     384.49,   382.98,     384.31,   382.82
+2007, 04,   39187, 2007.2877,   386.20,   383.51,     385.85,   383.14,     386.20,   383.51
+2007, 05,   39217, 2007.3699,   386.38,   383.10,     386.58,   383.30,     386.38,   383.10
+2007, 06,   39248, 2007.4548,   385.84,   383.36,     385.92,   383.46,     385.84,   383.36
+2007, 07,   39278, 2007.5370,   384.42,   383.63,     384.37,   383.62,     384.42,   383.63
+2007, 08,   39309, 2007.6219,   381.81,   383.30,     382.26,   383.78,     381.81,   383.30
+2007, 09,   39340, 2007.7068,   380.83,   384.20,     380.56,   383.95,     380.83,   384.20
+2007, 10,   39370, 2007.7890,   380.83,   384.33,     380.62,   384.10,     380.83,   384.33
+2007, 11,   39401, 2007.8740,   382.32,   384.51,     382.09,   384.26,     382.32,   384.51
+2007, 12,   39431, 2007.9562,   383.58,   384.48,     383.53,   384.41,     383.58,   384.48
+2008, 01,   39462, 2008.0410,   385.04,   384.99,     384.62,   384.55,     385.04,   384.99
+2008, 02,   39493, 2008.1257,   385.81,   385.07,     385.45,   384.70,     385.81,   385.07
+2008, 03,   39522, 2008.2049,   385.80,   384.28,     386.38,   384.84,     385.80,   384.28
+2008, 04,   39553, 2008.2896,   386.74,   384.01,     387.73,   384.99,     386.74,   384.01
+2008, 05,   39583, 2008.3716,   388.49,   385.20,     388.43,   385.15,     388.49,   385.20
+2008, 06,   39614, 2008.4563,   388.02,   385.56,     387.76,   385.32,     388.02,   385.56
+2008, 07,   39644, 2008.5383,   386.22,   385.47,     386.20,   385.48,     386.22,   385.47
+2008, 08,   39675, 2008.6230,   384.05,   385.57,     384.10,   385.65,     384.05,   385.57
+2008, 09,   39706, 2008.7077,   383.05,   386.45,     382.41,   385.82,     383.05,   386.45
+2008, 10,   39736, 2008.7896,   382.75,   386.25,     382.49,   385.98,     382.75,   386.25
+2008, 11,   39767, 2008.8743,   383.98,   386.17,     383.97,   386.14,     383.98,   386.17
+2008, 12,   39797, 2008.9563,   385.08,   385.98,     385.41,   386.29,     385.08,   385.98
+2009, 01,   39828, 2009.0411,   386.63,   386.57,     386.51,   386.44,     386.63,   386.57
+2009, 02,   39859, 2009.1260,   387.10,   386.36,     387.35,   386.60,     387.10,   386.36
+2009, 03,   39887, 2009.2027,   388.50,   387.00,     388.26,   386.75,     388.50,   387.00
+2009, 04,   39918, 2009.2877,   389.54,   386.84,     389.64,   386.91,     389.54,   386.84
+2009, 05,   39948, 2009.3699,   390.15,   386.85,     390.38,   387.08,     390.15,   386.85
+2009, 06,   39979, 2009.4548,   389.60,   387.10,     389.74,   387.27,     389.60,   387.10
+2009, 07,   40009, 2009.5370,   388.05,   387.26,     388.21,   387.45,     388.05,   387.26
+2009, 08,   40040, 2009.6219,   386.07,   387.56,     386.13,   387.66,     386.07,   387.56
+2009, 09,   40071, 2009.7068,   384.64,   388.03,     384.46,   387.87,     384.64,   388.03
+2009, 10,   40101, 2009.7890,   384.32,   387.84,     384.58,   388.08,     384.32,   387.84
+2009, 11,   40132, 2009.8740,   386.05,   388.25,     386.13,   388.31,     386.05,   388.25
+2009, 12,   40162, 2009.9562,   387.49,   388.39,     387.65,   388.53,     387.49,   388.39
+2010, 01,   40193, 2010.0411,   388.55,   388.50,     388.83,   388.76,     388.55,   388.50
+2010, 02,   40224, 2010.1260,   390.08,   389.33,     389.75,   388.99,     390.08,   389.33
+2010, 03,   40252, 2010.2027,   391.02,   389.52,     390.71,   389.19,     391.02,   389.52
+2010, 04,   40283, 2010.2877,   392.39,   389.68,     392.13,   389.40,     392.39,   389.68
+2010, 05,   40313, 2010.3699,   393.24,   389.93,     392.90,   389.59,     393.24,   389.93
+2010, 06,   40344, 2010.4548,   392.26,   389.75,     392.26,   389.78,     392.26,   389.75
+2010, 07,   40374, 2010.5370,   390.35,   389.55,     390.71,   389.95,     390.35,   389.55
+2010, 08,   40405, 2010.6219,   388.53,   390.03,     388.60,   390.13,     388.53,   390.03
+2010, 09,   40436, 2010.7068,   386.85,   390.25,     386.87,   390.30,     386.85,   390.25
+2010, 10,   40466, 2010.7890,   387.18,   390.71,     386.94,   390.45,     387.18,   390.71
+2010, 11,   40497, 2010.8740,   388.69,   390.90,     388.42,   390.60,     388.69,   390.90
+2010, 12,   40527, 2010.9562,   389.83,   390.74,     389.86,   390.74,     389.83,   390.74
+2011, 01,   40558, 2011.0411,   391.33,   391.28,     390.94,   390.88,     391.33,   391.28
+2011, 02,   40589, 2011.1260,   391.96,   391.21,     391.77,   391.01,     391.96,   391.21
+2011, 03,   40617, 2011.2027,   392.49,   390.98,     392.65,   391.13,     392.49,   390.98
+2011, 04,   40648, 2011.2877,   393.41,   390.69,     394.01,   391.27,     393.41,   390.69
+2011, 05,   40678, 2011.3699,   394.33,   391.01,     394.73,   391.41,     394.33,   391.01
+2011, 06,   40709, 2011.4548,   393.74,   391.23,     394.06,   391.57,     393.74,   391.23
+2011, 07,   40739, 2011.5370,   392.64,   391.85,     392.50,   391.74,     392.64,   391.85
+2011, 08,   40770, 2011.6219,   390.25,   391.75,     390.38,   391.92,     390.25,   391.75
+2011, 09,   40801, 2011.7068,   389.05,   392.46,     388.67,   392.10,     389.05,   392.46
+2011, 10,   40831, 2011.7890,   388.98,   392.52,     388.76,   392.28,     388.98,   392.52
+2011, 11,   40862, 2011.8740,   390.30,   392.51,     390.27,   392.47,     390.30,   392.51
+2011, 12,   40892, 2011.9562,   391.86,   392.77,     391.76,   392.65,     391.86,   392.77
+2012, 01,   40923, 2012.0410,   393.13,   393.08,     392.90,   392.83,     393.13,   393.08
+2012, 02,   40954, 2012.1257,   393.42,   392.67,     393.78,   393.03,     393.42,   392.67
+2012, 03,   40983, 2012.2049,   394.43,   392.89,     394.77,   393.21,     394.43,   392.89
+2012, 04,   41014, 2012.2896,   396.51,   393.75,     396.19,   393.41,     396.51,   393.75
+2012, 05,   41044, 2012.3716,   396.96,   393.63,     396.94,   393.62,     396.96,   393.63
+2012, 06,   41075, 2012.4563,   395.97,   393.48,     396.31,   393.84,     395.97,   393.48
+2012, 07,   41105, 2012.5383,   394.60,   393.84,     394.79,   394.06,     394.60,   393.84
+2012, 08,   41136, 2012.6230,   392.61,   394.14,     392.72,   394.30,     392.61,   394.14
+2012, 09,   41167, 2012.7077,   391.20,   394.63,     391.09,   394.54,     391.20,   394.63
+2012, 10,   41197, 2012.7896,   391.09,   394.63,     391.25,   394.77,     391.09,   394.63
+2012, 11,   41228, 2012.8743,   393.03,   395.24,     392.83,   395.02,     393.03,   395.24
+2012, 12,   41258, 2012.9563,   394.42,   395.32,     394.36,   395.25,     394.42,   395.32
+2013, 01,   41289, 2013.0411,   395.69,   395.64,     395.55,   395.48,     395.69,   395.64
+2013, 02,   41320, 2013.1260,   396.94,   396.19,     396.47,   395.71,     396.94,   396.19
+2013, 03,   41348, 2013.2027,   397.35,   395.84,     397.44,   395.91,     397.35,   395.84
+2013, 04,   41379, 2013.2877,   398.44,   395.71,     398.88,   396.12,     398.44,   395.71
+2013, 05,   41409, 2013.3699,   400.06,   396.72,     399.66,   396.33,     400.06,   396.72
+2013, 06,   41440, 2013.4548,   398.95,   396.43,     399.03,   396.53,     398.95,   396.43
+2013, 07,   41470, 2013.5370,   397.45,   396.66,     397.48,   396.72,     397.45,   396.66
+2013, 08,   41501, 2013.6219,   395.49,   397.00,     395.37,   396.91,     395.49,   397.00
+2013, 09,   41532, 2013.7068,   393.48,   396.91,     393.65,   397.10,     393.48,   396.91
+2013, 10,   41562, 2013.7890,   393.77,   397.33,     393.74,   397.28,     393.77,   397.33
+2013, 11,   41593, 2013.8740,   395.27,   397.50,     395.26,   397.46,     395.27,   397.50
+2013, 12,   41623, 2013.9562,   396.90,   397.81,     396.74,   397.64,     396.90,   397.81
+2014, 01,   41654, 2014.0411,   398.01,   397.96,     397.87,   397.81,     398.01,   397.96
+2014, 02,   41685, 2014.1260,   398.18,   397.43,     398.74,   397.98,     398.18,   397.43
+2014, 03,   41713, 2014.2027,   399.56,   398.04,     399.67,   398.13,     399.56,   398.04
+2014, 04,   41744, 2014.2877,   401.44,   398.69,     401.06,   398.30,     401.44,   398.69
+2014, 05,   41774, 2014.3699,   401.99,   398.64,     401.80,   398.46,     401.99,   398.64
+2014, 06,   41805, 2014.4548,   401.41,   398.88,     401.13,   398.62,     401.41,   398.88
+2014, 07,   41835, 2014.5370,   399.17,   398.37,     399.54,   398.77,     399.17,   398.37
+2014, 08,   41866, 2014.6219,   397.30,   398.81,     397.38,   398.93,     397.30,   398.81
+2014, 09,   41897, 2014.7068,   395.49,   398.93,     395.64,   399.10,     395.49,   398.93
+2014, 10,   41927, 2014.7890,   395.74,   399.30,     395.70,   399.26,     395.74,   399.30
+2014, 11,   41958, 2014.8740,   397.32,   399.55,     397.21,   399.43,     397.32,   399.55
+2014, 12,   41988, 2014.9562,   398.89,   399.80,     398.69,   399.59,     398.89,   399.80
+2015, 01,   42019, 2015.0411,   399.94,   399.89,     399.83,   399.76,     399.94,   399.89
+2015, 02,   42050, 2015.1260,   400.39,   399.64,     400.71,   399.94,     400.39,   399.64
+2015, 03,   42078, 2015.2027,   401.60,   400.07,     401.65,   400.11,     401.60,   400.07
+2015, 04,   42109, 2015.2877,   403.53,   400.77,     403.07,   400.30,     403.53,   400.77
+2015, 05,   42139, 2015.3699,   404.04,   400.68,     403.85,   400.50,     404.04,   400.68
+2015, 06,   42170, 2015.4548,   402.81,   400.27,     403.23,   400.72,     402.81,   400.27
+2015, 07,   42200, 2015.5370,   401.54,   400.73,     401.72,   400.95,     401.54,   400.73
+2015, 08,   42231, 2015.6219,   398.93,   400.44,     399.66,   401.21,     398.93,   400.44
+2015, 09,   42262, 2015.7068,   397.43,   400.88,     398.03,   401.50,     397.43,   400.88
+2015, 10,   42292, 2015.7890,   398.21,   401.79,     398.23,   401.79,     398.21,   401.79
+2015, 11,   42323, 2015.8740,   400.17,   402.41,     399.89,   402.11,     400.17,   402.41
+2015, 12,   42353, 2015.9562,   401.82,   402.74,     401.52,   402.42,     401.82,   402.74
+2016, 01,   42384, 2016.0410,   402.58,   402.53,     402.80,   402.73,     402.58,   402.53
+2016, 02,   42415, 2016.1257,   404.09,   403.33,     403.81,   403.04,     404.09,   403.33
+2016, 03,   42444, 2016.2049,   404.79,   403.23,     404.89,   403.32,     404.79,   403.23
+2016, 04,   42475, 2016.2896,   407.50,   404.71,     406.40,   403.60,     407.50,   404.71
+2016, 05,   42505, 2016.3716,   407.59,   404.22,     407.21,   403.85,     407.59,   404.22
+2016, 06,   42536, 2016.4563,   406.94,   404.42,     406.59,   404.09,     406.94,   404.42
+2016, 07,   42566, 2016.5383,   404.43,   403.66,     405.05,   404.31,     404.43,   403.66
+2016, 08,   42597, 2016.6230,   402.17,   403.72,     402.95,   404.54,     402.17,   403.72
+2016, 09,   42628, 2016.7077,   400.94,   404.42,     401.26,   404.76,     400.94,   404.42
+2016, 10,   42658, 2016.7896,   401.43,   405.01,     401.40,   404.97,     401.43,   405.01
+2016, 11,   42689, 2016.8743,   403.57,   405.81,     402.96,   405.18,     403.57,   405.81
+2016, 12,   42719, 2016.9563,   404.48,   405.40,     404.47,   405.37,     404.48,   405.40
+2017, 01,   42750, 2017.0411,   406.00,   405.95,     405.63,   405.56,     406.00,   405.95
+2017, 02,   42781, 2017.1260,   406.57,   405.81,     406.52,   405.74,     406.57,   405.81
+2017, 03,   42809, 2017.2027,   406.99,   405.45,     407.45,   405.90,     406.99,   405.45
+2017, 04,   42840, 2017.2877,   408.88,   406.11,     408.86,   406.07,     408.88,   406.11
+2017, 05,   42870, 2017.3699,   409.84,   406.46,     409.60,   406.23,     409.84,   406.46
+2017, 06,   42901, 2017.4548,   409.05,   406.50,     408.92,   406.39,     409.05,   406.50
+2017, 07,   42931, 2017.5370,   407.13,   406.32,     407.31,   406.54,     407.13,   406.32
+2017, 08,   42962, 2017.6219,   405.17,   406.70,     405.13,   406.70,     405.17,   406.70
+2017, 09,   42993, 2017.7068,   403.20,   406.67,     403.36,   406.85,     403.20,   406.67
+2017, 10,   43023, 2017.7890,   403.57,   407.17,     403.42,   407.00,     403.57,   407.17
+2017, 11,   43054, 2017.8740,   405.10,   407.36,     404.92,   407.15,     405.10,   407.36
+2017, 12,   43084, 2017.9562,   406.68,   407.61,     406.40,   407.30,     406.68,   407.61
+2018, 01,   43115, 2018.0411,   407.98,   407.93,     407.52,   407.45,     407.98,   407.93
+2018, 02,   43146, 2018.1260,   408.28,   407.51,     408.38,   407.61,     408.28,   407.51
+2018, 03,   43174, 2018.2027,   409.19,   407.65,     409.32,   407.76,     409.19,   407.65
+2018, 04,   43205, 2018.2877,   410.24,   407.46,     410.74,   407.94,     410.24,   407.46
+2018, 05,   43235, 2018.3699,   411.23,   407.85,     411.52,   408.13,     411.23,   407.85
+2018, 06,   43266, 2018.4548,   410.81,   408.25,     410.90,   408.36,     410.81,   408.25
+2018, 07,   43296, 2018.5370,   408.83,   408.02,     409.36,   408.59,     408.83,   408.02
+2018, 08,   43327, 2018.6219,   407.02,   408.56,     407.28,   408.85,     407.02,   408.56
+2018, 09,   43358, 2018.7068,   405.52,   409.01,     405.62,   409.12,     405.52,   409.01
+2018, 10,   43388, 2018.7890,   405.93,   409.54,     405.79,   409.39,     405.93,   409.54
+2018, 11,   43419, 2018.8740,   408.05,   410.31,     407.43,   409.66,     408.05,   410.31
+2018, 12,   43449, 2018.9562,   409.16,   410.09,     409.02,   409.92,     409.16,   410.09
+2019, 01,   43480, 2019.0411,   410.85,   410.80,     410.25,   410.18,     410.85,   410.80
+2019, 02,   43511, 2019.1260,   411.59,   410.83,     411.20,   410.43,     411.59,   410.83
+2019, 03,   43539, 2019.2027,   411.93,   410.39,     412.20,   410.64,     411.93,   410.39
+2019, 04,   43570, 2019.2877,   413.46,   410.68,     413.67,   410.86,     413.46,   410.68
+2019, 05,   43600, 2019.3699,   414.76,   411.36,     414.48,   411.08,     414.76,   411.36
+2019, 06,   43631, 2019.4548,   413.89,   411.32,     413.85,   411.30,     413.89,   411.32
+2019, 07,   43661, 2019.5370,   411.78,   410.97,     412.29,   411.51,     411.78,   410.97
+2019, 08,   43692, 2019.6219,   410.01,   411.55,     410.16,   411.74,     410.01,   411.55
+2019, 09,   43723, 2019.7068,   408.48,   411.98,     408.45,   411.96,     408.48,   411.98
+2019, 10,   43753, 2019.7890,   408.37,   411.99,     408.57,   412.18,     408.37,   411.99
+2019, 11,   43784, 2019.8740,   410.22,   412.49,     410.16,   412.40,     410.22,   412.49
+2019, 12,   43814, 2019.9562,   411.78,   412.71,     411.70,   412.61,     411.78,   412.71
+2020, 01,   43845, 2020.0410,   413.38,   413.32,     412.89,   412.83,     413.38,   413.32
+2020, 02,   43876, 2020.1257,   414.03,   413.26,     413.81,   413.03,     414.03,   413.26
+2020, 03,   43905, 2020.2049,   414.44,   412.87,     414.82,   413.23,     414.44,   412.87
+2020, 04,   43936, 2020.2896,   416.11,   413.29,     416.27,   413.43,     416.11,   413.29
+2020, 05,   43966, 2020.3716,   417.10,   413.69,     417.03,   413.63,     417.10,   413.69
+2020, 06,   43997, 2020.4563,   416.23,   413.68,     416.36,   413.83,     416.23,   413.68
+2020, 07,   44027, 2020.5383,   414.47,   413.68,     414.78,   414.03,     414.47,   413.68
+2020, 08,   44058, 2020.6230,   412.53,   414.10,     412.63,   414.23,     412.53,   414.10
+2020, 09,   44089, 2020.7077,   411.19,   414.70,     410.90,   414.44,     411.19,   414.70
+2020, 10,   44119, 2020.7896,   411.15,   414.78,     411.02,   414.63,     411.15,   414.78
+2020, 11,   44150, 2020.8743,   412.88,   415.15,     412.58,   414.82,     412.88,   415.15
+2020, 12,   44180, 2020.9563,   413.89,   414.82,     414.09,   415.00,     413.89,   414.82
+2021, 01,   44211, 2021.0411,   415.17,   415.11,     415.24,   415.17,     415.17,   415.11
+2021, 02,   44242, 2021.1260,   416.47,   415.70,     416.13,   415.35,     416.47,   415.70
+2021, 03,   44270, 2021.2027,   417.14,   415.59,     417.06,   415.50,     417.14,   415.59
+2021, 04,   44301, 2021.2877,   418.24,   415.44,     418.48,   415.66,     418.24,   415.44
+2021, 05,   44331, 2021.3699,   418.92,   415.50,     419.23,   415.81,     418.92,   415.50
+2021, 06,   44362, 2021.4548,   418.73,   416.14,     -99.99,   -99.99,     418.73,   416.14
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+2021, 09,   44454, 2021.7068,   -99.99,   -99.99,     -99.99,   -99.99,     -99.99,   -99.99
+2021, 10,   44484, 2021.7890,   -99.99,   -99.99,     -99.99,   -99.99,     -99.99,   -99.99
+2021, 11,   44515, 2021.8740,   -99.99,   -99.99,     -99.99,   -99.99,     -99.99,   -99.99
+2021, 12,   44545, 2021.9562,   -99.99,   -99.99,     -99.99,   -99.99,     -99.99,   -99.99