diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb
index a53068996dd3803166dbf2926851822ea279422e..e2aee40c3eb403a0423f95eee4ad8903f7451ec8 100644
--- a/module3/exo3/exercice.ipynb
+++ b/module3/exo3/exercice.ipynb
@@ -28,6 +28,8 @@
     "import os\n",
     "import urllib.request\n",
     "from datetime import date\n",
+    "import time\n",
+    "import numpy as np\n",
     "\n",
     "today = date.today()"
    ]
@@ -54,13 +56,23 @@
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "file downloaded on Wed Apr  8 12:59:10 2020\n"
+     ]
+    }
+   ],
    "source": [
     "data_file =\"monthly_in_situ_co2_mlo.csv\"\n",
     "\n",
     "if not os.path.exists(data_file):\n",
     "    urllib.request.urlretrieve(data_url, data_file)\n",
-    "    print('fichier téléchargé le ',today)"
+    "modtime=os.path.getmtime(data_file)\n",
+    "modtime=time.ctime(modtime)\n",
+    "print('file downloaded on',modtime)"
    ]
   },
   {
@@ -3471,2257 +3483,333 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "#data=newh_data[newh_data['seasonally adjusted filled [ppm]']>0]\n",
+    "data=newh_data.drop(newh_data[newh_data['seasonally adjusted filled [ppm]']<0].index)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data['period'] = [pd.Period(freq='M',year=year,month=month) for (year,month) in zip(data['Yr'], data['Mn'])]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data.set_index('period',inplace=True)\n",
+    "periods = data.index\n",
+    "\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": "markdown",
+   "metadata": {},
+   "source": [
+    "Il n'y a aucune semaine manquante"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hideOutput": false
+   },
+   "source": [
+    "Regardons les données :"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Données superposées"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa4e72794a8>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data['CO2 filled [ppm]'].plot(legend=True, title='Atmospheric CO2 data',figsize=(10,8))\n",
+    "data['seasonally adjusted filled [ppm]'].plot(legend=True)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "L'évolution du CO2 dans l'atmosphère suit une oscillation périodique, qu'on supperpose avec une évolution systématique plus lente"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Séparation des deux phénomènes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Evolution systématique"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa4e502b160>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data['seasonally adjusted filled [ppm]'].plot(legend=True, title='Atmospheric CO2 data',figsize=(10,8))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On va essayer de faire une régression polynomiale sur ces données."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "743\n"
+      "           4            3            2\n",
+      "3.674e-16 x - 4.72e-11 x + 2.33e-06 x - 0.04813 x + 663.9\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fa4e0fe6e10>]"
+      ]
+     },
+     "execution_count": 16,
+     "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": [
-    "#data=newh_data[newh_data['seasonally adjusted filled [ppm]']>0]\n",
-    "data=newh_data.drop(newh_data[newh_data['seasonally adjusted filled [ppm]']<0].index)\n",
-    "print(len(data))"
+    "x=data['Date Excel'].values\n",
+    "y=data['seasonally adjusted filled [ppm]'].values\n",
+    "p4 = np.poly1d(np.polyfit(x, y, 4))\n",
+    "print(p4)\n",
+    "#xp = np.linspace(0, 7, 100)\n",
+    "plt.plot(x,y)\n",
+    "plt.plot(x, p4(x), c='r')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On a commencé par utilisé le format excel de la date pour avoir des données de type float pour pouvoir travailler avec numpy. En effet : Excel stocke les dates sous la forme de numéros de série séquentiels afin qu’elles soient utilisables dans des calculs. Le 1er janvier 1900 porte le numéro de série 1, et le 1er janvier 2008 le numéro de série 39448 car il se situe 39 447 jours après le 1er janvier 1900. Pour pouvoir afficher une date correcte, vous devez modifier le format de nombre (Format de cellule)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The model gives 430.40 ppm of atmospheric CO2 in June 2025\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>Yr</th>\n",
-       "      <th>Mn</th>\n",
-       "      <th>Date Excel</th>\n",
-       "      <th>Date</th>\n",
-       "      <th>CO2 [ppm]</th>\n",
-       "      <th>seasonally adjusted [ppm]</th>\n",
-       "      <th>fit [ppm]</th>\n",
-       "      <th>seasonally adjusted fit [ppm]</th>\n",
-       "      <th>CO2 filled [ppm]</th>\n",
-       "      <th>seasonally adjusted filled [ppm]</th>\n",
-       "      <th>period</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>3</td>\n",
-       "      <td>21259</td>\n",
-       "      <td>1958.2027</td>\n",
-       "      <td>315.70</td>\n",
-       "      <td>314.44</td>\n",
-       "      <td>316.19</td>\n",
-       "      <td>314.91</td>\n",
-       "      <td>315.70</td>\n",
-       "      <td>314.44</td>\n",
-       "      <td>1958-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>4</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>314.99</td>\n",
-       "      <td>317.45</td>\n",
-       "      <td>315.16</td>\n",
-       "      <td>1958-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>5</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",
-       "      <td>1958-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>6</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",
-       "      <td>1958-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>7</td>\n",
-       "      <td>21381</td>\n",
-       "      <td>1958.5370</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>315.19</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>315.22</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>315.19</td>\n",
-       "      <td>1958-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>8</td>\n",
-       "      <td>21412</td>\n",
-       "      <td>1958.6219</td>\n",
-       "      <td>314.93</td>\n",
-       "      <td>316.19</td>\n",
-       "      <td>314.00</td>\n",
-       "      <td>315.29</td>\n",
-       "      <td>314.93</td>\n",
-       "      <td>316.19</td>\n",
-       "      <td>1958-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>9</td>\n",
-       "      <td>21443</td>\n",
-       "      <td>1958.7068</td>\n",
-       "      <td>313.21</td>\n",
-       "      <td>316.08</td>\n",
-       "      <td>312.46</td>\n",
-       "      <td>315.35</td>\n",
-       "      <td>313.21</td>\n",
-       "      <td>316.08</td>\n",
-       "      <td>1958-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>10</td>\n",
-       "      <td>21473</td>\n",
-       "      <td>1958.7890</td>\n",
-       "      <td>-99.99</td>\n",
-       "      <td>-99.99</td>\n",
-       "      <td>312.44</td>\n",
-       "      <td>315.40</td>\n",
-       "      <td>312.44</td>\n",
-       "      <td>315.40</td>\n",
-       "      <td>1958-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>11</td>\n",
-       "      <td>21504</td>\n",
-       "      <td>1958.8740</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>315.20</td>\n",
-       "      <td>313.62</td>\n",
-       "      <td>315.46</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>315.20</td>\n",
-       "      <td>1958-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>12</td>\n",
-       "      <td>21534</td>\n",
-       "      <td>1958.9562</td>\n",
-       "      <td>314.67</td>\n",
-       "      <td>315.43</td>\n",
-       "      <td>314.77</td>\n",
-       "      <td>315.51</td>\n",
-       "      <td>314.67</td>\n",
-       "      <td>315.43</td>\n",
-       "      <td>1958-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>1</td>\n",
-       "      <td>21565</td>\n",
-       "      <td>1959.0411</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>315.54</td>\n",
-       "      <td>315.62</td>\n",
-       "      <td>315.57</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>315.54</td>\n",
-       "      <td>1959-01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>2</td>\n",
-       "      <td>21596</td>\n",
-       "      <td>1959.1260</td>\n",
-       "      <td>316.49</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>316.27</td>\n",
-       "      <td>315.63</td>\n",
-       "      <td>316.49</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>1959-02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>3</td>\n",
-       "      <td>21624</td>\n",
-       "      <td>1959.2027</td>\n",
-       "      <td>316.65</td>\n",
-       "      <td>315.38</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>315.69</td>\n",
-       "      <td>316.65</td>\n",
-       "      <td>315.38</td>\n",
-       "      <td>1959-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>4</td>\n",
-       "      <td>21655</td>\n",
-       "      <td>1959.2877</td>\n",
-       "      <td>317.72</td>\n",
-       "      <td>315.42</td>\n",
-       "      <td>318.09</td>\n",
-       "      <td>315.77</td>\n",
-       "      <td>317.72</td>\n",
-       "      <td>315.42</td>\n",
-       "      <td>1959-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>5</td>\n",
-       "      <td>21685</td>\n",
-       "      <td>1959.3699</td>\n",
-       "      <td>318.29</td>\n",
-       "      <td>315.49</td>\n",
-       "      <td>318.65</td>\n",
-       "      <td>315.85</td>\n",
-       "      <td>318.29</td>\n",
-       "      <td>315.49</td>\n",
-       "      <td>1959-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>6</td>\n",
-       "      <td>21716</td>\n",
-       "      <td>1959.4548</td>\n",
-       "      <td>318.15</td>\n",
-       "      <td>316.03</td>\n",
-       "      <td>318.04</td>\n",
-       "      <td>315.94</td>\n",
-       "      <td>318.15</td>\n",
-       "      <td>316.03</td>\n",
-       "      <td>1959-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>7</td>\n",
-       "      <td>21746</td>\n",
-       "      <td>1959.5370</td>\n",
-       "      <td>316.54</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>316.67</td>\n",
-       "      <td>316.03</td>\n",
-       "      <td>316.54</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>1959-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>8</td>\n",
-       "      <td>21777</td>\n",
-       "      <td>1959.6219</td>\n",
-       "      <td>314.80</td>\n",
-       "      <td>316.06</td>\n",
-       "      <td>314.83</td>\n",
-       "      <td>316.12</td>\n",
-       "      <td>314.80</td>\n",
-       "      <td>316.06</td>\n",
-       "      <td>1959-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>9</td>\n",
-       "      <td>21808</td>\n",
-       "      <td>1959.7068</td>\n",
-       "      <td>313.84</td>\n",
-       "      <td>316.72</td>\n",
-       "      <td>313.32</td>\n",
-       "      <td>316.22</td>\n",
-       "      <td>313.84</td>\n",
-       "      <td>316.72</td>\n",
-       "      <td>1959-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>21</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>10</td>\n",
-       "      <td>21838</td>\n",
-       "      <td>1959.7890</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>316.32</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>316.30</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>316.32</td>\n",
-       "      <td>1959-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>11</td>\n",
-       "      <td>21869</td>\n",
-       "      <td>1959.8740</td>\n",
-       "      <td>314.81</td>\n",
-       "      <td>316.68</td>\n",
-       "      <td>314.54</td>\n",
-       "      <td>316.39</td>\n",
-       "      <td>314.81</td>\n",
-       "      <td>316.68</td>\n",
-       "      <td>1959-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>12</td>\n",
-       "      <td>21899</td>\n",
-       "      <td>1959.9562</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>315.72</td>\n",
-       "      <td>316.47</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>1959-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>1</td>\n",
-       "      <td>21930</td>\n",
-       "      <td>1960.0410</td>\n",
-       "      <td>316.43</td>\n",
-       "      <td>316.39</td>\n",
-       "      <td>316.61</td>\n",
-       "      <td>316.56</td>\n",
-       "      <td>316.43</td>\n",
-       "      <td>316.39</td>\n",
-       "      <td>1960-01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>2</td>\n",
-       "      <td>21961</td>\n",
-       "      <td>1960.1257</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>317.27</td>\n",
-       "      <td>316.64</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>1960-02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>26</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>3</td>\n",
-       "      <td>21990</td>\n",
-       "      <td>1960.2049</td>\n",
-       "      <td>317.58</td>\n",
-       "      <td>316.28</td>\n",
-       "      <td>318.03</td>\n",
-       "      <td>316.71</td>\n",
-       "      <td>317.58</td>\n",
-       "      <td>316.28</td>\n",
-       "      <td>1960-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>4</td>\n",
-       "      <td>22021</td>\n",
-       "      <td>1960.2896</td>\n",
-       "      <td>319.03</td>\n",
-       "      <td>316.70</td>\n",
-       "      <td>319.14</td>\n",
-       "      <td>316.79</td>\n",
-       "      <td>319.03</td>\n",
-       "      <td>316.70</td>\n",
-       "      <td>1960-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>5</td>\n",
-       "      <td>22051</td>\n",
-       "      <td>1960.3716</td>\n",
-       "      <td>320.04</td>\n",
-       "      <td>317.22</td>\n",
-       "      <td>319.67</td>\n",
-       "      <td>316.86</td>\n",
-       "      <td>320.04</td>\n",
-       "      <td>317.22</td>\n",
-       "      <td>1960-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>6</td>\n",
-       "      <td>22082</td>\n",
-       "      <td>1960.4563</td>\n",
-       "      <td>319.59</td>\n",
-       "      <td>317.48</td>\n",
-       "      <td>319.01</td>\n",
-       "      <td>316.93</td>\n",
-       "      <td>319.59</td>\n",
-       "      <td>317.48</td>\n",
-       "      <td>1960-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>30</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>7</td>\n",
-       "      <td>22112</td>\n",
-       "      <td>1960.5383</td>\n",
-       "      <td>318.18</td>\n",
-       "      <td>317.53</td>\n",
-       "      <td>317.60</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>318.18</td>\n",
-       "      <td>317.53</td>\n",
-       "      <td>1960-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>31</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>8</td>\n",
-       "      <td>22143</td>\n",
-       "      <td>1960.6230</td>\n",
-       "      <td>315.90</td>\n",
-       "      <td>317.20</td>\n",
-       "      <td>315.69</td>\n",
-       "      <td>317.01</td>\n",
-       "      <td>315.90</td>\n",
-       "      <td>317.20</td>\n",
-       "      <td>1960-08</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",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>715</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>8</td>\n",
-       "      <td>42962</td>\n",
-       "      <td>2017.6219</td>\n",
-       "      <td>405.24</td>\n",
-       "      <td>406.77</td>\n",
-       "      <td>405.20</td>\n",
-       "      <td>406.76</td>\n",
-       "      <td>405.24</td>\n",
-       "      <td>406.77</td>\n",
-       "      <td>2017-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>716</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>9</td>\n",
-       "      <td>42993</td>\n",
-       "      <td>2017.7068</td>\n",
-       "      <td>403.27</td>\n",
-       "      <td>406.76</td>\n",
-       "      <td>403.41</td>\n",
-       "      <td>406.92</td>\n",
-       "      <td>403.27</td>\n",
-       "      <td>406.76</td>\n",
-       "      <td>2017-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>717</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>10</td>\n",
-       "      <td>43023</td>\n",
-       "      <td>2017.7890</td>\n",
-       "      <td>403.64</td>\n",
-       "      <td>407.25</td>\n",
-       "      <td>403.47</td>\n",
-       "      <td>407.07</td>\n",
-       "      <td>403.64</td>\n",
-       "      <td>407.25</td>\n",
-       "      <td>2017-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>718</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>11</td>\n",
-       "      <td>43054</td>\n",
-       "      <td>2017.8740</td>\n",
-       "      <td>405.17</td>\n",
-       "      <td>407.43</td>\n",
-       "      <td>404.98</td>\n",
-       "      <td>407.22</td>\n",
-       "      <td>405.17</td>\n",
-       "      <td>407.43</td>\n",
-       "      <td>2017-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>719</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>12</td>\n",
-       "      <td>43084</td>\n",
-       "      <td>2017.9562</td>\n",
-       "      <td>406.75</td>\n",
-       "      <td>407.68</td>\n",
-       "      <td>406.46</td>\n",
-       "      <td>407.37</td>\n",
-       "      <td>406.75</td>\n",
-       "      <td>407.68</td>\n",
-       "      <td>2017-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>720</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>1</td>\n",
-       "      <td>43115</td>\n",
-       "      <td>2018.0411</td>\n",
-       "      <td>408.05</td>\n",
-       "      <td>408.00</td>\n",
-       "      <td>407.58</td>\n",
-       "      <td>407.52</td>\n",
-       "      <td>408.05</td>\n",
-       "      <td>408.00</td>\n",
-       "      <td>2018-01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>721</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>2</td>\n",
-       "      <td>43146</td>\n",
-       "      <td>2018.1260</td>\n",
-       "      <td>408.34</td>\n",
-       "      <td>407.59</td>\n",
-       "      <td>408.44</td>\n",
-       "      <td>407.68</td>\n",
-       "      <td>408.34</td>\n",
-       "      <td>407.59</td>\n",
-       "      <td>2018-02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>722</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>3</td>\n",
-       "      <td>43174</td>\n",
-       "      <td>2018.2027</td>\n",
-       "      <td>409.25</td>\n",
-       "      <td>407.71</td>\n",
-       "      <td>409.39</td>\n",
-       "      <td>407.82</td>\n",
-       "      <td>409.25</td>\n",
-       "      <td>407.71</td>\n",
-       "      <td>2018-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>723</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>4</td>\n",
-       "      <td>43205</td>\n",
-       "      <td>2018.2877</td>\n",
-       "      <td>410.30</td>\n",
-       "      <td>407.51</td>\n",
-       "      <td>410.82</td>\n",
-       "      <td>408.00</td>\n",
-       "      <td>410.30</td>\n",
-       "      <td>407.51</td>\n",
-       "      <td>2018-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>724</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>5</td>\n",
-       "      <td>43235</td>\n",
-       "      <td>2018.3699</td>\n",
-       "      <td>411.30</td>\n",
-       "      <td>407.90</td>\n",
-       "      <td>411.60</td>\n",
-       "      <td>408.20</td>\n",
-       "      <td>411.30</td>\n",
-       "      <td>407.90</td>\n",
-       "      <td>2018-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>725</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>6</td>\n",
-       "      <td>43266</td>\n",
-       "      <td>2018.4548</td>\n",
-       "      <td>410.88</td>\n",
-       "      <td>408.30</td>\n",
-       "      <td>410.97</td>\n",
-       "      <td>408.42</td>\n",
-       "      <td>410.88</td>\n",
-       "      <td>408.30</td>\n",
-       "      <td>2018-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>726</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>7</td>\n",
-       "      <td>43296</td>\n",
-       "      <td>2018.5370</td>\n",
-       "      <td>408.90</td>\n",
-       "      <td>408.08</td>\n",
-       "      <td>409.43</td>\n",
-       "      <td>408.65</td>\n",
-       "      <td>408.90</td>\n",
-       "      <td>408.08</td>\n",
-       "      <td>2018-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>727</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>8</td>\n",
-       "      <td>43327</td>\n",
-       "      <td>2018.6219</td>\n",
-       "      <td>407.10</td>\n",
-       "      <td>408.63</td>\n",
-       "      <td>407.33</td>\n",
-       "      <td>408.91</td>\n",
-       "      <td>407.10</td>\n",
-       "      <td>408.63</td>\n",
-       "      <td>2018-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>728</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>9</td>\n",
-       "      <td>43358</td>\n",
-       "      <td>2018.7068</td>\n",
-       "      <td>405.59</td>\n",
-       "      <td>409.09</td>\n",
-       "      <td>405.66</td>\n",
-       "      <td>409.18</td>\n",
-       "      <td>405.59</td>\n",
-       "      <td>409.09</td>\n",
-       "      <td>2018-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>729</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>10</td>\n",
-       "      <td>43388</td>\n",
-       "      <td>2018.7890</td>\n",
-       "      <td>405.99</td>\n",
-       "      <td>409.62</td>\n",
-       "      <td>405.83</td>\n",
-       "      <td>409.44</td>\n",
-       "      <td>405.99</td>\n",
-       "      <td>409.62</td>\n",
-       "      <td>2018-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>730</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>11</td>\n",
-       "      <td>43419</td>\n",
-       "      <td>2018.8740</td>\n",
-       "      <td>408.12</td>\n",
-       "      <td>410.39</td>\n",
-       "      <td>407.47</td>\n",
-       "      <td>409.72</td>\n",
-       "      <td>408.12</td>\n",
-       "      <td>410.39</td>\n",
-       "      <td>2018-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>731</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>12</td>\n",
-       "      <td>43449</td>\n",
-       "      <td>2018.9562</td>\n",
-       "      <td>409.23</td>\n",
-       "      <td>410.16</td>\n",
-       "      <td>409.07</td>\n",
-       "      <td>409.97</td>\n",
-       "      <td>409.23</td>\n",
-       "      <td>410.16</td>\n",
-       "      <td>2018-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>732</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>1</td>\n",
-       "      <td>43480</td>\n",
-       "      <td>2019.0411</td>\n",
-       "      <td>410.92</td>\n",
-       "      <td>410.87</td>\n",
-       "      <td>410.29</td>\n",
-       "      <td>410.23</td>\n",
-       "      <td>410.92</td>\n",
-       "      <td>410.87</td>\n",
-       "      <td>2019-01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>733</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>2</td>\n",
-       "      <td>43511</td>\n",
-       "      <td>2019.1260</td>\n",
-       "      <td>411.66</td>\n",
-       "      <td>410.90</td>\n",
-       "      <td>411.24</td>\n",
-       "      <td>410.47</td>\n",
-       "      <td>411.66</td>\n",
-       "      <td>410.90</td>\n",
-       "      <td>2019-02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>734</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>3</td>\n",
-       "      <td>43539</td>\n",
-       "      <td>2019.2027</td>\n",
-       "      <td>412.00</td>\n",
-       "      <td>410.45</td>\n",
-       "      <td>412.25</td>\n",
-       "      <td>410.68</td>\n",
-       "      <td>412.00</td>\n",
-       "      <td>410.45</td>\n",
-       "      <td>2019-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>735</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>4</td>\n",
-       "      <td>43570</td>\n",
-       "      <td>2019.2877</td>\n",
-       "      <td>413.52</td>\n",
-       "      <td>410.72</td>\n",
-       "      <td>413.73</td>\n",
-       "      <td>410.91</td>\n",
-       "      <td>413.52</td>\n",
-       "      <td>410.72</td>\n",
-       "      <td>2019-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>736</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>5</td>\n",
-       "      <td>43600</td>\n",
-       "      <td>2019.3699</td>\n",
-       "      <td>414.83</td>\n",
-       "      <td>411.42</td>\n",
-       "      <td>414.54</td>\n",
-       "      <td>411.13</td>\n",
-       "      <td>414.83</td>\n",
-       "      <td>411.42</td>\n",
-       "      <td>2019-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>737</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>6</td>\n",
-       "      <td>43631</td>\n",
-       "      <td>2019.4548</td>\n",
-       "      <td>413.96</td>\n",
-       "      <td>411.38</td>\n",
-       "      <td>413.91</td>\n",
-       "      <td>411.35</td>\n",
-       "      <td>413.96</td>\n",
-       "      <td>411.38</td>\n",
-       "      <td>2019-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>738</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>7</td>\n",
-       "      <td>43661</td>\n",
-       "      <td>2019.5370</td>\n",
-       "      <td>411.85</td>\n",
-       "      <td>411.03</td>\n",
-       "      <td>412.36</td>\n",
-       "      <td>411.57</td>\n",
-       "      <td>411.85</td>\n",
-       "      <td>411.03</td>\n",
-       "      <td>2019-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>739</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>8</td>\n",
-       "      <td>43692</td>\n",
-       "      <td>2019.6219</td>\n",
-       "      <td>410.08</td>\n",
-       "      <td>411.62</td>\n",
-       "      <td>410.23</td>\n",
-       "      <td>411.81</td>\n",
-       "      <td>410.08</td>\n",
-       "      <td>411.62</td>\n",
-       "      <td>2019-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>740</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>9</td>\n",
-       "      <td>43723</td>\n",
-       "      <td>2019.7068</td>\n",
-       "      <td>408.55</td>\n",
-       "      <td>412.06</td>\n",
-       "      <td>408.52</td>\n",
-       "      <td>412.05</td>\n",
-       "      <td>408.55</td>\n",
-       "      <td>412.06</td>\n",
-       "      <td>2019-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>741</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>10</td>\n",
-       "      <td>43753</td>\n",
-       "      <td>2019.7890</td>\n",
-       "      <td>408.43</td>\n",
-       "      <td>412.07</td>\n",
-       "      <td>408.67</td>\n",
-       "      <td>412.29</td>\n",
-       "      <td>408.43</td>\n",
-       "      <td>412.07</td>\n",
-       "      <td>2019-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>742</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>11</td>\n",
-       "      <td>43784</td>\n",
-       "      <td>2019.8740</td>\n",
-       "      <td>410.28</td>\n",
-       "      <td>412.56</td>\n",
-       "      <td>410.29</td>\n",
-       "      <td>412.54</td>\n",
-       "      <td>410.28</td>\n",
-       "      <td>412.56</td>\n",
-       "      <td>2019-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>743</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>12</td>\n",
-       "      <td>43814</td>\n",
-       "      <td>2019.9562</td>\n",
-       "      <td>411.85</td>\n",
-       "      <td>412.78</td>\n",
-       "      <td>411.88</td>\n",
-       "      <td>412.79</td>\n",
-       "      <td>411.85</td>\n",
-       "      <td>412.78</td>\n",
-       "      <td>2019-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>744</th>\n",
-       "      <td>2020</td>\n",
-       "      <td>1</td>\n",
-       "      <td>43845</td>\n",
-       "      <td>2020.0410</td>\n",
-       "      <td>413.37</td>\n",
-       "      <td>413.33</td>\n",
-       "      <td>413.11</td>\n",
-       "      <td>413.05</td>\n",
-       "      <td>413.37</td>\n",
-       "      <td>413.33</td>\n",
-       "      <td>2020-01</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>743 rows × 11 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       Yr  Mn  Date Excel       Date  CO2 [ppm]  seasonally adjusted [ppm]  \\\n",
-       "2    1958   3       21259  1958.2027     315.70                     314.44   \n",
-       "3    1958   4       21290  1958.2877     317.45                     315.16   \n",
-       "4    1958   5       21320  1958.3699     317.51                     314.71   \n",
-       "5    1958   6       21351  1958.4548     -99.99                     -99.99   \n",
-       "6    1958   7       21381  1958.5370     315.86                     315.19   \n",
-       "7    1958   8       21412  1958.6219     314.93                     316.19   \n",
-       "8    1958   9       21443  1958.7068     313.21                     316.08   \n",
-       "9    1958  10       21473  1958.7890     -99.99                     -99.99   \n",
-       "10   1958  11       21504  1958.8740     313.33                     315.20   \n",
-       "11   1958  12       21534  1958.9562     314.67                     315.43   \n",
-       "12   1959   1       21565  1959.0411     315.58                     315.54   \n",
-       "13   1959   2       21596  1959.1260     316.49                     315.86   \n",
-       "14   1959   3       21624  1959.2027     316.65                     315.38   \n",
-       "15   1959   4       21655  1959.2877     317.72                     315.42   \n",
-       "16   1959   5       21685  1959.3699     318.29                     315.49   \n",
-       "17   1959   6       21716  1959.4548     318.15                     316.03   \n",
-       "18   1959   7       21746  1959.5370     316.54                     315.86   \n",
-       "19   1959   8       21777  1959.6219     314.80                     316.06   \n",
-       "20   1959   9       21808  1959.7068     313.84                     316.72   \n",
-       "21   1959  10       21838  1959.7890     313.33                     316.32   \n",
-       "22   1959  11       21869  1959.8740     314.81                     316.68   \n",
-       "23   1959  12       21899  1959.9562     315.58                     316.35   \n",
-       "24   1960   1       21930  1960.0410     316.43                     316.39   \n",
-       "25   1960   2       21961  1960.1257     316.98                     316.35   \n",
-       "26   1960   3       21990  1960.2049     317.58                     316.28   \n",
-       "27   1960   4       22021  1960.2896     319.03                     316.70   \n",
-       "28   1960   5       22051  1960.3716     320.04                     317.22   \n",
-       "29   1960   6       22082  1960.4563     319.59                     317.48   \n",
-       "30   1960   7       22112  1960.5383     318.18                     317.53   \n",
-       "31   1960   8       22143  1960.6230     315.90                     317.20   \n",
-       "..    ...  ..         ...        ...        ...                        ...   \n",
-       "715  2017   8       42962  2017.6219     405.24                     406.77   \n",
-       "716  2017   9       42993  2017.7068     403.27                     406.76   \n",
-       "717  2017  10       43023  2017.7890     403.64                     407.25   \n",
-       "718  2017  11       43054  2017.8740     405.17                     407.43   \n",
-       "719  2017  12       43084  2017.9562     406.75                     407.68   \n",
-       "720  2018   1       43115  2018.0411     408.05                     408.00   \n",
-       "721  2018   2       43146  2018.1260     408.34                     407.59   \n",
-       "722  2018   3       43174  2018.2027     409.25                     407.71   \n",
-       "723  2018   4       43205  2018.2877     410.30                     407.51   \n",
-       "724  2018   5       43235  2018.3699     411.30                     407.90   \n",
-       "725  2018   6       43266  2018.4548     410.88                     408.30   \n",
-       "726  2018   7       43296  2018.5370     408.90                     408.08   \n",
-       "727  2018   8       43327  2018.6219     407.10                     408.63   \n",
-       "728  2018   9       43358  2018.7068     405.59                     409.09   \n",
-       "729  2018  10       43388  2018.7890     405.99                     409.62   \n",
-       "730  2018  11       43419  2018.8740     408.12                     410.39   \n",
-       "731  2018  12       43449  2018.9562     409.23                     410.16   \n",
-       "732  2019   1       43480  2019.0411     410.92                     410.87   \n",
-       "733  2019   2       43511  2019.1260     411.66                     410.90   \n",
-       "734  2019   3       43539  2019.2027     412.00                     410.45   \n",
-       "735  2019   4       43570  2019.2877     413.52                     410.72   \n",
-       "736  2019   5       43600  2019.3699     414.83                     411.42   \n",
-       "737  2019   6       43631  2019.4548     413.96                     411.38   \n",
-       "738  2019   7       43661  2019.5370     411.85                     411.03   \n",
-       "739  2019   8       43692  2019.6219     410.08                     411.62   \n",
-       "740  2019   9       43723  2019.7068     408.55                     412.06   \n",
-       "741  2019  10       43753  2019.7890     408.43                     412.07   \n",
-       "742  2019  11       43784  2019.8740     410.28                     412.56   \n",
-       "743  2019  12       43814  2019.9562     411.85                     412.78   \n",
-       "744  2020   1       43845  2020.0410     413.37                     413.33   \n",
-       "\n",
-       "     fit [ppm]  seasonally adjusted fit [ppm]  CO2 filled [ppm]  \\\n",
-       "2       316.19                         314.91            315.70   \n",
-       "3       317.30                         314.99            317.45   \n",
-       "4       317.86                         315.06            317.51   \n",
-       "5       317.24                         315.14            317.24   \n",
-       "6       315.86                         315.22            315.86   \n",
-       "7       314.00                         315.29            314.93   \n",
-       "8       312.46                         315.35            313.21   \n",
-       "9       312.44                         315.40            312.44   \n",
-       "10      313.62                         315.46            313.33   \n",
-       "11      314.77                         315.51            314.67   \n",
-       "12      315.62                         315.57            315.58   \n",
-       "13      316.27                         315.63            316.49   \n",
-       "14      316.98                         315.69            316.65   \n",
-       "15      318.09                         315.77            317.72   \n",
-       "16      318.65                         315.85            318.29   \n",
-       "17      318.04                         315.94            318.15   \n",
-       "18      316.67                         316.03            316.54   \n",
-       "19      314.83                         316.12            314.80   \n",
-       "20      313.32                         316.22            313.84   \n",
-       "21      313.33                         316.30            313.33   \n",
-       "22      314.54                         316.39            314.81   \n",
-       "23      315.72                         316.47            315.58   \n",
-       "24      316.61                         316.56            316.43   \n",
-       "25      317.27                         316.64            316.98   \n",
-       "26      318.03                         316.71            317.58   \n",
-       "27      319.14                         316.79            319.03   \n",
-       "28      319.67                         316.86            320.04   \n",
-       "29      319.01                         316.93            319.59   \n",
-       "30      317.60                         316.98            318.18   \n",
-       "31      315.69                         317.01            315.90   \n",
-       "..         ...                            ...               ...   \n",
-       "715     405.20                         406.76            405.24   \n",
-       "716     403.41                         406.92            403.27   \n",
-       "717     403.47                         407.07            403.64   \n",
-       "718     404.98                         407.22            405.17   \n",
-       "719     406.46                         407.37            406.75   \n",
-       "720     407.58                         407.52            408.05   \n",
-       "721     408.44                         407.68            408.34   \n",
-       "722     409.39                         407.82            409.25   \n",
-       "723     410.82                         408.00            410.30   \n",
-       "724     411.60                         408.20            411.30   \n",
-       "725     410.97                         408.42            410.88   \n",
-       "726     409.43                         408.65            408.90   \n",
-       "727     407.33                         408.91            407.10   \n",
-       "728     405.66                         409.18            405.59   \n",
-       "729     405.83                         409.44            405.99   \n",
-       "730     407.47                         409.72            408.12   \n",
-       "731     409.07                         409.97            409.23   \n",
-       "732     410.29                         410.23            410.92   \n",
-       "733     411.24                         410.47            411.66   \n",
-       "734     412.25                         410.68            412.00   \n",
-       "735     413.73                         410.91            413.52   \n",
-       "736     414.54                         411.13            414.83   \n",
-       "737     413.91                         411.35            413.96   \n",
-       "738     412.36                         411.57            411.85   \n",
-       "739     410.23                         411.81            410.08   \n",
-       "740     408.52                         412.05            408.55   \n",
-       "741     408.67                         412.29            408.43   \n",
-       "742     410.29                         412.54            410.28   \n",
-       "743     411.88                         412.79            411.85   \n",
-       "744     413.11                         413.05            413.37   \n",
-       "\n",
-       "     seasonally adjusted filled [ppm]  period  \n",
-       "2                              314.44 1958-03  \n",
-       "3                              315.16 1958-04  \n",
-       "4                              314.71 1958-05  \n",
-       "5                              315.14 1958-06  \n",
-       "6                              315.19 1958-07  \n",
-       "7                              316.19 1958-08  \n",
-       "8                              316.08 1958-09  \n",
-       "9                              315.40 1958-10  \n",
-       "10                             315.20 1958-11  \n",
-       "11                             315.43 1958-12  \n",
-       "12                             315.54 1959-01  \n",
-       "13                             315.86 1959-02  \n",
-       "14                             315.38 1959-03  \n",
-       "15                             315.42 1959-04  \n",
-       "16                             315.49 1959-05  \n",
-       "17                             316.03 1959-06  \n",
-       "18                             315.86 1959-07  \n",
-       "19                             316.06 1959-08  \n",
-       "20                             316.72 1959-09  \n",
-       "21                             316.32 1959-10  \n",
-       "22                             316.68 1959-11  \n",
-       "23                             316.35 1959-12  \n",
-       "24                             316.39 1960-01  \n",
-       "25                             316.35 1960-02  \n",
-       "26                             316.28 1960-03  \n",
-       "27                             316.70 1960-04  \n",
-       "28                             317.22 1960-05  \n",
-       "29                             317.48 1960-06  \n",
-       "30                             317.53 1960-07  \n",
-       "31                             317.20 1960-08  \n",
-       "..                                ...     ...  \n",
-       "715                            406.77 2017-08  \n",
-       "716                            406.76 2017-09  \n",
-       "717                            407.25 2017-10  \n",
-       "718                            407.43 2017-11  \n",
-       "719                            407.68 2017-12  \n",
-       "720                            408.00 2018-01  \n",
-       "721                            407.59 2018-02  \n",
-       "722                            407.71 2018-03  \n",
-       "723                            407.51 2018-04  \n",
-       "724                            407.90 2018-05  \n",
-       "725                            408.30 2018-06  \n",
-       "726                            408.08 2018-07  \n",
-       "727                            408.63 2018-08  \n",
-       "728                            409.09 2018-09  \n",
-       "729                            409.62 2018-10  \n",
-       "730                            410.39 2018-11  \n",
-       "731                            410.16 2018-12  \n",
-       "732                            410.87 2019-01  \n",
-       "733                            410.90 2019-02  \n",
-       "734                            410.45 2019-03  \n",
-       "735                            410.72 2019-04  \n",
-       "736                            411.42 2019-05  \n",
-       "737                            411.38 2019-06  \n",
-       "738                            411.03 2019-07  \n",
-       "739                            411.62 2019-08  \n",
-       "740                            412.06 2019-09  \n",
-       "741                            412.07 2019-10  \n",
-       "742                            412.56 2019-11  \n",
-       "743                            412.78 2019-12  \n",
-       "744                            413.33 2020-01  \n",
-       "\n",
-       "[743 rows x 11 columns]"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data['period'] = [pd.Period(freq='M',year=year,month=month) for (year,month) in zip(data['Yr'], data['Mn'])]\n",
-    "data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Int64Index([  2,   3,   4,   5,   6,   7,   8,   9,  10,  11,\n",
-      "            ...\n",
-      "            735, 736, 737, 738, 739, 740, 741, 742, 743, 744],\n",
-      "           dtype='int64', length=743)\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
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-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
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-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
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-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
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-       "</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 Excel</th>\n",
-       "      <th>Date</th>\n",
-       "      <th>CO2 [ppm]</th>\n",
-       "      <th>seasonally adjusted [ppm]</th>\n",
-       "      <th>fit [ppm]</th>\n",
-       "      <th>seasonally adjusted fit [ppm]</th>\n",
-       "      <th>CO2 filled [ppm]</th>\n",
-       "      <th>seasonally adjusted filled [ppm]</th>\n",
-       "      <th>period</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>3</td>\n",
-       "      <td>21259</td>\n",
-       "      <td>1958.2027</td>\n",
-       "      <td>315.70</td>\n",
-       "      <td>314.44</td>\n",
-       "      <td>316.19</td>\n",
-       "      <td>314.91</td>\n",
-       "      <td>315.70</td>\n",
-       "      <td>314.44</td>\n",
-       "      <td>1958-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>4</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>314.99</td>\n",
-       "      <td>317.45</td>\n",
-       "      <td>315.16</td>\n",
-       "      <td>1958-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>5</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",
-       "      <td>1958-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>6</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",
-       "      <td>1958-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>7</td>\n",
-       "      <td>21381</td>\n",
-       "      <td>1958.5370</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>315.19</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>315.22</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>315.19</td>\n",
-       "      <td>1958-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>8</td>\n",
-       "      <td>21412</td>\n",
-       "      <td>1958.6219</td>\n",
-       "      <td>314.93</td>\n",
-       "      <td>316.19</td>\n",
-       "      <td>314.00</td>\n",
-       "      <td>315.29</td>\n",
-       "      <td>314.93</td>\n",
-       "      <td>316.19</td>\n",
-       "      <td>1958-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>9</td>\n",
-       "      <td>21443</td>\n",
-       "      <td>1958.7068</td>\n",
-       "      <td>313.21</td>\n",
-       "      <td>316.08</td>\n",
-       "      <td>312.46</td>\n",
-       "      <td>315.35</td>\n",
-       "      <td>313.21</td>\n",
-       "      <td>316.08</td>\n",
-       "      <td>1958-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>10</td>\n",
-       "      <td>21473</td>\n",
-       "      <td>1958.7890</td>\n",
-       "      <td>-99.99</td>\n",
-       "      <td>-99.99</td>\n",
-       "      <td>312.44</td>\n",
-       "      <td>315.40</td>\n",
-       "      <td>312.44</td>\n",
-       "      <td>315.40</td>\n",
-       "      <td>1958-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>11</td>\n",
-       "      <td>21504</td>\n",
-       "      <td>1958.8740</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>315.20</td>\n",
-       "      <td>313.62</td>\n",
-       "      <td>315.46</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>315.20</td>\n",
-       "      <td>1958-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>1958</td>\n",
-       "      <td>12</td>\n",
-       "      <td>21534</td>\n",
-       "      <td>1958.9562</td>\n",
-       "      <td>314.67</td>\n",
-       "      <td>315.43</td>\n",
-       "      <td>314.77</td>\n",
-       "      <td>315.51</td>\n",
-       "      <td>314.67</td>\n",
-       "      <td>315.43</td>\n",
-       "      <td>1958-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>1</td>\n",
-       "      <td>21565</td>\n",
-       "      <td>1959.0411</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>315.54</td>\n",
-       "      <td>315.62</td>\n",
-       "      <td>315.57</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>315.54</td>\n",
-       "      <td>1959-01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>2</td>\n",
-       "      <td>21596</td>\n",
-       "      <td>1959.1260</td>\n",
-       "      <td>316.49</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>316.27</td>\n",
-       "      <td>315.63</td>\n",
-       "      <td>316.49</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>1959-02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>3</td>\n",
-       "      <td>21624</td>\n",
-       "      <td>1959.2027</td>\n",
-       "      <td>316.65</td>\n",
-       "      <td>315.38</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>315.69</td>\n",
-       "      <td>316.65</td>\n",
-       "      <td>315.38</td>\n",
-       "      <td>1959-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>4</td>\n",
-       "      <td>21655</td>\n",
-       "      <td>1959.2877</td>\n",
-       "      <td>317.72</td>\n",
-       "      <td>315.42</td>\n",
-       "      <td>318.09</td>\n",
-       "      <td>315.77</td>\n",
-       "      <td>317.72</td>\n",
-       "      <td>315.42</td>\n",
-       "      <td>1959-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>5</td>\n",
-       "      <td>21685</td>\n",
-       "      <td>1959.3699</td>\n",
-       "      <td>318.29</td>\n",
-       "      <td>315.49</td>\n",
-       "      <td>318.65</td>\n",
-       "      <td>315.85</td>\n",
-       "      <td>318.29</td>\n",
-       "      <td>315.49</td>\n",
-       "      <td>1959-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>6</td>\n",
-       "      <td>21716</td>\n",
-       "      <td>1959.4548</td>\n",
-       "      <td>318.15</td>\n",
-       "      <td>316.03</td>\n",
-       "      <td>318.04</td>\n",
-       "      <td>315.94</td>\n",
-       "      <td>318.15</td>\n",
-       "      <td>316.03</td>\n",
-       "      <td>1959-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>7</td>\n",
-       "      <td>21746</td>\n",
-       "      <td>1959.5370</td>\n",
-       "      <td>316.54</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>316.67</td>\n",
-       "      <td>316.03</td>\n",
-       "      <td>316.54</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>1959-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>8</td>\n",
-       "      <td>21777</td>\n",
-       "      <td>1959.6219</td>\n",
-       "      <td>314.80</td>\n",
-       "      <td>316.06</td>\n",
-       "      <td>314.83</td>\n",
-       "      <td>316.12</td>\n",
-       "      <td>314.80</td>\n",
-       "      <td>316.06</td>\n",
-       "      <td>1959-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>9</td>\n",
-       "      <td>21808</td>\n",
-       "      <td>1959.7068</td>\n",
-       "      <td>313.84</td>\n",
-       "      <td>316.72</td>\n",
-       "      <td>313.32</td>\n",
-       "      <td>316.22</td>\n",
-       "      <td>313.84</td>\n",
-       "      <td>316.72</td>\n",
-       "      <td>1959-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>21</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>10</td>\n",
-       "      <td>21838</td>\n",
-       "      <td>1959.7890</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>316.32</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>316.30</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>316.32</td>\n",
-       "      <td>1959-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>11</td>\n",
-       "      <td>21869</td>\n",
-       "      <td>1959.8740</td>\n",
-       "      <td>314.81</td>\n",
-       "      <td>316.68</td>\n",
-       "      <td>314.54</td>\n",
-       "      <td>316.39</td>\n",
-       "      <td>314.81</td>\n",
-       "      <td>316.68</td>\n",
-       "      <td>1959-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>12</td>\n",
-       "      <td>21899</td>\n",
-       "      <td>1959.9562</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>315.72</td>\n",
-       "      <td>316.47</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>1959-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>1</td>\n",
-       "      <td>21930</td>\n",
-       "      <td>1960.0410</td>\n",
-       "      <td>316.43</td>\n",
-       "      <td>316.39</td>\n",
-       "      <td>316.61</td>\n",
-       "      <td>316.56</td>\n",
-       "      <td>316.43</td>\n",
-       "      <td>316.39</td>\n",
-       "      <td>1960-01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>2</td>\n",
-       "      <td>21961</td>\n",
-       "      <td>1960.1257</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>317.27</td>\n",
-       "      <td>316.64</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>1960-02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>26</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>3</td>\n",
-       "      <td>21990</td>\n",
-       "      <td>1960.2049</td>\n",
-       "      <td>317.58</td>\n",
-       "      <td>316.28</td>\n",
-       "      <td>318.03</td>\n",
-       "      <td>316.71</td>\n",
-       "      <td>317.58</td>\n",
-       "      <td>316.28</td>\n",
-       "      <td>1960-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>4</td>\n",
-       "      <td>22021</td>\n",
-       "      <td>1960.2896</td>\n",
-       "      <td>319.03</td>\n",
-       "      <td>316.70</td>\n",
-       "      <td>319.14</td>\n",
-       "      <td>316.79</td>\n",
-       "      <td>319.03</td>\n",
-       "      <td>316.70</td>\n",
-       "      <td>1960-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>5</td>\n",
-       "      <td>22051</td>\n",
-       "      <td>1960.3716</td>\n",
-       "      <td>320.04</td>\n",
-       "      <td>317.22</td>\n",
-       "      <td>319.67</td>\n",
-       "      <td>316.86</td>\n",
-       "      <td>320.04</td>\n",
-       "      <td>317.22</td>\n",
-       "      <td>1960-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>6</td>\n",
-       "      <td>22082</td>\n",
-       "      <td>1960.4563</td>\n",
-       "      <td>319.59</td>\n",
-       "      <td>317.48</td>\n",
-       "      <td>319.01</td>\n",
-       "      <td>316.93</td>\n",
-       "      <td>319.59</td>\n",
-       "      <td>317.48</td>\n",
-       "      <td>1960-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>30</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>7</td>\n",
-       "      <td>22112</td>\n",
-       "      <td>1960.5383</td>\n",
-       "      <td>318.18</td>\n",
-       "      <td>317.53</td>\n",
-       "      <td>317.60</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>318.18</td>\n",
-       "      <td>317.53</td>\n",
-       "      <td>1960-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>31</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>8</td>\n",
-       "      <td>22143</td>\n",
-       "      <td>1960.6230</td>\n",
-       "      <td>315.90</td>\n",
-       "      <td>317.20</td>\n",
-       "      <td>315.69</td>\n",
-       "      <td>317.01</td>\n",
-       "      <td>315.90</td>\n",
-       "      <td>317.20</td>\n",
-       "      <td>1960-08</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",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>715</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>8</td>\n",
-       "      <td>42962</td>\n",
-       "      <td>2017.6219</td>\n",
-       "      <td>405.24</td>\n",
-       "      <td>406.77</td>\n",
-       "      <td>405.20</td>\n",
-       "      <td>406.76</td>\n",
-       "      <td>405.24</td>\n",
-       "      <td>406.77</td>\n",
-       "      <td>2017-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>716</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>9</td>\n",
-       "      <td>42993</td>\n",
-       "      <td>2017.7068</td>\n",
-       "      <td>403.27</td>\n",
-       "      <td>406.76</td>\n",
-       "      <td>403.41</td>\n",
-       "      <td>406.92</td>\n",
-       "      <td>403.27</td>\n",
-       "      <td>406.76</td>\n",
-       "      <td>2017-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>717</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>10</td>\n",
-       "      <td>43023</td>\n",
-       "      <td>2017.7890</td>\n",
-       "      <td>403.64</td>\n",
-       "      <td>407.25</td>\n",
-       "      <td>403.47</td>\n",
-       "      <td>407.07</td>\n",
-       "      <td>403.64</td>\n",
-       "      <td>407.25</td>\n",
-       "      <td>2017-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>718</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>11</td>\n",
-       "      <td>43054</td>\n",
-       "      <td>2017.8740</td>\n",
-       "      <td>405.17</td>\n",
-       "      <td>407.43</td>\n",
-       "      <td>404.98</td>\n",
-       "      <td>407.22</td>\n",
-       "      <td>405.17</td>\n",
-       "      <td>407.43</td>\n",
-       "      <td>2017-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>719</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>12</td>\n",
-       "      <td>43084</td>\n",
-       "      <td>2017.9562</td>\n",
-       "      <td>406.75</td>\n",
-       "      <td>407.68</td>\n",
-       "      <td>406.46</td>\n",
-       "      <td>407.37</td>\n",
-       "      <td>406.75</td>\n",
-       "      <td>407.68</td>\n",
-       "      <td>2017-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>720</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>1</td>\n",
-       "      <td>43115</td>\n",
-       "      <td>2018.0411</td>\n",
-       "      <td>408.05</td>\n",
-       "      <td>408.00</td>\n",
-       "      <td>407.58</td>\n",
-       "      <td>407.52</td>\n",
-       "      <td>408.05</td>\n",
-       "      <td>408.00</td>\n",
-       "      <td>2018-01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>721</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>2</td>\n",
-       "      <td>43146</td>\n",
-       "      <td>2018.1260</td>\n",
-       "      <td>408.34</td>\n",
-       "      <td>407.59</td>\n",
-       "      <td>408.44</td>\n",
-       "      <td>407.68</td>\n",
-       "      <td>408.34</td>\n",
-       "      <td>407.59</td>\n",
-       "      <td>2018-02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>722</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>3</td>\n",
-       "      <td>43174</td>\n",
-       "      <td>2018.2027</td>\n",
-       "      <td>409.25</td>\n",
-       "      <td>407.71</td>\n",
-       "      <td>409.39</td>\n",
-       "      <td>407.82</td>\n",
-       "      <td>409.25</td>\n",
-       "      <td>407.71</td>\n",
-       "      <td>2018-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>723</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>4</td>\n",
-       "      <td>43205</td>\n",
-       "      <td>2018.2877</td>\n",
-       "      <td>410.30</td>\n",
-       "      <td>407.51</td>\n",
-       "      <td>410.82</td>\n",
-       "      <td>408.00</td>\n",
-       "      <td>410.30</td>\n",
-       "      <td>407.51</td>\n",
-       "      <td>2018-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>724</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>5</td>\n",
-       "      <td>43235</td>\n",
-       "      <td>2018.3699</td>\n",
-       "      <td>411.30</td>\n",
-       "      <td>407.90</td>\n",
-       "      <td>411.60</td>\n",
-       "      <td>408.20</td>\n",
-       "      <td>411.30</td>\n",
-       "      <td>407.90</td>\n",
-       "      <td>2018-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>725</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>6</td>\n",
-       "      <td>43266</td>\n",
-       "      <td>2018.4548</td>\n",
-       "      <td>410.88</td>\n",
-       "      <td>408.30</td>\n",
-       "      <td>410.97</td>\n",
-       "      <td>408.42</td>\n",
-       "      <td>410.88</td>\n",
-       "      <td>408.30</td>\n",
-       "      <td>2018-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>726</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>7</td>\n",
-       "      <td>43296</td>\n",
-       "      <td>2018.5370</td>\n",
-       "      <td>408.90</td>\n",
-       "      <td>408.08</td>\n",
-       "      <td>409.43</td>\n",
-       "      <td>408.65</td>\n",
-       "      <td>408.90</td>\n",
-       "      <td>408.08</td>\n",
-       "      <td>2018-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>727</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>8</td>\n",
-       "      <td>43327</td>\n",
-       "      <td>2018.6219</td>\n",
-       "      <td>407.10</td>\n",
-       "      <td>408.63</td>\n",
-       "      <td>407.33</td>\n",
-       "      <td>408.91</td>\n",
-       "      <td>407.10</td>\n",
-       "      <td>408.63</td>\n",
-       "      <td>2018-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>728</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>9</td>\n",
-       "      <td>43358</td>\n",
-       "      <td>2018.7068</td>\n",
-       "      <td>405.59</td>\n",
-       "      <td>409.09</td>\n",
-       "      <td>405.66</td>\n",
-       "      <td>409.18</td>\n",
-       "      <td>405.59</td>\n",
-       "      <td>409.09</td>\n",
-       "      <td>2018-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>729</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>10</td>\n",
-       "      <td>43388</td>\n",
-       "      <td>2018.7890</td>\n",
-       "      <td>405.99</td>\n",
-       "      <td>409.62</td>\n",
-       "      <td>405.83</td>\n",
-       "      <td>409.44</td>\n",
-       "      <td>405.99</td>\n",
-       "      <td>409.62</td>\n",
-       "      <td>2018-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>730</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>11</td>\n",
-       "      <td>43419</td>\n",
-       "      <td>2018.8740</td>\n",
-       "      <td>408.12</td>\n",
-       "      <td>410.39</td>\n",
-       "      <td>407.47</td>\n",
-       "      <td>409.72</td>\n",
-       "      <td>408.12</td>\n",
-       "      <td>410.39</td>\n",
-       "      <td>2018-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>731</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>12</td>\n",
-       "      <td>43449</td>\n",
-       "      <td>2018.9562</td>\n",
-       "      <td>409.23</td>\n",
-       "      <td>410.16</td>\n",
-       "      <td>409.07</td>\n",
-       "      <td>409.97</td>\n",
-       "      <td>409.23</td>\n",
-       "      <td>410.16</td>\n",
-       "      <td>2018-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>732</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>1</td>\n",
-       "      <td>43480</td>\n",
-       "      <td>2019.0411</td>\n",
-       "      <td>410.92</td>\n",
-       "      <td>410.87</td>\n",
-       "      <td>410.29</td>\n",
-       "      <td>410.23</td>\n",
-       "      <td>410.92</td>\n",
-       "      <td>410.87</td>\n",
-       "      <td>2019-01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>733</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>2</td>\n",
-       "      <td>43511</td>\n",
-       "      <td>2019.1260</td>\n",
-       "      <td>411.66</td>\n",
-       "      <td>410.90</td>\n",
-       "      <td>411.24</td>\n",
-       "      <td>410.47</td>\n",
-       "      <td>411.66</td>\n",
-       "      <td>410.90</td>\n",
-       "      <td>2019-02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>734</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>3</td>\n",
-       "      <td>43539</td>\n",
-       "      <td>2019.2027</td>\n",
-       "      <td>412.00</td>\n",
-       "      <td>410.45</td>\n",
-       "      <td>412.25</td>\n",
-       "      <td>410.68</td>\n",
-       "      <td>412.00</td>\n",
-       "      <td>410.45</td>\n",
-       "      <td>2019-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>735</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>4</td>\n",
-       "      <td>43570</td>\n",
-       "      <td>2019.2877</td>\n",
-       "      <td>413.52</td>\n",
-       "      <td>410.72</td>\n",
-       "      <td>413.73</td>\n",
-       "      <td>410.91</td>\n",
-       "      <td>413.52</td>\n",
-       "      <td>410.72</td>\n",
-       "      <td>2019-04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>736</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>5</td>\n",
-       "      <td>43600</td>\n",
-       "      <td>2019.3699</td>\n",
-       "      <td>414.83</td>\n",
-       "      <td>411.42</td>\n",
-       "      <td>414.54</td>\n",
-       "      <td>411.13</td>\n",
-       "      <td>414.83</td>\n",
-       "      <td>411.42</td>\n",
-       "      <td>2019-05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>737</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>6</td>\n",
-       "      <td>43631</td>\n",
-       "      <td>2019.4548</td>\n",
-       "      <td>413.96</td>\n",
-       "      <td>411.38</td>\n",
-       "      <td>413.91</td>\n",
-       "      <td>411.35</td>\n",
-       "      <td>413.96</td>\n",
-       "      <td>411.38</td>\n",
-       "      <td>2019-06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>738</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>7</td>\n",
-       "      <td>43661</td>\n",
-       "      <td>2019.5370</td>\n",
-       "      <td>411.85</td>\n",
-       "      <td>411.03</td>\n",
-       "      <td>412.36</td>\n",
-       "      <td>411.57</td>\n",
-       "      <td>411.85</td>\n",
-       "      <td>411.03</td>\n",
-       "      <td>2019-07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>739</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>8</td>\n",
-       "      <td>43692</td>\n",
-       "      <td>2019.6219</td>\n",
-       "      <td>410.08</td>\n",
-       "      <td>411.62</td>\n",
-       "      <td>410.23</td>\n",
-       "      <td>411.81</td>\n",
-       "      <td>410.08</td>\n",
-       "      <td>411.62</td>\n",
-       "      <td>2019-08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>740</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>9</td>\n",
-       "      <td>43723</td>\n",
-       "      <td>2019.7068</td>\n",
-       "      <td>408.55</td>\n",
-       "      <td>412.06</td>\n",
-       "      <td>408.52</td>\n",
-       "      <td>412.05</td>\n",
-       "      <td>408.55</td>\n",
-       "      <td>412.06</td>\n",
-       "      <td>2019-09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>741</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>10</td>\n",
-       "      <td>43753</td>\n",
-       "      <td>2019.7890</td>\n",
-       "      <td>408.43</td>\n",
-       "      <td>412.07</td>\n",
-       "      <td>408.67</td>\n",
-       "      <td>412.29</td>\n",
-       "      <td>408.43</td>\n",
-       "      <td>412.07</td>\n",
-       "      <td>2019-10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>742</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>11</td>\n",
-       "      <td>43784</td>\n",
-       "      <td>2019.8740</td>\n",
-       "      <td>410.28</td>\n",
-       "      <td>412.56</td>\n",
-       "      <td>410.29</td>\n",
-       "      <td>412.54</td>\n",
-       "      <td>410.28</td>\n",
-       "      <td>412.56</td>\n",
-       "      <td>2019-11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>743</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>12</td>\n",
-       "      <td>43814</td>\n",
-       "      <td>2019.9562</td>\n",
-       "      <td>411.85</td>\n",
-       "      <td>412.78</td>\n",
-       "      <td>411.88</td>\n",
-       "      <td>412.79</td>\n",
-       "      <td>411.85</td>\n",
-       "      <td>412.78</td>\n",
-       "      <td>2019-12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>744</th>\n",
-       "      <td>2020</td>\n",
-       "      <td>1</td>\n",
-       "      <td>43845</td>\n",
-       "      <td>2020.0410</td>\n",
-       "      <td>413.37</td>\n",
-       "      <td>413.33</td>\n",
-       "      <td>413.11</td>\n",
-       "      <td>413.05</td>\n",
-       "      <td>413.37</td>\n",
-       "      <td>413.33</td>\n",
-       "      <td>2020-01</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>743 rows × 11 columns</p>\n",
-       "</div>"
-      ],
+      "image/png": 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\n",
       "text/plain": [
-       "       Yr  Mn  Date Excel       Date  CO2 [ppm]  seasonally adjusted [ppm]  \\\n",
-       "2    1958   3       21259  1958.2027     315.70                     314.44   \n",
-       "3    1958   4       21290  1958.2877     317.45                     315.16   \n",
-       "4    1958   5       21320  1958.3699     317.51                     314.71   \n",
-       "5    1958   6       21351  1958.4548     -99.99                     -99.99   \n",
-       "6    1958   7       21381  1958.5370     315.86                     315.19   \n",
-       "7    1958   8       21412  1958.6219     314.93                     316.19   \n",
-       "8    1958   9       21443  1958.7068     313.21                     316.08   \n",
-       "9    1958  10       21473  1958.7890     -99.99                     -99.99   \n",
-       "10   1958  11       21504  1958.8740     313.33                     315.20   \n",
-       "11   1958  12       21534  1958.9562     314.67                     315.43   \n",
-       "12   1959   1       21565  1959.0411     315.58                     315.54   \n",
-       "13   1959   2       21596  1959.1260     316.49                     315.86   \n",
-       "14   1959   3       21624  1959.2027     316.65                     315.38   \n",
-       "15   1959   4       21655  1959.2877     317.72                     315.42   \n",
-       "16   1959   5       21685  1959.3699     318.29                     315.49   \n",
-       "17   1959   6       21716  1959.4548     318.15                     316.03   \n",
-       "18   1959   7       21746  1959.5370     316.54                     315.86   \n",
-       "19   1959   8       21777  1959.6219     314.80                     316.06   \n",
-       "20   1959   9       21808  1959.7068     313.84                     316.72   \n",
-       "21   1959  10       21838  1959.7890     313.33                     316.32   \n",
-       "22   1959  11       21869  1959.8740     314.81                     316.68   \n",
-       "23   1959  12       21899  1959.9562     315.58                     316.35   \n",
-       "24   1960   1       21930  1960.0410     316.43                     316.39   \n",
-       "25   1960   2       21961  1960.1257     316.98                     316.35   \n",
-       "26   1960   3       21990  1960.2049     317.58                     316.28   \n",
-       "27   1960   4       22021  1960.2896     319.03                     316.70   \n",
-       "28   1960   5       22051  1960.3716     320.04                     317.22   \n",
-       "29   1960   6       22082  1960.4563     319.59                     317.48   \n",
-       "30   1960   7       22112  1960.5383     318.18                     317.53   \n",
-       "31   1960   8       22143  1960.6230     315.90                     317.20   \n",
-       "..    ...  ..         ...        ...        ...                        ...   \n",
-       "715  2017   8       42962  2017.6219     405.24                     406.77   \n",
-       "716  2017   9       42993  2017.7068     403.27                     406.76   \n",
-       "717  2017  10       43023  2017.7890     403.64                     407.25   \n",
-       "718  2017  11       43054  2017.8740     405.17                     407.43   \n",
-       "719  2017  12       43084  2017.9562     406.75                     407.68   \n",
-       "720  2018   1       43115  2018.0411     408.05                     408.00   \n",
-       "721  2018   2       43146  2018.1260     408.34                     407.59   \n",
-       "722  2018   3       43174  2018.2027     409.25                     407.71   \n",
-       "723  2018   4       43205  2018.2877     410.30                     407.51   \n",
-       "724  2018   5       43235  2018.3699     411.30                     407.90   \n",
-       "725  2018   6       43266  2018.4548     410.88                     408.30   \n",
-       "726  2018   7       43296  2018.5370     408.90                     408.08   \n",
-       "727  2018   8       43327  2018.6219     407.10                     408.63   \n",
-       "728  2018   9       43358  2018.7068     405.59                     409.09   \n",
-       "729  2018  10       43388  2018.7890     405.99                     409.62   \n",
-       "730  2018  11       43419  2018.8740     408.12                     410.39   \n",
-       "731  2018  12       43449  2018.9562     409.23                     410.16   \n",
-       "732  2019   1       43480  2019.0411     410.92                     410.87   \n",
-       "733  2019   2       43511  2019.1260     411.66                     410.90   \n",
-       "734  2019   3       43539  2019.2027     412.00                     410.45   \n",
-       "735  2019   4       43570  2019.2877     413.52                     410.72   \n",
-       "736  2019   5       43600  2019.3699     414.83                     411.42   \n",
-       "737  2019   6       43631  2019.4548     413.96                     411.38   \n",
-       "738  2019   7       43661  2019.5370     411.85                     411.03   \n",
-       "739  2019   8       43692  2019.6219     410.08                     411.62   \n",
-       "740  2019   9       43723  2019.7068     408.55                     412.06   \n",
-       "741  2019  10       43753  2019.7890     408.43                     412.07   \n",
-       "742  2019  11       43784  2019.8740     410.28                     412.56   \n",
-       "743  2019  12       43814  2019.9562     411.85                     412.78   \n",
-       "744  2020   1       43845  2020.0410     413.37                     413.33   \n",
-       "\n",
-       "     fit [ppm]  seasonally adjusted fit [ppm]  CO2 filled [ppm]  \\\n",
-       "2       316.19                         314.91            315.70   \n",
-       "3       317.30                         314.99            317.45   \n",
-       "4       317.86                         315.06            317.51   \n",
-       "5       317.24                         315.14            317.24   \n",
-       "6       315.86                         315.22            315.86   \n",
-       "7       314.00                         315.29            314.93   \n",
-       "8       312.46                         315.35            313.21   \n",
-       "9       312.44                         315.40            312.44   \n",
-       "10      313.62                         315.46            313.33   \n",
-       "11      314.77                         315.51            314.67   \n",
-       "12      315.62                         315.57            315.58   \n",
-       "13      316.27                         315.63            316.49   \n",
-       "14      316.98                         315.69            316.65   \n",
-       "15      318.09                         315.77            317.72   \n",
-       "16      318.65                         315.85            318.29   \n",
-       "17      318.04                         315.94            318.15   \n",
-       "18      316.67                         316.03            316.54   \n",
-       "19      314.83                         316.12            314.80   \n",
-       "20      313.32                         316.22            313.84   \n",
-       "21      313.33                         316.30            313.33   \n",
-       "22      314.54                         316.39            314.81   \n",
-       "23      315.72                         316.47            315.58   \n",
-       "24      316.61                         316.56            316.43   \n",
-       "25      317.27                         316.64            316.98   \n",
-       "26      318.03                         316.71            317.58   \n",
-       "27      319.14                         316.79            319.03   \n",
-       "28      319.67                         316.86            320.04   \n",
-       "29      319.01                         316.93            319.59   \n",
-       "30      317.60                         316.98            318.18   \n",
-       "31      315.69                         317.01            315.90   \n",
-       "..         ...                            ...               ...   \n",
-       "715     405.20                         406.76            405.24   \n",
-       "716     403.41                         406.92            403.27   \n",
-       "717     403.47                         407.07            403.64   \n",
-       "718     404.98                         407.22            405.17   \n",
-       "719     406.46                         407.37            406.75   \n",
-       "720     407.58                         407.52            408.05   \n",
-       "721     408.44                         407.68            408.34   \n",
-       "722     409.39                         407.82            409.25   \n",
-       "723     410.82                         408.00            410.30   \n",
-       "724     411.60                         408.20            411.30   \n",
-       "725     410.97                         408.42            410.88   \n",
-       "726     409.43                         408.65            408.90   \n",
-       "727     407.33                         408.91            407.10   \n",
-       "728     405.66                         409.18            405.59   \n",
-       "729     405.83                         409.44            405.99   \n",
-       "730     407.47                         409.72            408.12   \n",
-       "731     409.07                         409.97            409.23   \n",
-       "732     410.29                         410.23            410.92   \n",
-       "733     411.24                         410.47            411.66   \n",
-       "734     412.25                         410.68            412.00   \n",
-       "735     413.73                         410.91            413.52   \n",
-       "736     414.54                         411.13            414.83   \n",
-       "737     413.91                         411.35            413.96   \n",
-       "738     412.36                         411.57            411.85   \n",
-       "739     410.23                         411.81            410.08   \n",
-       "740     408.52                         412.05            408.55   \n",
-       "741     408.67                         412.29            408.43   \n",
-       "742     410.29                         412.54            410.28   \n",
-       "743     411.88                         412.79            411.85   \n",
-       "744     413.11                         413.05            413.37   \n",
-       "\n",
-       "     seasonally adjusted filled [ppm]  period  \n",
-       "2                              314.44 1958-03  \n",
-       "3                              315.16 1958-04  \n",
-       "4                              314.71 1958-05  \n",
-       "5                              315.14 1958-06  \n",
-       "6                              315.19 1958-07  \n",
-       "7                              316.19 1958-08  \n",
-       "8                              316.08 1958-09  \n",
-       "9                              315.40 1958-10  \n",
-       "10                             315.20 1958-11  \n",
-       "11                             315.43 1958-12  \n",
-       "12                             315.54 1959-01  \n",
-       "13                             315.86 1959-02  \n",
-       "14                             315.38 1959-03  \n",
-       "15                             315.42 1959-04  \n",
-       "16                             315.49 1959-05  \n",
-       "17                             316.03 1959-06  \n",
-       "18                             315.86 1959-07  \n",
-       "19                             316.06 1959-08  \n",
-       "20                             316.72 1959-09  \n",
-       "21                             316.32 1959-10  \n",
-       "22                             316.68 1959-11  \n",
-       "23                             316.35 1959-12  \n",
-       "24                             316.39 1960-01  \n",
-       "25                             316.35 1960-02  \n",
-       "26                             316.28 1960-03  \n",
-       "27                             316.70 1960-04  \n",
-       "28                             317.22 1960-05  \n",
-       "29                             317.48 1960-06  \n",
-       "30                             317.53 1960-07  \n",
-       "31                             317.20 1960-08  \n",
-       "..                                ...     ...  \n",
-       "715                            406.77 2017-08  \n",
-       "716                            406.76 2017-09  \n",
-       "717                            407.25 2017-10  \n",
-       "718                            407.43 2017-11  \n",
-       "719                            407.68 2017-12  \n",
-       "720                            408.00 2018-01  \n",
-       "721                            407.59 2018-02  \n",
-       "722                            407.71 2018-03  \n",
-       "723                            407.51 2018-04  \n",
-       "724                            407.90 2018-05  \n",
-       "725                            408.30 2018-06  \n",
-       "726                            408.08 2018-07  \n",
-       "727                            408.63 2018-08  \n",
-       "728                            409.09 2018-09  \n",
-       "729                            409.62 2018-10  \n",
-       "730                            410.39 2018-11  \n",
-       "731                            410.16 2018-12  \n",
-       "732                            410.87 2019-01  \n",
-       "733                            410.90 2019-02  \n",
-       "734                            410.45 2019-03  \n",
-       "735                            410.72 2019-04  \n",
-       "736                            411.42 2019-05  \n",
-       "737                            411.38 2019-06  \n",
-       "738                            411.03 2019-07  \n",
-       "739                            411.62 2019-08  \n",
-       "740                            412.06 2019-09  \n",
-       "741                            412.07 2019-10  \n",
-       "742                            412.56 2019-11  \n",
-       "743                            412.78 2019-12  \n",
-       "744                            413.33 2020-01  \n",
-       "\n",
-       "[743 rows x 11 columns]"
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ref_excel=pd.Timestamp(year=1900,month=1,day=1)\n",
+    "end_pred=pd.Timestamp(year=2025,month=6,day=1)\n",
+    "end_pred_xl=(end_pred-ref_excel).days\n",
+    "xpred=np.linspace(data.iloc[0]['Date Excel'],end_pred_xl,900)\n",
+    "plt.plot(xpred, p4(xpred), c='r',label='Polynomial regression')\n",
+    "plt.plot(x,y,label='seasonally adjusted filled [ppm]')\n",
+    "plt.legend()\n",
+    "prd=p4(end_pred_xl)\n",
+    "print('The model gives %.2f ppm of atmospheric CO2 in June 2025' %prd)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Oscillation saisonnière"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa4e5118c18>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "data.set_index('period')\n",
-    "periods = data.index\n",
-    "print(periods)\n",
-    "data\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)"
+    "data['seasonnal_diff']=data['CO2 filled [ppm]']-data['seasonally adjusted filled [ppm]']\n",
+    "data['seasonnal_diff'].plot(legend=True, title='Atmospheric CO2 data',figsize=(20,5))"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "Un zoom sur les dernières années"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa4e0ff1be0>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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B8Pbbb3f5eZMnT+b9998H+EFeo0hh1QvyKxq44fWNKKV4986JDDQF/+gxkcF+PH11KgeO1POXZdIRSAhXprXmb1/t45Xv87hp0gD+NGfECa+oJw+K4u5zzby/uZClO4sNSCo8xa5duzjnnHNIS0vjqaee4vHHH2fRokU8+OCDpKamkpaWxrp16wB44oknmDhxIjNmzGDYsGHHjvHb3/6WUaNGMXLkSKZNm0Zqair33HMPFouFUaNGce2117JgwYIf3Kk6E3/84x+5+uqrmTp1KlFRUV1+3nPPPceLL77IhAkTqKmpOatzO5I61W28njJ+/HidmZnZ6+c1QmFVI9e8sp6Wdivv3zWJITGhp3z8n5bs5q21BSz46QTOG9q3l1IKIRxFa83/fr2PF1fkcsPEATx5+Ui8vE4+TNFmsXLNK+vJOVLPF7+cSkJk0EkfK1xTdnY2w4cPNzqG6KIT/byUUlu01uO78ny5Y9WDDlc3cd2rG2hstfDOvImnLaoAHpw5jKExoTzw0U4q61t6IaUQwpGeWb6fF1fkcv05CactqgB8vb14/roxoOGX72+jzWLtpaRCiJ4ghVUPKatt5obXNlDb1MZ/5p3T5VU/Ab7ePHtdGrVNbTz48c5TTgwUQjiXZ7/Zz/Pf5XDt+ASe+smo0xZVHRIig/ifuaPYdqiaZ7/Z38MphXBNTz31FGlpaT/4eOqpp4yO9SOy3UIPKK9r4YbXNlBR18J/7pjI6P59zuj5w+PC+N3MoTz5eTYLNx3ixokDeyipEMJRnv/2AM9+c4CrxvXnz3O7XlR1mJ0az5oDFfxrZS6TzVFkDOr6HBPh/LTWTrVyzRU99NBDx/ba6imOuJkhd6wcrKqhlZte30hxdTNv/fQcxg6IOKvj3D45iSmDonhi6R5yy+sdnFII4UgvfHeAfyzfz5Vj+/PXK0efcVHV4bE5KSRHBfOrD7bLVAA3EhAQcNqtCYTxtNZUVlYSEBDQrePI5HUHqmls4/rXNpBbXs+bt01gcjevOMtqm7n42VUkRATx8d0Z+PlIHSyEs/nXyhz+9uU+5o7px9+vTsX7LIuqDnuKa/nJi2uZMjiKN24dL3c53EBbWxtFRUVntC+TMEZAQAD9+/fH19f3B58/k8nrMhToILXNbdzy5kZyjtTz6i3jul1UAcSEBfCXuaP5+TtbePab/fxu5rDTP0kI0Wte/j6Xv325j8vT4h1SVIGt79sfLh3GH5fsse3WPqVru08L5+Xr69vlXcSF65NbIA7Q0NLOT9/azO7iWl68caxDt0mYOTKWa8cn8NL3uWzMq3TYcYUQ3fPqqlz+smwvs1PjedpBRVWHWzMSmT68L39Ztpesw8bvyyOE6DoprLqpqdXCvLc3s72wmuevH8OMlNN34j5Tj85OYWBkEL/5cAc1TW0OP74Q4sy8vjqP//liL5eNjuOZa1Lx8XbsW6lSir9dlUpEsC+/fG8bDS3S8kYIVyGFVTc0t1m46z+ZbMyv4h/XpHLpqLgeOU+wvw/PXJtGaW0zj36W1SPnEEJ0zZtr8nny82wuGxXHc9emObyo6hAZ7Mez144hv7KBPy7e3SPnEEI4nhRWZ6m13co9725l9YEK/nrlaC5P69ej5xszIIL7LhzMZ9uL+XTb4R49lxDixBaszefxpXu4ZGQsz17Xc0VVh3SzifnnD+KjLUV8tl1+74VwBVJYnYU2i5X5C7fy3d4jPHXFSK4Zn9Ar573nPDPjB0bwyKdZFFY19so5hRA2/15fwB+X7OHiETE8f/0YfHu4qOpw34WDGTcwgoc+yeJQpfzeC+HspLA6Q+0WK7/6YDtf7ynjsdkpvbp5p4+3F89cm4YG7v9wBxar7IkiRG94Z8NBHv1sNzNSYvjn9WN7ragC2+/9c9el4aXgXml5I4TTk8LqDFismt8t2snnO0v4/SXD+Onk3l8+mxAZxOOXj2BTQRUvf5/b6+cXwtMs3HiIhz/NYvrwvrx4w1hD9pPrHxHEX64czY7Cap7+WlreCOHMpLDqIqtV89Anu/jvtsPcP2MIPzvXbFiWK8b0Y9boOJ5Zvp+dRdWG5RDC3X2yrYg/fLKLC4b15cUbjSmqOlw6Ko7rzxnAy9/nsvpAuWE5hBCnJoVVF/1322He31zI/PMHce+Fgw3NopTiqZ+Mom+oP796fzuNrbIUWwhHa26z8NTn2YwfGMFLN43F38fb6Eg8OiuFwX1D+M2HO6iQljdCOCUprLrAYtW8uCKHlLgw7r9oiNFxAAgP8uXpa9LIr2zgiaXZRscRwu28v+kQFfWt/PbioU5RVAEE+nnzzxvGUNPUxv0f7sAq8yyFcDpSWHXBF7tKyK9o4BfnD3Kqvl3pZhM/m2bmvU2H+Hp3qdFxhHAbre1WXlmVx4TECCYmm4yO8wPDYsN45LLhfL+/nDfX5hsdRwhxHCmsTkNr290qc3QwM0fGGh3nR34zYwgj+4Xx4Mc7OVIrDT6FcIT/bi2ipKaZ+RcYO+x/MjdNGshFKTH89cu97CqSljdCOBMprE7j2+wj7C2t457zBjm0F5ij+Pl48ey1Y2hqs/DAop0yNCBEN7VbrLz0fS6j+oUzbXD3m6n3BFvLm9FEhfhz73tbqZeWN0I4DSmsTkFrzQsrcugfEcictHij45zUoL4hPHRZCqv2l/P2+gKj4wjh0j7fVcLBykanG/o/Xp8gP569No1DVY3S6koIJyKF1Smsy61ke2E1Pz/X3KsbAp6NmyYO4MJhffnzsr3sK60zOo4QLslqX6gyJCaEi3qgobqjTUw2ce8Fg/nv1sN8sq3I6DhCCKSwOqUXvsuhb6g/V43rb3SU01JK8derRhMW4MN972+jpd1idCQhXM7y7DL2l9Vzz3mD8HLCof8TufeCQZyTGMnDn2RxtKHV6DhCeDwprE5iy8GjrM+r5K5pyQT4OsdS69OJCvHn71elsre0jgVrC4yOI4RL6VioMiAyiFmj44yO02U+3l48NieFhlYLy7JkdbAQRpPC6iReXJFDRJAvN0wcYHSUM3L+sL6MGxjBJ9sOGx1FCJey+kAFO4tquPs8Mz5OPvR/vJS4MMzRwSzZUWx0FCE8XrffPZRSCUqpFUqpbKXUbqXUfY4IZqSswzV8t/cIt09OIsjPx+g4Z2xOajx7S+s4UCZzrYToqhdW5BAbFsDcsf2MjnLGlFLMTo1nQ36lbLsihMEccVnWDtyvtR4OTAJ+oZRKccBxDfOvlTmE+vtwS0ai0VHOyqWj4vBSyNWrEF20uaCKTflV3DUt2Wl2WT9Ts0bHo7VtVaMQwjjdLqy01iVa6632P9cB2YDrXfLZ5RypY1lWKbdkDCQ80NfoOGclOtSfDHMUi3cUo7XsayXE6bzwXQ6mYD+uP8e1hv47G9Q3hJS4MLmgEsJgDp1IoJRKBMYAG0/wtbuUUplKqczycuftzP6vlbkE+Hhz++Qko6N0y5zUeAoqG9l1WHZlFuJUdhZV8/3+cuZNTSLQzzXvVnWYnRrP1kPVFFY1Gh1FCI/lsMJKKRUCfAz8Smtde/zXtdavaq3Ha63HR0dHO+q0DlVY1chn24u5/pwBmEL8jY7TLRePiMXXW8nVqxCn8eKKHMICfLh50kCjo3Rbx2pGGQ4UwjgOKayUUr7Yiqp3tdb/dcQxjfDy97l4K8Vd05KNjtJt4UG+nDukL0t3lkibGyFOYn9ZHV/tLuO2jERCA1xz6L+zhMggxgzoIxdUQhjIEasCFfAGkK21/kf3IxmjrLaZjzKLuHJcf2LDA4yO4xBz0uIpqWlmc0GV0VGEcEr/WpFDkJ83P3Xxof/OZo+OZ3dxLbnl9UZHEcIjOeKO1WTgZuACpdR2+8elDjhur3ptVR4Wrbn7XLPRURxm+vC+BPp6s2SnXL0KcbyDlQ0s3lHMjRMHEBHsZ3Qch7lsdBxKwdIdMhwohBEcsSpwjdZaaa1Ha63T7B9fOCJcb6lqaOXdjYeYkxrPAFOQ0XEcJsjPh+kpMXyxq5Q2i9XoOEI4lZe/z8XH24s7p7r+0H9nMWEBTEyKZPGOw7IqWAgDuNb2wj3krbX5NLVZuOc897lb1WH26DiqGlpZm1NhdBQhnEZJTROLthRxzfj+9A1zj6H/zmanxpNb3kB2iWwSLERv8/jCqra5jQXrCpg5IpbBMaFGx3G4c4dGExbgwxIZFhDimFdX5WHV8LNp7ncxBXDJyDi8vZRMAxDCAB5fWP1n/UHqmtv5xfmDjI7SI/x9vJk5Mpavd5fS3GYxOo4Qhquob+G9TYf4SVo/EiLdZ+i/s8hgP6YMimKJbBIsRK/z6MKqsbWdN9bkc97QaEb1Dzc6To+ZnRpPXUs7K/cdMTqKEIZ7c00+Le1W7jnfPe9WdZidGk/R0Sa2F1YbHUUIj+LRhdV7mwqpamhlvpvereqQnmwiKsRPhgOFx6tpbOPf6w9y6ag4zNEhRsfpUReNiMHP20t+74XoZR5bWLW0W3h1VS4TkyIZnxhpdJwe5ePtxWWj4vgmu4z6lnaj4whhmLfXF1Df0s4vznPviymAsABfzhsazdKdxVhkk2Aheo3HFlYfbzlMWW0L8y9w/zdYsA0LtLRbWb6n1OgoQhiioaWdN9fmc+GwvqTEhxkdp1fMTo3nSF2LbBIsRC/yyMKq3WLl5e9zSe0fzpRBUUbH6RVjB0TQr0+gDAsIj7Vw4yGqG9v4hYdcTAFc2LFJsLS4EaLXeGRhtWRnMYeqGvnF+YOwdeRxf15eilmpcazaX87Rhlaj4wjRq5rbLLy6Oo8Ms4mxAyKMjtNrOjYJXpYlmwQL0Vs8rrCyWjX/WpHL0JhQpg+PMTpOr5o9Op52q2ZZlgwHCs/y0ZYiyuta3H6hyonMSY2nqqGVdbmVRkcRwiN4XGH19Z5SDhyp557zzXh5ecbdqg4j4sNIjg6WYQHhUdosVl5emcuYAX1IN5uMjtPrpg2JIjTAR37vheglHlVYaa3553c5JJqCmDU63ug4vU4pxZzUeDbkV1JW22x0HCF6xWfbizlc3cR8Dxr678zfx5uZI2L5KquUlnbZJFiInuZRhdXK/eXsLq7l7vPMeHvY3aoOs1Pj0RqW7pRJ7ML9Wayaf63MYXhcGBcM62t0HMN0bBL8/b5yo6MI4fY8prDSWvPidznEhwdwxZj+RscxjDk6hBHxYTIsIDzCl1ml5JU3eOzdqg4ZZhORwX4skQsqIXqcxxRWG/OryDx4lJ+da8bPx2O+7ROakxrP9sJqDlU2Gh1FiB6jteaFFTkkRwczc2Ss0XEM5ePtxaWjYvlmTxmNrbJJsBA9yWMqjBdX5BAV4s+1ExKMjmK4Wam2+WVLdspdK+G+Vuw7QnZJLfecN8hjh/47mz06nqY2C99mS89QIXqSRxRWOwqrWX2ggjumJhHg6210HMP16xPI+IERMhwo3FbHQpX+EYFcnuZ5C1VOZEJiJDFh/vJ7L0QP84jC6oUVOYQH+nLTpIFGR3Eac9Li2Vtax/6yOqOjCOFw63Mr2Xaomp+da8bX2yPe5k7Ly0sxa3Q8K/eVU9PUZnQcIdyW27/j7C2tZfmeMm7LSCTE38foOE7jkpFxeClYvF2uXoX7eWFFDn1D/bl6nOcuVDmR2anxtFqsfL1bNgkWoqe4fWH1rxW5BPt589PJiUZHcSrRof5MHhTFkp3FaK2NjiOEw2w9dJR1uZXcOTVZhv6Pk9o/nITIQFkdKEQPcuvCKr+igaU7i7lp0kD6BPkZHcfpzE6N52BlIzuLaoyOIoTDvPhdDn2CfLlh4gCjozgdpRSzR8ezNqeCyvoWo+MI4ZbcurB6aWUOPt5ezJuaZHQUp3TxiFj8vL1YLJNZhZvYU1zLt3uPcPvkJIJl6P+EZqfGY5GeoUL0GLctrA5XN/HfrYe5fkICfUMDjI7jlMIDfTl3aDRLdxZjtcpwoHB9L67MIdTfh1szEo2O4rSGxYYyqG+IrA4UbqHCCe+8um1h9er3uQDcda7Z4CTObU5qPGW1LWwqqDI6ihDdkltezxe7Srg5fSDhgb5Gx3FaHcOBmwqqKK2RnqHCde0urmHqX1c43aiLWxZW5XUtvL+5kLlj+9GvT6DRcZzahcP7Eujr7XT/Ywpxpl74Lgd/Hy/mTZEF053LAAAgAElEQVSh/9OZlRqH1vD5LpnELlxTQ0s79y7cRligD5PNJqPj/IBbFlbvbjxIm8XK3ecNMjqK0wvy82FGSgzLdpXQZrEaHUeIs/LZ9sN8su0w86YkYQrxNzqO05OeocLVPfJZFgWVDTx77Rin+513y8Lq7vPM/Pv2iSRFBRsdxSXMSY3naGMba3IqjI4ixBnbV1rH//t4F+ckRvKr6UOMjuMyZtt7hhZWSc9Q4VoWbSniv1sPc+8Fg0l3srtV4KaFlb+PN1MGRxkdw2VMHRJFWIAPS2SzUOFi6prbuPudLQT7+/DCDWNkl/UzMGt0HCA9Q4VryTlSzyOfZjExKZJfXjjY6DgnJO9CAn8fby4ZGcdXu0tpbrMYHUeILtFa87tFOzlY1ciLN4yhb5is/j0T/SOCGDcwgiU7ZJ6VcA3NbRbmL9xKoJ83z103xmmbq0thJQBb78CGVgsr9krne+Ea3liTz7KsUh6cOZSJyc43HOAKZo+OI7uklpwj0jNUOL8nP9/D3tI6nr4mldhw572QksJKADAp2URUiL+sDhQuYVN+FX9etpeZI2K5c2qy0XFc1qWjbT1D5a6VcHaf7yzhnQ2HuGtaMucP7Wt0nFOSwkoA4O2lmDU6jm/3HqGuuc3oOEKc1JG6Zn6xcCsDIoP4+9WjUco5hwNcQd/QACYlm6RnqHBqhVWN/L+Pd5Ka0IcHLhpqdJzTksJKHDM7NY7WdivL95QZHUWIE2q3WJm/cBv1ze28fNM4QgNkI9Dump0aT155A3tKao2OIsSPtLZbmf/eNlDwwvVj8PNx/rLFIQmVUm8qpY4opbIccTxhjLEDIujXJ1CGA4XT+vtX+2zDgHNHMTQ21Og4bmHmiFh8vJT83gun9L9f72NHYTV/u3I0CZFBRsfpEkeVfguAmQ46ljCIUorZqfGsOVBBVUOr0XGE+IEvs0p4ZVUeN08ayE/G9DM6jtuICPZj6uAolu4okeFA4VS+21vGq6vyuGnSAC4ZFWd0nC5zSGGltV4FSLM5NzA7NY52q2ZZlkxmFc4jr7yeBz6yzbF4eNZwo+O4ndmp8RyubmLroWqjowgBQGlNM/d/uINhsaE8fFmK0XHOiPMPVopelRIXhjk6mMWyWahwEo2t7dz9zlZ8vRX/unEs/j7eRkdyOzNSYvDz8ZIWN8IpWKya+97fRku7lRduGEuAr2v9zvdaYaWUuksplamUyiwvL++t04ozpJRiTmo/6XwvnILWmoc+yWL/kTqeu26MNFXvIaEBvlwwtC+f7yrBYpXhQGGs5789wMb8Kp64fCSD+oYYHeeM9VphpbV+VWs9Xms9Pjo6urdOK87C7FRb5/ul0upCGOydjYf4ZNthfj19CNOGyPtGT5qdGk95XQsb8yuNjiI82LrcCp7/7gBzx/bjynH9jY5zVmQoUPxIcnQII/tJ53thrO2F1Ty+ZDfnDY1m/vmDjI7j9i4Y1pcgP2/ZLFQYpqK+hV+9v52kqGCeuHyk0XHOmqO2W3gPWA8MVUoVKaXmOeK4wjhzUuPZUVRDQUWD0VGEB6pqaOWed7YQExbAs9em4eWkPcHcSaCfNzNSYliWVUKbxWp0HOFhrFbN/R/uoLqpjReuH0uwv4/Rkc6ao1YFXq+1jtNa+2qt+2ut33DEcYVxLhsdD8hwoOh9HRNXKxpaeenGcfQJ8jM6kseYPTqe6sY21uRUGB1FeJhXV+fx/f5yHpmVQkp8mNFxukWGAsUJ9esTyITECNk0UPS65749wOoDFTw+ZwSj+ocbHcejTB0SRViAj0wDEL1q66Gj/O9X+7hkZCw3TRxgdJxuk8JKnNSc1Hj2l9Wzt1RaXYjesWLvEZ7/9gBXj+vPtRMSjI7jcfx9vJk5Mpavd5fR3GYxOo7wADWNbdy7cBux4QH85Ur36P0phZU4qUtGxeHtpeTqVfSKwqpGfvXBdobHhfHET0a6xRusK5qdGk99Szsr98m2OKJnaa158OOdlNU288/rxxAe6B69P6WwEicVFeJPhtnEEml1IXpYc5uFe97dilVrXr7J9TYEdCfpySZMwX4skfmVoof9Z8NBvtxdyu9mDmXMgAij4ziMFFbilOakxnOoqpHthdLqQvScPy3Zza7DNfzjmjQGmoKNjuPRfLy9uHRUHN9ml9HQ0m50HOGmdhfX8OTSbM4bGs0dU5KNjuNQUliJU7poRCx+3l6yt43oMR9mFvLepkLuOc/MjJQYo+MIbMOBzW1WvskuMzqKcEMNLe3cu3AbEcG+PH11qtttpyKFlTil8EBfzhsazdKdxdLqQjjc7uIaHvk0iwyzid/MGGJ0HGE3fmAEceEBckElHE5rzcOfZlFQ2cBz143BFOJvdCSHk8JKnNactHiOSKsL4WA1TW3c/c5W+gT58vz1Y/DxlrcjZ+HlpZg1Oo7v9x+hprHN6DjCjSzaUsQn2w7zywsHMynZZHScHiHvZOK0LhwWQ5CfN1/skqtX4Ri2XZa3U1zdxL9uHEuUG161urpLRsXRZtGsOiCrA4Vj5Byp49HPdjMpOZJ7LxhsdJweI4WVOK1AP2/Sk02sy5E7VsIxXl6VyzfZR3j4suGMGxhpdBxxAqP7hRPi78P6PPm9F93X3GZh/sJtBPp589x1Y/B2s3lVnUlhJbok3Wwir6KBkpomo6MIF/dtdhl//2ofs1PjuTUj0eg44iR8vL2YmBTJhlwprET3aK353aKd7C2t4+lrUokJCzA6Uo+Swkp0SbrZNha+Xt5kRTdkl9Tyy/e2MTI+nL+5yS7L7qzjgqq0ptnoKMKFPf9tDot3FPPbi4dy/tC+RsfpcVJYiS4ZHhtGnyBf1klhJc5SeV0Ld7ydSUiAD6/dMp5AP9kE1Nl1TC5enydNmcXZWbqzmGe+2c/csf245zyz0XF6hRRWoku8vBSTkkysz62UXdjFGWtus/Cz/2RS2dDC67dMIDbcvYcC3EVKXBjhgb4yv1Kcle2F1dz/4Q7GD4zgz3NHecwdaimsRJdlDDJxuLqJwiqZZyW6rqMf2NZD1fzjmjRG9Q83OpLoIi8vxaTkSJnALs5YcXUTd/47k+hQf165eRz+Pp5zh1oKK9FlGfZ5VutyZVhAdN0L3+Xw2fZiHrhoCJeOijM6jjhD6ckmio42UVjVaHQU4SIaWtq54+1MmlotvHnbBLfcBPRUpLASXWaODiE61F+uXkWXfb6zhKeX7+eKMf34xfmDjI4jzkLGoChAFq6IrrFaNb/+YDt7S2v55w1jGBITanSkXieFlegypZRtPyuZZyW6YGdRNfd/tJ1xHja/wt0M7htCVIifXFCJLvn71/v4ek8ZD1+W4hErAE9ECitxRjLMJsrrWsgtrzc6inBiJTVN3PF2JqZg2/yKAF/PmV/hbpRSTEqWhSvi9BZtKeKllbncMHEAP52caHQcw0hhJc5IhlmGBcSpNbba5lc0tLTzxm3jpV2NG0g3myitbSa/osHoKMJJbS6o4vf/3UmG2cSf5ozw6DvUUliJM5IQGUi/PoGyn5U4IatV85sPdpBdYptfMSw2zOhIwgHSj+1nJb/34scOVTbys/9soX9EEP+6cSy+Ht5Q3bO/e3HGlFKkm02sz6vEapVhAfFDTy/fx5e7S/nDpcO5YFiM0XGEgyRFBRMbFiB3qsWP1Da3Me/tzVismjduHU+fID+jIxlOCitxxjLMJqob28gurTU6inAi/91axIsrcrn+nATmTUkyOo5woI4Lqg15Ms9K/J92i5V7F24jv6KBl24cS3J0iNGRnIIUVuKMSd9AcbzMgir+38e7SE828fjlIz16foW7Sk82UVHfyoEjsnBF2Dz5eTbf7y/n8ctHHtuWQ0hhJc5CXHggSVHBUlgJAAqrbPMr+kUE8tJNMr/CXXVcUK3LkQ2CBbyz4SAL1hVw++Qkbpg4wOg4TkXeAcVZSTeb2JhfRbvFanQUYaA6+/yKNouV12V+hVtLiAyif0SgTGAXrDlQwWOLd3P+0Ggeumy40XGcjhRW4qxkmE3Ut7STVSzzrDyVxar55XvbyC1v4F83jsMs8yvcXnqyiQ15VbJwxYPlltdzz7tbGBQdwvPXj8HbS4b9jyeFlTgrk5Klb6Cne+rzbFbsK+dPc0YwZbDMr/AEGYNM1DS1sadELqg8UXVjK/MWbMbX24vXbx1PaICv0ZGckhRW4qxEhfgzNCZU5ll5qIUbD/Hm2nxuy0jkpkkDjY4jekl6sq2A3iDDgR6nzWLl7ne2UlzdzCs3jyMhMsjoSE5LCitx1tLNJjYXVNHaLvOsPMm6nAoe/SyLc4dE87DMr/AoseEBsnDFA2mtefSzLNbnVfKXK0cxPjHS6EhOTQorcdbSzSaa26xsL6w2OoroJXnl9fz8nS0kRQXzzxvG4CMrAD2OLFzxPG+syee9TYXcc56ZuWP7Gx3H6cm7ojhrk5JMKCXzrDxFdWMr897OxMfbizdvm0CYzK/wSOnJsnDFk3y3t4ynvshm5ohYHrhoqNFxXIIUVuKshQf5MjI+XPoGeoA2i5V73t3K4aNNMr/Cw3UsXJHhQPe3t7SWexduY0R8GP+4NhUvWQHYJVJYiW5JN5vYfqiaplaL0VFED7HNr9jNutxK/jx3FBNkfoVHiw71Z0hMiNypdnMV9S3MW5BJsL8Pr98ygSA/H6MjuQyHFFZKqZlKqX1KqRyl1P9zxDGFa0g3m2i1WNly8KjRUUQPeXNtAe9tOsTd55m5cpzMrxC24cDMgqOycMVNNbdZuOvfmVQ2tPD6reOJDQ8wOpJL6XZhpZTyBl4ELgFSgOuVUindPa5wDRMSI/HxUnL16qayDtfw1Od7uCglht/K/Aphl26OoqnNwo4iWbjijp7+eh9bD1Xz9NVpjO7fx+g4LscRd6zOAXK01nla61bgfeByBxxXuIAQfx9G9w+XNhduyGLV/OGTXZhC/Pnfa2R+hfg/k5IjUUrmWbmjvaW1vLm2gOsmJHDZ6Dij47gkRxRW/YDCTn8vsn/uB5RSdymlMpVSmeXl5Q44rXAWGeYodhbVUNfcZnQU4UDvbDjIzqIaHpmVIisAxQ/0CfJjeGyYFFZuxmrVPPxJFmEBPjw4c5jRcVyWIwqrE13G/qiRlNb6Va31eK31+OjoaAecVjiLDLMJi1WzuaDK6CjCQcpqm/n7V/uYOjiK2XLVKk4gw2xiy6GjNLfJwhV3sWhrEZkHj/L7S4YTESwN1c+WIwqrIiCh09/7A8UOOK5wEWMHRuDn4yVXr27k8aV7aLVYeeLykSglQ4Dix9LNJlrbrWw9JAtX3MHRhlb+/EU24wdGcJUsUukWRxRWm4HBSqkkpZQfcB2w2AHHFS4iwNebsQP6yH5WbmLlviN8vrOE+ecPIjEq2Og4wklNSIrES8EG+b13C3/7ai+1ze088ZORMp+ym7pdWGmt24H5wFdANvCh1np3d48rXEuGOYo9JbUcbWg1OorohuY2C498lkVydDA/OzfZ6DjCiYUF+DKqv1xQuYMtB4/y3qZCbp+cyPC4MKPjuDyH7GOltf5Caz1Ea23WWj/liGMK15JhNqE1bMyXN1lX9s/vDlBY1cSTPxmJv4+30XGEk0tPNrGjqJrG1najo4iz1G6x8vCnWcSGBXDf9CFGx3ELsvO6cIjR/fsQ6Ost86xc2IGyOl5dlcfcsf3IMEcZHUe4gHSziTaLJrNA5lm5qrfXHyS7pJbHZqcQ4i+7qzuCFFbCIfx8vJiQFCnDAi5Ka81Dn2YR5OfDHy4dbnQc4SImJEbYNwiW33tXVFrTzD++3sd5Q6OZOTLW6DhuQwor4TAZZhMHjtRzpK7Z6CjiDC3aUsSm/Cp+f8kwokL8jY4jXESQnw9pCX1kg2AX9cTne2i3av40Z4Ss/nUgKayEw6Tbu95vyJP9rFzJ0YZW/se+zPqa8Qmnf4IQnWSYTewqqqZWNgh2Kav2l/P5zhJ+cf4gBppk9a8jSWElHGZEfBihAT6sl76BLuXPy7Kpa27nyStkmbU4c5PMJqwaNufLBZWraG6z8OhnWSRFyerfniCFlXAYH28vJiaZZL6FC9mUX8WHmUXMm5rEsFhZZi3O3NgBskGwq3nl+zwKKht5/PIRsvq3B0hhJRwqw2ziYGUjh6ubjI4iTqO13cpDn+yiX59A7rtwsNFxhIsK8PVm3IAIuaByEQUVDby4ModZo+OYOljay/UEKayEQ6WbbfOs5OrV+b2+Jo8DR+p5/PIRBPnJMmtx9tLNJrJLa6lulA2CnZnWmkcX78bP24tHZqUYHcdtSWElHGpoTCiRwX6sk3lWTq2wqpHnvz3AzBGxXDg8xug4wsWl2zcIloUrzm1ZVimr9pfzmxlDiAkLMDqO25LCSjiUl5ciPdnE+txKtNZGxxEnoLXmkc+y8FaKx+bIVavovtRjGwTLBZWzqm9p5/Ele0iJC+OW9IFGx3FrUlgJh5tkNlFS08zBykajo4gTWJZVysp95fzmoqHEhQcaHUe4AT8fL8YnRsh+Vk7s2eX7Katr5qkrRuLjLf/09yR5dYXDZdjnWclkVudT19zGn5bsJiUujFvlqlU4ULrZxP6yesrrWoyOIo6TXVLLW+sKuG7CAMYMiDA6jtuTwko4XHJUMDFh/jLPygk9/fV+jtS18D9zR8lVq3Cojv6SG+SulVOxWjUPf5pFeKAvD84canQcjyDvrMLhlLLNs9qQJ/OsnMmuohr+vb6AmyYOJC2hj9FxhJsZGR9GiL+PDAc6mUVbithy8Ci/v2QYfYL8jI7jEaSwEj0iwxxFRX0rB47UGx1FABar5qFPd2EK8eeBi+WqVTiej7cX5yRFskGmADiNow2t/HlZNuckRnLVuP5Gx/EYUliJHtGxn9W6HBkOdAbvbDjIzqIaHpmVQnigr9FxhJvKMJvIq2igtEYasTuDvyzbS11zO0/8ZKQ0We5FUliJHpEQGURCZKAMCziBstpm/v7VPqYOjmL26Dij4wg3NsneiH19nlxQGW3LwSo+yCxk3pQkhsaGGh3Ho0hhJXqMbZ5VFRarzLMy0uNL99BqsfLE5XLVKnpWSlwY4YG+rMuRCyojtVusPPRJFvHhAfxS2lX1OimsRI/JMEdR09RGdkmt0VE81sp9R/h8Zwnzzx9EYlSw0XGEm/PyUkxKjpQ71QZbsK6AvaV1PDp7BMH+0q6qt0lhJXrMsXlWsu2CIZrbLDzyWRbJ0cH87Nxko+MID5GebKLoaBOFVbJBsBFKapp4Zvl+LhjWl4tHSLsqI0hhJXpMTFgAydHB0pDZIP/87gCFVU08+ZOR+Pt4Gx1HeIiMQbb9rOT33hhPLs2m3ar54+wRMvRvECmsRI/KMJvYlF9Fm8VqdBSPcqCsjldX5TF3bL9jGzcK0RsG9w0hKsRPhgMN8P3+cj7fVcK9FwxigCnI6DgeSwor0aMyzFE0tFrYWVRjdBSPobXmoU+zCPLz4Q+XDjc6jvAwSikmSiP2XtfcZuFR+9D/ndNk6N9IUliJHtWx/FraXPSeRVuK2JRfxe8vGUZUiL/RcYQHyjCbKK1tJr+iwegoHuOllbkcrGzkictl6N9oUliJHhUZ7Mew2FCZwN5Lqhpa+Z8vshk/MIJrxicYHUd4qPRj+1nJBVVvyK9o4KXvc5mTGs/kQTL0bzQprESPyzBHkVlwlJZ2i9FR3N5flmVT19zOk1eMxMtLJq4KYyTZG7HLBPaep7Xm0c+y8Pf24uHLZOjfGUhhJXpcutlES7uVbYeqjY7i1nYV1fBhZhHzpiYxLDbM6DjCgymlyDBHSSP2XrAsq5TVByq4/6Ih9A0LMDqOQAor0QvOSYrES8E6uXrtUa+tziPE34f55w8yOooQpCebpBF7D9Na89w3BxgSE8LN6YlGxxF2UliJHhce6MuofuGsl3lWPaa4uonPd5Vw3YQEQgOkybIwnjRi73mrDlSwr6yOu6aZ8Zahf6chhZXoFenmKLYXVtPY2m50FLe0YF0BALdNTjQ0hxAdEiKD6B8hjdh70uur84gJ82dOarzRUUQnUliJXpFuNtFm0WQWHDU6itupb2nnvY2HuGRkLP0jZFNA4Tw6GrFbpRG7w+0prmX1gQpuzUjEz0f+KXcm8tMQvWJCYgQ+XkrmWfWADzcXUtfSzh1TZVNA4VwyBpmoaWpjjzRid7jX1+QR5OfNjecMNDqKOI4UVqJXBPn5MGZAH5ln5WAWq+bNtfmMHxhBWkIfo+MI8QPpybY9lWSDYMcqq21myY5irhmfQHiQzKl0NlJYiV6Tnmxi1+EaapvbjI7iNr7aXUrR0SbumJpkdBQhfiQ2PICkKGnE7mgL1hVgsWpunyy/986oW4WVUupqpdRupZRVKTXeUaGEe0o3R2HVsCmvyugobuP11XkMiAxiRkqs0VGEOKF0s4mN+VW0SyN2h2hoaefdDQeZOTJWGi07qe7escoC5gKrHJBFuLkxA/rg7+Ml86wcZMvBo2w9VM3tkxNlqbVwWunJJupb2skqlnlWjvBhZiG1zTKn0pl1q7DSWmdrrfc5KoxwbwG+3owbGCHLrx3kzTX5hAb4cLX0BBROrKMRuwwHdl+7xcqba/MZNzCCsQMijI4jTqLX5lgppe5SSmUqpTLLy8t767TCyWSYTWSX1FLV0Gp0FJdWWNXIsqwSbpg4gGB/H6PjCHFS0aH+DIkJkUbsDvDV7jIKq5q4U+5WObXTFlZKqW+UUlkn+Lj8TE6ktX5Vaz1eaz0+Ojr67BMLl5ZullVCjvDW2gK8lOK2jESjowhxWunJJjILjtLaLvOszpbWmtdW5zHQFMSMlBij44hTOG1hpbWerrUeeYKPz3ojoHAvo/uHE+znLVev3VDb3MYHmw8xa3QcceGBRscR4rTSzSaa2izsKJJG7Gdry8GjbC+sZt6UJJlT6eRkuwXRq3y9vZiQFCnzLbrhg02FNLRamDdFhgOEa5iYZEIpmWfVHa+tziM80JerxvU3Ooo4je5ut3CFUqoISAc+V0p95ZhYwp1lmE3kljdQVttsdBSX026x8tbafCYmRTKqf7jRcYTokohgP4bHhklhdZbyKxr4ek8ZN08aSJCfzKl0dt1dFfiJ1rq/1tpfax2jtb7YUcGE+8qwz7OSN9kz90VWKcU1zbLUWricdLOJLYeO0txmMTqKy3lzTT6+Xl7ckiHta1yBDAWKXjc8LoywAB8prM6Q1prXV+eRFBXMhcP6Gh1HiDOSYTbR2m5l6yFpxH4mjja08tGWQi5Pi6dvaIDRcUQXSGElep23l2JSsol1eTKB/UxkHjzKzqIabp+ShJdMXhUuZkJSJF4KNsgF1Rl5d+NBmtuscpfahUhhJQyRYTZRWNVEYVWj0VFcxuur8+gT5MuVY/sZHUWIMxYW4MuofuHSeeEMNLdZWLDuIOcOiWZobKjRcUQXSWElDNGxn5Xswt41BfbJqzdOHCCTV4XLSjdHsaOomsbWdqOjuITF24upqG+RDUFdjBRWwhBDYkIwBfuxLkeGA7virbX5+Hgpbk1PNDqKEGct3WyizaLZXCDzrE5Ha83ra/IYFhvK5EEmo+OIMyCFlTCEUoqpg6NYdaACi1UbHcep1TS28WFmEXNS+9E3TCavCtc1ITECfx8vVu47YnQUp/f9/nL2l9Vz59RklJI5la5ECithmOkpMVQ1tLLloFy9nsrCTYdoarMwb0qS0VGE6JYgPx+mDIpi+Z4ytJYLqlN5bXUeMWH+zE6NNzqKOENSWAnDnDskGl9vxfI9pUZHcVqt7VYWrMtn8iATKfFhRscRotump8RQdLSJfWV1RkdxWruLa1ibU8ltGUn4+cg/065GfmLCMKEBvqSb5er1VD7fVUxZbYsstRZuo2MPtm/2lBmcxHm9sTqfID9vbjhngNFRxFmQwkoYasbwvhRUNpJbXm90FKdj2xA0n0F9Qzh3cLTRcYRwiL5hAaQm9GF5tsyzOpGSmiYW7yjmmvEJhAf5Gh1HnAUprIShpqfEAPC1XL3+yIa8KnYX1zJPNgQVbuailBh2FFZLv9ATWLCuAKvWMqfShUlhJQwVFx7IqH7hLJfC6kfeWJNHZLAfV4yRDUGFe5k+3HZB9a3ctfqB+pZ2Fm48xCUj40iIDDI6jjhLUlgJw81IiWF7YTVH6uTqtUNueT3fZB/hpkkDCfD1NjqOEA41JCaEhMhAvsmWC6rOPtxcSF1zO3dMlbtVrkwKK2G46cNj0Bq+k6vXY95ck4+fjxc3T5Ju9sL9KKWYPjyGNTkVNLTILuwA7RYrb6zJZ/zACMYMiDA6jugGKayE4YbHhdKvT6AMB9pVNbTy8dYirkjrR3Sov9FxhOgRM1JiaG23svqAdF8A+HJ3KYerm7hzmqwAdnVSWAnDKaWYkWK7epUeYrDQ3s1+ngwHCDc2ITGSsAAfGQ7EtgL4tdX5JJqCjs0/E65LCivhFGakxNAiV6+0tFt4e/1Bpg2JZkiMdLMX7svX24vzh/Xlu71HPL6tVebBo+worGbelCS8ZQWwy5PCSjiFc5JsV6+ePhy4eHsx5XUt3Cl3q4QHmGFva7X1kGe3tXp1VR59gny5alyC0VGEA0hhJZyCXL3ahgPeWJPP0JhQpgyKMjqOED1umr2tlSfvwp5f0cA32WXcPGkggX6yAtgdSGElnMYMD2/KvDankr2ldcybmiTd7IVHCAvwZVKyieUePM/qjTV5+Hp5cXO6rAB2F1JYCafR0ZTZUyezvrY6j6gQfy5Pk272wnNMHx5DXnmDR7a1qmpoZdGWIn4yJp6+oQFGxxEOIoWVcBqhHVevHtiUeX9ZHd/vL+fW9IH4+8hwgPAcHW2tPHE48J0NthXA0mTdvUhhJZzKRSkx5Fd43tXrm2vy8ffx4kbZEFR4mH59AkmJC/O4O9XNbRb+vb6A84bKCmB3I4WVcCqe2JS5or6F/247zJXj+hMZ7Gd0HCF63fSUGLYcPIT2++IAABZxSURBVEplfYvRUXrNZ9sPU1Hfyp1yt8rtSGElnEpceCAj+4V51LDAf9YfpLXdyu2TZYsF4ZlmDI/BqmHFvnKjo/QKq9W2IejwuDAyzCaj4wgHk8JKOJ0Zw2PZVlhNeZ37X702t1l4Z8NBLhjWl0F9Q4yOI4QhRvYLIzYsgOV7So2O0iu+319OzpF67pQVwG5JCivhdGak2Joyf+sBcy4+3XaYyoZW6WYvPJpSiukpfVm1v4LmNovRcXrca6vziA0LYNZoWQHsjqSwEk7HU5oya615fU0+KXFhpCfLcIDwbNOHx9DUZmF9bqXRUXrU7uIa1uVWctvkRPx85J9gdyQ/VeF0PKUpc8dwwB0yHCAE6WYTwX7ebr9w5fXV+QT7eXP9OQOMjiJ6iBRWwil5QlPm11fnExPmL8MBQgD+Pt6cOzSab7PLsLppW6uSmiaW7CjmmgkJhAf6Gh1H9BAprIRTcvemzNkltazJqeDWDBkOEKLD9OExHKlrYdfhGqOj9IgFawuwai0rgN2cvKMLp+TuTZlfW51HoK83N8hwgBDHnD+0L14Kt9wstKGlnYWbDnHJyDgSIoOMjiN6kBRWwmlNH25ryrz1kHs1ZS6paWLx9mKunZBAnyDZEFSIDhHBfoxPjHTLO9UfZRZS19zOPFkB7Pa6VVgppf6ulNqrlNqplPpEKdXHUcGEOG+orSmzu73JLlhnGw6YN0XeYIU43kUpMewtraOwqtHoKA5jsWreWlfAmAF9GDsgwug4ood1947VcmCk1no0sB/4ffcjCWHjjk2Z65rbWLjhEJeMkuEAIU7kwuH2psxuNBz4bXYZBysb5WLKQ3SrsNJaf6217lgPvwHo3/1IQvwfd2vK/MHmQupa2rlL+oMJcUJJUcEM6hviVoXVG2vy6dcnkJkjYo2OInqBI+dY3Q4sc+DxhDh29bp8zxGDk3Rfm8XKm2vymZgUSWqCjJoLcTIzUmLYmFdFTVOb0VG6LetwDRvzq7gtIxEfb5nW7AlO+1NWSn2jlMo6wcflnR7zENAOvHuK49yllMpUSmWWl3tGo03RffF9bE2Z3aGH2Oc7SyiuaeauaXK3SohTmT48hnarZuU+17+gemONbUPQa89JMDqK6CWnLay01tO11iNP8PEZgFLqVmAWcKM+xUQYrfWrWuvxWuvx0dHRjvsOhNtzh6bMWmteXZXHoL4hnD+0r9FxhHBqaQl9iArx45ts1y6symqbWbKjmKvHJxAWIBuCeorurgqcCTwIzNFau88SDuFU3KEp87rcSvaU1HLn1CS8vKR9jRCn4u2luGBYX1buO0Jru9XoOGft3+sLsGjNTycnGh1F9KLuDvi+AIQCy5VS25VSLzsgkxA/0NGU+f+3d+fBUZxnHse/jyQQhyTACIQAi8PmkHwEsI3vW8pmN1k7jpPK+oivOF6yqbiy2WSPJJVsZStbqc1Rm+zWLvEBrJfYxtkcPuIrOLY5fQAGDEbGgEBgwIhbHBI6nv2jW0TGAgTqmZ6e+X2qVMz0TL/zjOAZnnm7+32SfDLrL+ZtoLSokBsnjYg7FJFEqKkaRmNTK2/U7Y47lNNy+Egbv3y9nprKMkYN7h93OJJGBT3Z2d3PjioQkePpaMr82Bv1HDrSSr/ePfpnm3Zrtu1n3toGvvlnE+jTKz/ucEQS4YqzSyksyGPumg+4Ylxp3OGcsl8v28LeQy3cqyuAc44uUZBESHJT5ofm19G3Vz63Xaz2NSLd1bd3PleOK03kOnbt7c6MhXWcN2IAF43WgqC5RoWVJMLUMWdQnMCmzNv3NfHUivfVvkbkNFRXlvH+3sPUbm+MO5RT8uraBjY0HOSLV4zBTOdU5hoVVpIIvfLzuHZC8poyz1xUR1u72teInI7rK8swI3FfqB5eUEdZSSF/cV553KFIDFRYSWLUVCWrKbPa14j0zJDiQiadOTBRF67Ubt/PgnU7ufOy0fQu0H+xuUh/65IYSWvKrPY1Ij1XXVnGyi372L6vKe5QuuXh8JzKW6fqnMpcpcJKEiNJTZnVvkYkGjVVyWnK3NDYzJPLt3LzBSN0TmUOU2EliVJztCnzwbhDOaFn31b7GpEojBtaxKjB/RJRWM1+bRNH2tq5+3KdU5nLVFhJolQfbcqcuR+yHe1rzhrSX+1rRHrIzKiuLGPRul0cbG6NO5zjamppY/Zrm7hu4lDOGlIUdzgSIxVWkihJaMq8aP0uVm/dz31XjVX7GpEIVFeWcaStnfnvNcQdynE9tXwruw4e4V5dAZzzVFhJ4mR6U+YH1L5GJFIXjR7EgL69eDFDZ6rdnYcWbGDisGIuPWtw3OFIzFRYSeJUVw3FHf5Ym3kfsu9ub+TVtQ3cddkota8RiUhBfh7XTRzKy7U7aG3LvKbMC9btZO0HB7QgqAAqrCSBqspLGDGwb0aeZ/XAvA307ZXP7ZeMijsUkaxSXVnGnkMtLKvfG3coH/HwgjpKiwq5YdLwuEORDKDCShKnoynz/Pd2cuhI5pzMqvY1Iqlz1fhSeuVbxl0duG5HI6+828AXLhlFYYFmqUWFlSRUJjZlnrVoo9rXiKRIpq5jN2PhRnoX5HH7JVoQVAIqrCSROpoyz82Qw4EHmlv55eub1L5GJIU+nmHr2O0+eITfLNvCZyaPYHBRYdzhSIZQYSWJlGlNmR9/o57GJrWvEUml6yszaxX2R1/fRFNLO/dollo6UWEliVVTVcauDGjK3NLWzsyFG5mq9jUiKTV8YF/OGV6SETPVR1rbeWTxJq4cV8r4suK4w5EMosJKEuvqDGnK/Ozb23h/72H+Wu1rRFKupqqMpfV72Hkg3nXsnlm5lR2NzdyrWWo5hgorSayS8GTWOL+9qn2NSHpVV5aF69jtiC0Gd+fhBXWMG1rEVeNKY4tDMpMKK0m0mqoyNuw8yLodB2J5/cVh+5ovXan2NSLpcM7wEsoH9In1C9XrdbtZvXU/92hBUOmCCitJtLibMj8wP2hf8+nJal8jkg4dTZnnv7eTppa2WGJ4aH4dZ/TvzU3Ke+mCCitJtDibMr+7PVgYUO1rRNKrpqqMwy1tLFyX/nXsNu48yEu1H3DbxRXKe+mSCitJvOrKsliaMj84P2hfc9vFal8jkk4Xjz2DosKCWJZdmLmwjl55eXzhUuW9dE2FlSReTVVZ2psyf7C/iSeXB+1rBvVX+xqRdCosyOfq8UOYu2YH7Wlcx27f4RZ+tXQLf/mx4Qwt7pO215VkUWEliRdHU+aZC4P2NfdcroUBReJQXTWUhsZmVmxJX1Pmx9+o59CRNrWtkhNSYSWJl+6mzEfb15xbTsVgta8RicO1E4aSn5e+pswtbe3MWrSRS8cOpmp4SVpeU5JJhZVkherKoCnzgjQ0ZZ7z5uagfY0WBBWJzcB+vblo9CDmvpOe9ayeW7WdbfuauPdKzVbJiamwkqxw8digKXOqDwe2tLUzY0Gd2teIZIDqyjLe/aCR+l2HUvo6HQuCji3VQsByciqsJCukqylzR/saNVsWiV9NVbiOXYoPBy6r38OKzXu5+/LRWghYTkqFlWSNVDdldncenB+0r7luor61isRt1OD+jC8rSvkq7A8vqGNA317cfMHIlL6OZAcVVpI1Opoyp+pDdvH6Xax6X+1rRDJJdWUZb2zczb5DLSkZf/PuQzy/aju3TK2gX++ClLyGZBf9K5Gs0dGUecbCOhZv2MXEYcVUlpcwcVgJVeUlDOjXq0fjq32NSOaprirjv15Zz49erOXGSSM4b8SASFdEn7VoI3lm3HmZFgSV7lFhJVnlu5+qYs6bm1mzfT9z1+zgiSVbjj42fEAfJpaXUFlezMRhJVSWlzCmtD/53Zh96mhf842Pj1cbC5EMMmnkQK44u5TZr9Uz+7V6CvKMc4aXMLliEJMrBjKlYhAjB/U9rWbJjU0tzHlzM588v5zyAX1TEL1kIxVWklXGlRXznU9VAcE5UQ2NzbyzbT+12xtZs20/tdsambe2gdbwBPfCgjwmDCv+0OxWZXkxA/t9eDX1h9S+RiQj5eUZs++9mJ0Hmnmrfi/L6vewbNMe5ry5mVmLNgIwpLiQKWGRNWXUoG7Paj2xZAsHmlu1IKickh4VVmb2L8CNQDuwA7jL3bdGEZhIT5kZQ0v6MLSkD9d0ukS6ubWNdTsOsGZbI7Xb9nc5u1U+oE9YaBUzprQ/v1v+PrdOrVD7GpEMVVpUSE1V2dErBVvb2qnd3shb9XtYFhZcL6wOzr8syDOqhpcw5QSzWm3tzsyFdVw0ehDnj9TSKtJ95n76l6abWYm77w9v3w9Uufu0k+134YUX+pIlS077dUWidrzZrfUNB2htd/LzjJf/7hqttC6SYB2zWkGxtYcVm/dxuKUNCGa1Jp85kCmjBjGlYhBb9x7ma3OWM/32KXzi3PKYI5e4mdlSd7+wO8/t0YxVR1EV6g+krxumSIRONrvljooqkYTrzqzWi52uKj7zjL7UVA2LK1xJqB7NWAGY2Q+AO4B9wLXu3nCc590H3AdQUVFxwaZNm3r0uiIiIlHbeaCZ5fV7WbFlL5edVcqlZw2OOyTJAKcyY3XSwsrM5gJdlezfdvcnOz3vn4A+7v69k72oDgWKiIhIUkR6KNDdq7v5uo8CvwdOWliJiIiIZKMerbxuZuM63b0BqO1ZOCIiIiLJ1dN1rH5oZhMIllvYBJz0ikARERGRbNXTqwJvjioQERERkaRTE2YRERGRiKiwEhEREYmICisRERGRiKiwEhEREYmICisRERGRiKiwEhEREYlIj3sFntaLmjUQrHvVYQBBr8EoJWXMVI2rMXNzzFSNWwHURzxmUn6nGjN6SYk1l8dMSs6natxjxxzl7kO6tae7x/4DPJCrYyYpVo2Z+WOmMNaGhMSpMTN8zCTFmuNjJiLnM/F3mimHAp/O4TFTNa7GzM0xUzXu3hSMmZTfqcZMxrgaM1pJyflUjXvaY8ZyKFBEksXMlng3O7uLSPIp509fpsxYiUhmeyDuAEQkrZTzp0kzViIiIiIR0YxVF8zsJjNzM5sYdyxxMbMDJ3n8FTPLqmliMxtpZk+a2Xtmtt7MfmZmvU/w/K+ZWb90xiipo7xX3ivvc0uqcl6FVdduARYAf3UqO5lZfmrCkVQzMwN+A/zO3ccB44Ei4Acn2O1rgD5gs4fyPsco73NeSnJehdUxzKwIuBz4IuEv28yuMbN5ZvZbM3vHzKabWV742AEz+76ZvQ5cGl/k0Qvf9zOd7v+nmd0VY0ipdB3Q5O4zAdy9Dfhb4B4z629mPzazt81spZl91czuB4YDL5vZyzHGHZmTzVZkM+X9nyjvlfe5IJU5X5Dq4BPo08Dz7r7WzHab2ZRw+1SgimBh0+eBzwD/B/QHVrn7d2OJVqJyDrC08wZ3329m9cC9wBhgsru3mtkZ7r7bzL4OXOvuO2OIV6KlvM9NyvvclbKc14zVR90CPB7efjy8D/CGu28Iv9E8BlwRbm8Dfp3eECUFDOjqSg4DrgKmu3srgLvvTmdg6WRmRWb2kpktC7+p3xhuH21ma8zsQTNbbWYvmlnfuOONkPI+Nynvydm8T1nOa8aqEzMbTDA1fK6ZOZBPkHTP8tHk67jfFP4FZKNWPlx894krkDRYDdzceYOZlQBnAhvo+sM3GzUBN4Xf2kuB18zsqfCxccAt7v4lM3uC4Pc1O65Ao6K8/wjlvfI+q/M+1TmvGasP+yzwiLuPcvfR7n4mUEdQsU41szHh8dbPE5zwlu02AVVmVmhmA4Dr4w4ohV4C+pnZHXD05MSfALOAF4FpZlYQPnZGuE8jUJz+UFPKgH81s5XAXGAEUBY+Vufuy8PbS4HR6Q8vJZT3H6a8V95ne96nNOdVWH3YLcBvj9n2a+BWYDHwQ2AVwV/Asc/LGuEHSbO7bwaeAFYCvwTeijWwFPJgQbebgM+Z2XvAWoJvcd8CHiJoRrrSzFYQ/HuAYAG957LlJNbQbcAQ4AJ3nwR8wJ9mLJo7Pa+N7JnxVt6jvFfe51TepzTntUBoN5jZNcA33P1TcceSDmb2MeBBd58adyySPuHVQd8Gznb3r5rZtcAfCU7gBXjG3c8Nn/sNoMjd/zmWYNNAeS+5QHn/J1HlfDZUnhIhM5sG3E+wVovkiI7ZCoIZiqfNbAmwHKiNNTBJC+V9blLep4ZmrEREsxUiOUh5nxo6x0okx4WzFY8B34k7FhFJD+V96mjGSkRERCQimrESERERiYgKK5EcZGYzzGyHma3qtO1jZrY4XHn56XChxI7Vlw+b2fLwZ3qnfT5vQR+11Wb2b3G8FxHpnlPJ+/Cx88PHVoeP9wm3XxDeX2dmPzczi+P9ZCoVViK5aRbwiWO2PQT8o7ufR7B2yzc7Pbbe3SeFP9Pg6OrFPwKud/dzgDIzy+bFJEWSbhbdzPvwisHZwLQwv68BWsJ9/hu4j2BV9nFdjJnTVFiJ5CB3nwcc2/tsAjAvvP0Hjmn10YWxwFp3bwjvz+3GPiISk1PM+48DK919RbjvLndvM7NyoMTdF4cLrD5C0NBYQiqsRKTDKuCG8PbnCPqldRhjZm+Z2atmdmW4bR0wMTxUWEDw4dp5HxHJfMfL+/GAm9kLYXPmvw+3jwC2dNp/S7hNQiqsRKTDPcBXzGwpQS+0I+H2bUCFu08Gvg48amYl7r4H+DIwB5gPbCRo4CsiyXG8vC8g6J13W/jnTeGh/q7Op9LyAp1o5XURAcDdawmm/zGz8cAnw+3NhP3C3H2pma0n+Da7xN2fBp4O97mPoJeYiCTE8fKeYCbqVXffGT72LDCF4LyrkZ2GGAlsTVvACaAZKxEBwMyGhn/mESwaOD28P8TM8sPbYwlOVt1wzD6DgL8hOBFWRBLieHkPvACcb2b9wkP9VwPvuPs2oNHMLgmvBrwDeDKG0DOWZqxEcpCZPUZwlU+pmW0BvgcUmdlXwqf8BpgZ3r4K+L6ZtRLMSE1z944TYH8WtsUA+L67r03LGxCRU3Yqee/ue8zsp8CbBIf6nnX334fP+zLBFYZ9gefCHwlp5XURERGRiOhQoIiIiEhEVFiJiIiIRESFlYiIiEhEVFiJiIiIRESFlYiIiEhEVFiJSFYxs2lmdscpPH+0ma1KZUwikju0jpWIZA0zK3D36Sd/pohIaqiwEpGMYmajgeeB14HJwFqC1Z0rgZ8CRcBO4C5332ZmrwCLgMuBp8ysGDjg7j82s0kEK0n3A9YD94QLH14AzAAOAQvS9+5EJNvpUKCIZKIJwAPufj6wH/gK8B/AZ929oyj6QafnD3T3q939J8eM8wjwD+E4bxOsNA3B6tL3u/ulqXwTIpJ7NGMlIplos7svDG/PBr4FnAv8IWhPRj6wrdPz5xw7gJkNICi4Xg03/Q/wqy62/y/w59G/BRHJRSqsRCQTHdtrqxFYfYIZpoOnMLZ1Mb6ISCR0KFBEMlGFmXUUUbcArwFDOraZWS8zO+dEA7j7PmCPmV0ZbvoC8Kq77wX2mdkV4fbbog9fRHKVZqxEJBOtAe40s18A7xGcX/UC8PPwUF4B8O/A6pOMcycw3cz6ARuAu8PtdwMzzOxQOK6ISCTMXTPiIpI5wqsCn3H3c2MORUTklOlQoIiIiEhENGMlIiIiEhHNWImIiIhERIWViIiISERUWImIiIhERIWViIiISERUWImIiIhE5P8B31fT4mD6C20AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data['seasonnal_diff'][:25].plot(legend=True, title='Atmospheric CO2 data',figsize=(10,5))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On identifie une évolution sinusoïdale dont l'amplitude augmente légèrement.\n",
+    "la période de ces oscillations est d'environ 1 an.\n",
+    "l'amplidue des oscillations est de +/- 3 ppm."
+   ]
   }
  ],
  "metadata": {
+  "celltoolbar": "Hide code",
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",