Skip to content

M
mooc-rr
Commit 16dc2775 authored by c356ed33d414d53760b5d8b0a508adc0's avatar c356ed33d414d53760b5d8b0a508adc0
Browse files
Options

Tests (je n'ai pas mis à jour les commentaires)

parent 32a38a43
Hide whitespace changes
Inline Side-by-side
Showing with 163 additions and 134 deletions
module2/exo5/exo5_fr.ipynb
View file @ 16dc2775
......@@ -40,7 +40,7 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 29,
"metadata": {},
"outputs": [
{
......@@ -261,33 +261,33 @@
"</div>"
],
"text/plain": [
" Date Count Temperature Pressure Malfunction\n",
"0 4/12/81 6 66 50 0\n",
"1 11/12/81 6 70 50 1\n",
"2 3/22/82 6 69 50 0\n",
"3 11/11/82 6 68 50 0\n",
"4 4/04/83 6 67 50 0\n",
"5 6/18/82 6 72 50 0\n",
"6 8/30/83 6 73 100 0\n",
"7 11/28/83 6 70 100 0\n",
"8 2/03/84 6 57 200 1\n",
"9 4/06/84 6 63 200 1\n",
"10 8/30/84 6 70 200 1\n",
"11 10/05/84 6 78 200 0\n",
"12 11/08/84 6 67 200 0\n",
"13 1/24/85 6 53 200 2\n",
"14 4/12/85 6 67 200 0\n",
"15 4/29/85 6 75 200 0\n",
"16 6/17/85 6 70 200 0\n",
"17 7/29/85 6 81 200 0\n",
"18 8/27/85 6 76 200 0\n",
"19 10/03/85 6 79 200 0\n",
"20 10/30/85 6 75 200 2\n",
"21 11/26/85 6 76 200 0\n",
"22 1/12/86 6 58 200 1"
" Date Count Temperature Pressure Malfunction\n",
"0 4/12/81 6 66 50 0\n",
"1 11/12/81 6 70 50 1\n",
"2 3/22/82 6 69 50 0\n",
"3 11/11/82 6 68 50 0\n",
"4 4/04/83 6 67 50 0\n",
"5 6/18/82 6 72 50 0\n",
"6 8/30/83 6 73 100 0\n",
"7 11/28/83 6 70 100 0\n",
"8 2/03/84 6 57 200 1\n",
"9 4/06/84 6 63 200 1\n",
"10 8/30/84 6 70 200 1\n",
"11 10/05/84 6 78 200 0\n",
"12 11/08/84 6 67 200 0\n",
"13 1/24/85 6 53 200 2\n",
"14 4/12/85 6 67 200 0\n",
"15 4/29/85 6 75 200 0\n",
"16 6/17/85 6 70 200 0\n",
"17 7/29/85 6 81 200 0\n",
"18 8/27/85 6 76 200 0\n",
"19 10/03/85 6 79 200 0\n",
"20 10/30/85 6 75 200 2\n",
"21 11/26/85 6 76 200 0\n",
"22 1/12/86 6 58 200 1"
]
},
"execution_count": 1,
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
......@@ -310,129 +310,158 @@
]
},
{
"cell_type": "markdown",
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Temperature\n",
"(50, 55] 0.333333\n",
"(55, 60] 0.166667\n",
"(60, 65] 0.166667\n",
"(65, 70] 0.033333\n",
"(70, 75] 0.083333\n",
"(75, 80] 0.000000\n",
"(80, 85] 0.000000\n",
"Name: Frequency, dtype: float64"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## Inspection graphique des données\n",
"Les vols où aucun incident n'est relevé n'apportant aucun information\n",
"sur l'influence de la température ou de la pression sur les\n",
"dysfonctionnements, nous nous concentrons sur les expériences où au\n",
"moins un joint a été défectueux.\n"
"data = data.groupby(pd.cut(data['Temperature'], np.arange(50, 90, 5))).sum()\n",
"data[\"Frequency\"]=data.Malfunction/data.Count"
]
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date</th>\n",
" <th>Count</th>\n",
" <th>Temperature</th>\n",
" <th>Pressure</th>\n",
" <th>Malfunction</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>11/12/81</td>\n",
" <td>6</td>\n",
" <td>70</td>\n",
" <td>50</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2/03/84</td>\n",
" <td>6</td>\n",
" <td>57</td>\n",
" <td>200</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>4/06/84</td>\n",
" <td>6</td>\n",
" <td>63</td>\n",
" <td>200</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>8/30/84</td>\n",
" <td>6</td>\n",
" <td>70</td>\n",
" <td>200</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>1/24/85</td>\n",
" <td>6</td>\n",
" <td>53</td>\n",
" <td>200</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>10/30/85</td>\n",
" <td>6</td>\n",
" <td>75</td>\n",
" <td>200</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1/12/86</td>\n",
" <td>6</td>\n",
" <td>58</td>\n",
" <td>200</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date Count Temperature Pressure Malfunction\n",
"1 11/12/81 6 70 50 1\n",
"8 2/03/84 6 57 200 1\n",
"9 4/06/84 6 63 200 1\n",
"10 8/30/84 6 70 200 1\n",
"13 1/24/85 6 53 200 2\n",
"20 10/30/85 6 75 200 2\n",
"22 1/12/86 6 58 200 1"
"<matplotlib.axes._subplots.AxesSubplot at 0x7fa3b6cf7668>"
]
},
"execution_count": 2,
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEACAYAAAC08h1NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAIABJREFUeJzt3Xl4VOXdxvHvLxtL2CGsYSdhR8ARQVERAXErIlXAra5IK62KtqWtrbb6qq27FRVw17rQKpXXDQRFQdmCInsgBISwhn0N2Z73j4xv0xjMCUxyJjP357q4yMx5njP34YI7DydnzphzDhERiR4xfgcQEZHKpeIXEYkyKn4RkSij4hcRiTIqfhGRKKPiFxGJMp6K38yGmlm6mWWY2YRStg8zs2VmttTM0sysf7FtG81s+ffbQhleRETKz8q6jt/MYoG1wGAgC1gMjHbOrSo2phZw2DnnzKwHMNU51ym4bSMQcM7tqphDEBGR8vCy4u8DZDjnMp1zucBbwLDiA5xzh9x/voMkAnpXmIhImIrzMKYFsLnY4yzg9JKDzGw48CDQGLio2CYHzDQzB0xyzk0u7UXMbAwwBiAxMfHUTp06eToAERGBJUuW7HLOJXkZ66X4rZTnfrCid85NA6aZ2dnAfcCg4KYznXNbzawx8ImZrXHOfVHK/MnAZIBAIODS0vTjABERr8zsO69jvZzqyQJaFnucDGw93uBgqbc3s0bBx1uDv+8EplF06khERHzipfgXAylm1tbMEoBRwPTiA8ysg5lZ8OveQAKw28wSzax28PlEYAiwIpQHICIi5VPmqR7nXL6ZjQNmALHAi865lWY2Nrj9OWAEcK2Z5QFHgZHBK3yaUHT65/vXesM593EFHYuIiHhQ5uWcftA5fhGR8jGzJc65gJexeueuiEiUUfGLiEQZFb+ISJSJmOLPyStg8hfrWbRhj99RRETCWsQUP8CL8zbyt4/XEI4/sBYRCRcRU/zV42MZN7ADad/t5fO12X7HEREJWxFT/ABXBFqSXL8Gj32yVqt+EZHjiKjiT4iL4VfnpbAsaz+zVu/0O46ISFiKqOIHuKxXC9o2SuTRmekUFmrVLyJSUsQVf1xsDLcPSmHN9oN8tGK733FERMJOxBU/wMU9mpPSuBaPz1pLgVb9IiL/JSKLPzbGuGNwKhk7DzH92y1+xxERCSsRWfwAQ7s2pUuzOjw5ax15BYV+xxERCRsRW/wxMcb4wals3H2Ed7/O8juOiEjYiNjiBzivc2NOaVmPp2ZncCy/wO84IiJhIaKL38y4c3AqW/YdZerizWVPEBGJAhFd/ABnpTTitDb1efqzDHLytOoXEYn44jcz7hzSkR0HjvGPhZv8jiMi4ruIL36Avu0acmaHhjw7J4Mjufl+xxER8VVUFD/A+MEd2XUol1e++s7vKCIivoqa4j+1dX3O7ZjEpC/WczAnz+84IiK+8VT8ZjbUzNLNLMPMJpSyfZiZLTOzpWaWZmb9vc6tTOMHd2TfkTxenLfRzxgiIr4qs/jNLBaYCFwAdAFGm1mXEsNmA6c453oCNwDPl2NupemeXJfzuzbh+bmZ7DuS61cMERFfeVnx9wEynHOZzrlc4C1gWPEBzrlD7j+ffJIIOK9zK9sdg1M5lJvPlLmZfsYQEfGNl+JvARR/91NW8Ln/YmbDzWwN8AFFq37Pc4PzxwRPE6VlZ1fcRyd2alqHi7o346UvN7L70LEKex0RkXDlpfitlOd+cK9j59w051wn4FLgvvLMDc6f7JwLOOcCSUlJHmKduNsHpZKTV8Bzn6+v0NcREQlHXoo/C2hZ7HEysPV4g51zXwDtzaxReedWlg6Na3Fprxa8Ov87dh7I8TuOiEil8lL8i4EUM2trZgnAKGB68QFm1sHMLPh1byAB2O1lrl9uOy+F/ELHM3O06heR6FJm8Tvn8oFxwAxgNTDVObfSzMaa2djgsBHACjNbStFVPCNdkVLnVsSBlFfrholcEUjmjYWb2LLvqN9xREQqjf3nYpzwEQgEXFpaWoW/zpZ9Rzn34TmMODWZBy/rXuGvJyJSUcxsiXMu4GVs1LxztzQt6tVgdJ+W/DNtM5t2H/E7johIpYjq4ge49dwOxMYYT85e53cUEZFKEfXF37hOda7p25pp32SxPvuQ33FERCpc1Bc/wNgB7akeH8sTs7TqF5HIp+IHGtWqxnVntOH9ZVtZs/2A33FERCqUij9ozNntqJUQx+OfrPU7iohIhVLxB9WrmcCNZ7VlxsodrNiy3+84IiIVRsVfzA3921K3RjyPadUvIhFMxV9Mnerx3HJOOz5ds5Ml3+31O46ISIVQ8Zfws35taJiYoHP9IhKxVPwlJFaL4+cD2jMvYxcLMnf7HUdEJORU/KW4um9rGteuxmMz1xKO9zISETkZKv5SVI+PZdzADizauId5Gbv8jiMiElIq/uMYeVpLWtSrwSNa9YtIhFHxH0e1uFh+ObAD327ex6drdvodR0QkZFT8P2LEqcm0alCTR2eupbBQq34RiQwq/h8RHxvD7YNSWLXtADNWbvc7johISKj4yzCsZwvaJyXy+Ky1FGjVLyIRQMVfhtgY4/ZBqazdcYj3l231O46IyElT8XtwUfdmdGpamydmrSO/oNDvOCIiJ0XF70FMjHHH4FQ27DrMu99s8TuOiMhJ8VT8ZjbUzNLNLMPMJpSy/SozWxb89ZWZnVJs20YzW25mS80sLZThK9OQLk3o3qIuT81eR26+Vv0iUnWVWfxmFgtMBC4AugCjzaxLiWEbgHOccz2A+4DJJbaf65zr6ZwLhCCzL8yM8UNSydp7lH8u2ex3HBGRE+Zlxd8HyHDOZTrncoG3gGHFBzjnvnLOfX8f4wVAcmhjhocBqUn0blWPv8/OICevwO84IiInxEvxtwCKL3Gzgs8dz43AR8UeO2CmmS0xszHHm2RmY8wszczSsrOzPcSqfGbGXUM6sv1ADm8u2uR3HBGRE+Kl+K2U50q9oN3MzqWo+H9b7OkznXO9KTpVdKuZnV3aXOfcZOdcwDkXSEpK8hDLH2d0aETfdg2Y+Nl6juZq1S8iVY+X4s8CWhZ7nAz84IJ2M+sBPA8Mc879/43snXNbg7/vBKZRdOqoSrtzSEd2HTrGq/M3+h1FRKTcvBT/YiDFzNqaWQIwCphefICZtQLeBa5xzq0t9nyimdX+/mtgCLAiVOH9clqbBpydmsRzn6/n0LF8v+OIiJRLmcXvnMsHxgEzgNXAVOfcSjMba2Zjg8P+BDQEnilx2WYTYJ6ZfQssAj5wzn0c8qPwwfjBqew9ksdL8zb4HUVEpFwsHO81HwgEXFpa+F/yf9MraSzcsJt5vxlI3ZrxfscRkShmZku8XjKvd+6ehPGDUzmYk8/z8zL9jiIi4pmK/yR0aV6HC7s35cV5G9hzONfvOCIinqj4T9Idg1I5klfApC/W+x1FRMQTFf9JSmlSm2GnNOeVrzay82CO33FERMqk4g+B2walklfgeHaOVv0iEv5U/CHQtlEiI3q34B8LNrFt/1G/44iI/CgVf4j8cmAKDsfTn2b4HUVE5Eep+EOkZYOajDytJVPTNrN5zxG/44iIHJeKP4TGnZuCmfHU7HV+RxEROS4Vfwg1rVudq05vxbvfbCEz+5DfcURESqXiD7GfD2hPQmwMT2rVLyJhSsUfYo1rV+faM1oz/dutrN1x0O84IiI/oOKvAGPPbk9iQhxPzFpb9mARkUqm4q8A9RMTuOHMNny4fDsrt+73O46IyH9R8VeQG89qR53qcTz+iVb9IhJeVPwVpG6NeMac3Y5Zq3fyzaa9fscREfl/Kv4KdN2ZbalfM57HtOoXkTCi4q9AtarF8fMB7Zm7bheLNuzxO46ICKDir3DX9G1DUu1qPDoznXD8mEsRiT4q/gpWIyGWXwxoz8INe/hq/W6/44iIeCt+MxtqZulmlmFmE0rZfpWZLQv++srMTvE6NxqM7tOKZnWr84hW/SISBsosfjOLBSYCFwBdgNFm1qXEsA3AOc65HsB9wORyzI141eNjGTewA99s2sec9Gy/44hIlPOy4u8DZDjnMp1zucBbwLDiA5xzXznnvr9mcQGQ7HVutLj81JYk16/Bo59o1S8i/vJS/C2AzcUeZwWfO54bgY/KO9fMxphZmpmlZWdH3qo4IS6G285LYcWWA8xYucPvOCISxbwUv5XyXKlLVjM7l6Li/2155zrnJjvnAs65QFJSkodYVc/wXi1o1yiRxz9ZS2GhVv0i4g8vxZ8FtCz2OBnYWnKQmfUAngeGOed2l2dutIiLjeG2QSmk7zjI+8u3+R1HRKKUl+JfDKSYWVszSwBGAdOLDzCzVsC7wDXOubXlmRttLunRnNQmtXhi1lryCwr9jiMiUajM4nfO5QPjgBnAamCqc26lmY01s7HBYX8CGgLPmNlSM0v7sbkVcBxVRkyMccegVDKzD/Pe0qj9z4+I+MjC8QqTQCDg0tLS/I5RYQoLHZc8PY+DOfnMvvMc4mP1PjoROTlmtsQ5F/AyVo3jg5gYY/zgVDbtOcK/lmT5HUdEooyK3ycDOzWmZ8t6/H32Oo7lF/gdR0SiiIrfJ2bGnUNS2bo/h7cWbS57gohIiKj4fdS/QyP6tGnA059lcDRXq34RqRwqfh99v+rPPniM1xd853ccEYkSKn6fnd6uIf07NOLZz9dz+Fi+33FEJAqo+MPA+CGp7Dmcy8tfbfQ7iohEARV/GOjdqj4DOzVm8heZHMjJ8zuOiEQ4FX+YGD84lf1H83hh7ga/o4hIhFPxh4luLeoytGtTXpi3gb2Hc/2OIyIRTMUfRu4YnMrh3Hwmz830O4qIRDAVfxjp2LQ2F/dozstfbiT74DG/44hIhFLxh5nbB6VwLL+A5z5f73cUEYlQcX4HkP/WPqkWw3sl89qC79i676jfcUKiQ+Na3DEolZiY0j6QTUQqm4o/DN0xOIWM7EOszz7kd5STll/g+GjFdprUqc7VfVv7HUdEUPGHpeT6NXnv1jP9jhESzjmufmEhD320hkGdm9C0bnW/I4lEPZ3jlwplZjwwvDv5hYXc/e8VhOMH/4hEGxW/VLjWDRMZPziVWat38OHy7X7HEYl6Kn6pFDec2ZbuLepyz/QV7DuiN6iJ+EnFL5UiLjaGh0Z0Z++RPB74cLXfcUSimopfKk3X5nUZc3Y7pqZl8WXGLr/jiEQtT8VvZkPNLN3MMsxsQinbO5nZfDM7ZmZ3ldi20cyWm9lSM0sLVXCpmm47L4U2DWvyu3eX61PHRHxSZvGbWSwwEbgA6AKMNrMuJYbtAX4FPHKc3ZzrnOvpnAucTFip+qrHx/LgZT3YtOcIT8xa63cckajkZcXfB8hwzmU653KBt4BhxQc453Y65xYDupm8lKlf+4aM7tOSKXMzWbFlv99xRKKOl+JvAWwu9jgr+JxXDphpZkvMbMzxBpnZGDNLM7O07OzscuxeqqIJF3SmYa1q/OZfy8grKPQ7jkhU8VL8pd1gpTzvwjnTOdebolNFt5rZ2aUNcs5Nds4FnHOBpKSkcuxeqqK6NeK5b1hXVm07wPP68BmRSuWl+LOAlsUeJwNbvb6Ac25r8PedwDSKTh2JMLRbM87v2oQnZq1lw67DfscRiRpein8xkGJmbc0sARgFTPeyczNLNLPa338NDAFWnGhYiTx/GdaNhLgYfvfuMt3OQaSSlFn8zrl8YBwwA1gNTHXOrTSzsWY2FsDMmppZFjAeuNvMssysDtAEmGdm3wKLgA+ccx9X1MFI1dOkTnV+f2FnFmTuYWra5rIniMhJs3BcZQUCAZeWpkv+o0VhoWP0lAWs2naA2ePPoXEd3cFTpLzMbInXS+b1zl3xXUyM8eBl3TmWX8g901f6HUck4qn4JSy0S6rF7YNS+GjFdj5eoTt4ilQkFb+EjZvPakfnZnX403sr2H9U7wUUqSgqfgkb8bEx/HVEd3YdOsZDH63xO45IxFLxS1jpkVyPG/u35c1Fm1iQudvvOCIRScUvYWf84I60alB0B8+cPN3BUyTUVPwSdmokxPLA8O5s2HWYv3+6zu84IhFHxS9hqX9KI356ajKTPs9k1dYDfscRiSgqfglbf7iwM/VqxjPh3WXk6w6eIiGj4pewVT8xgXsu6cqyrP28/NVGv+OIRAwVv4S1i3s0Y1DnxjwyM51Nu4/4HUckIqj4JayZGfdd2o24mBh+P2257uApEgIqfgl7zerW4LdDOzIvYxfvfL3F7zgiVZ6KX6qEq05vTaB1fe57fxXZB4/5HUekSlPxS5UQE2M8NKI7R3ML+Mv7q/yOI1KlqfilyujQuDbjBnbgf7/dyuzVO/yOI1JlqfilShl7TntSm9Ti7n+v4GCO7uApciJU/FKlJMTF8NCIHmw/kMPDM9L9jiNSJan4pcrp3ao+153RhtcWfEfaxj1+xxGpclT8UiXdNaQjzevWYMK7yzmWrzt4ipSHp+I3s6Fmlm5mGWY2oZTtncxsvpkdM7O7yjNX5EQkVovj/uHdyNh5iImfrfc7jkiVUmbxm1ksMBG4AOgCjDazLiWG7QF+BTxyAnNFTsi5HRtzac/mPDsng/TtB/2OI1JleFnx9wEynHOZzrlc4C1gWPEBzrmdzrnFQMnLLMqcK3Iy/nRJV2pXj+e37yyjoFC3cxDxwkvxtwA2F3ucFXzOi5OZK1KmBokJ/OniLizdvI9X52/0O45IleCl+K2U57wurTzPNbMxZpZmZmnZ2dkedy8Cw3o255zUJB6ekU7WXt3BU6QsXoo/C2hZ7HEysNXj/j3Pdc5Nds4FnHOBpKQkj7sXKbqD5/8M7wbA3f9eoTt4ipTBS/EvBlLMrK2ZJQCjgOke938yc0U8S65fk1+f35E56dlM/9brukQkOpVZ/M65fGAcMANYDUx1zq00s7FmNhbAzJqaWRYwHrjbzLLMrM7x5lbUwUh0u7ZfG3q2rMef/3cVew7n+h1HJGxZOP63OBAIuLS0NL9jSBWUvv0gFz01l0tOac7jI3v6HUek0pjZEudcwMtYvXNXIkrHprX5xYD2TPtmC3PSd/odRyQsqfgl4tw6sAPtkxL5w7QVHD6W73cckbCj4peIUy0ulr+O6MGWfUd5ZKbu4ClSkopfIlKgTQOu6dual7/ayDeb9vodJ+xk7DxEbn6h3zHEJyp+iVi/GdqRJrWrM+Gd5Sq5oM17jvDz15cw6LHP+dmLiziSq1Nh0UjFLxGrdvV47r+0G+k7DjLp8+i+g+fR3AIe+2Qtgx77nDnp2Vx+ajILN+zmuhcXc0g/B4k6Kn6JaIO6NOHiHs34+6cZZOyMvjt4Ouf4YNk2znt0Dk/NXsf5XZvy6V3n8PDlp/DkqF4s2bSXa19YyAF9jGVUUfFLxLvnkq7USIhlwjvLKYyiO3iu3naAUZMXcOsbX1O3ZgJTb+nHU6N70axuDQAuOaU5E6/sxfIt+7n6+YXsO6I3vUULFb9EvKTa1bj7os6kfbeXfyza5HecCrf3cC5//PcKLnpqLmt3HOT+S7vx/i/706dtgx+MHdqtGc9dfSprth3kyikL9Y7nKKHil6jw01OT6d+hEX/9aA3b9h/1O06FKCh0vLbgO859dA7/WPgd1/RtzWd3DeDqvq2JjSntRrlFzuvchCk/C7A++xCjJy8g++CxSkwtflDxS1QwMx4Y3p38wkL+GIF38FyQuZuLnprLH/+9gs5N6/DhbWfx52HdqFczwdP8c1KTeOm609i05wijJs9nx4GcCk4sflLxS9Ro1bAmdw7uyKzVO/lg+Ta/44TE1n1HGffG14yavICDOfk8c1Vv3rj5dDo1rVPufZ3RoREvX38a2/fnMHLSfLbui8z/GYmKX6LM9We2oXuLutw7fWWV/mFmTl4BT81ex8BH5/DJqh3cPiiFWePP4cLuzTA7/mmdspzeriGv3ng6uw/lMnLyfDbv0QfbRCIVv0SVuNgYHhrRnb1H8vifD1b7HafcnHN8vGIbgx77nMc+Wct5nZow+85zuH1QKjUSYkPyGqe2rs/rN53O/iN5jJw0n+92Hw7JfiV8qPgl6nRtXpdbzm7HP5dkMW/dLr/jeLZ2x0GufmEhY1//msSEON64+XQmXtWb5Po1Q/5ap7Ssxxs39+VoXgFXTJrP+uxDIX8N8Y+KX6LSr85LoW2jRH43bRlHcwv8jvOj9h/J497pK7ngybms2HKAvwzryge/6s8Z7RtV6Ot2a1GXN8f0paDQMXLSAtbuiL43wEUqFb9EperxsTx4WXc27znK47PW+h2nVAWFjjcWbuLcR+fw6vyNjO7Tks/uGsC1/doQF1s5/3Q7Na3DW2P6EmMwavICVm09UCmvKxVLxS9Rq2+7hozu05Ln52ayPGu/33H+S9rGPfzk6Xn8ftpyOiTV4n9/2Z/7L+1Og0Rvl2eGUofGtXn7ln5Ui4th9JQFYfdnJeWn4peoNuGCzjSqVY3fvLOMvAL/7+C5fX8Ot731DT99bj57Dufy99G9ePuWvnRtXtfXXG0bJTL1ln7UqhbHlc8v0K2uqzgVv0S1ujXi+cuwbqzedoApczN9y5GTV8DEzzIY+OgcPlqxnV8O7MDsO8/hklOan9TlmaHUskFNpo7tR/2aCVzzwiIWb9zjdyQ5QSp+iXpDuzVlaNemPDFrHRt2Ve6li845Plm1gyGPf8HDM9I5K6URs8efw51DOlIzIa5Ss3jRol4Npt7Sj8a1q/GzFxcxf/1uvyPJCfBU/GY21MzSzSzDzCaUst3M7Kng9mVm1rvYto1mttzMlppZWijDi4TKn4d1pVpcDBPeWVZpd/DM2HmQa19cxM2vplEtLobXbzydSdcEaNkg9JdnhlLTutV565a+tKhXg+tfXsTcddl+R5JyKrP4zSwWmAhcAHQBRptZlxLDLgBSgr/GAM+W2H6uc66ncy5w8pFFQq9Jner84cLOLNywh7fTNlfoax3IyeO+91cx9Im5LN28jz9d3IUPbzuL/ikVe3lmKDWuXZ23xvSlTcNEbnwljc/W7PQ7kpSDlxV/HyDDOZfpnMsF3gKGlRgzDHjVFVkA1DOzZiHOKlKhRp7Wkr7tGvDAh6sr5CZlhYWOqYs3M/CRObz45QYuDyQz564B3NC/LfGVdHlmKDWsVY03b+5LapNajHktjZkrt/sdSTzy8retBVB8CZQVfM7rGAfMNLMlZjbmeC9iZmPMLM3M0rKz9V9HqXxmxoOX9eBYfiH3vLcypPte8t1eLn3mS37zzjJaN0xk+q39efCyHjSsVS2kr1PZ6icm8I+biq46+sU/vuaDZZFx87tI56X4S7ukoORJ0B8bc6ZzrjdFp4NuNbOzS3sR59xk51zAORdISkryEEsk9No2SuT2QSl8vHI7H684+RLbeSCH8VOXMuLZr9hxIIcnRvbkX2P70T3Z38szQ6lujXheu7EPPVvW45dvfs17S7f4HUnK4KX4s4CWxR4nA1u9jnHOff/7TmAaRaeORMLWzWe1o0uzOvzpvZXsP3pin0V7LL+A5z5fz7mPzOH9b7fxiwHt+fTOAVzaq0XYXJ4ZSrWrx/PKDX3o07YBt7+9lH8tyfI7kvwIL8W/GEgxs7ZmlgCMAqaXGDMduDZ4dU9fYL9zbpuZJZpZbQAzSwSGACtCmF8k5OJjY/jriB7sOnSMhz4q/x08P12zg/Mf/4KHPlpDv/aNmHnH2fxmaCcSq4Xf5ZmhlFgtjpeu60P/Do349b++5c0o+JjLqqrMv4nOuXwzGwfMAGKBF51zK81sbHD7c8CHwIVABnAEuD44vQkwLbjCiQPecM59HPKjEAmx7sl1uemsdkz+IpOfnNKCfu0bljknM/sQ972/is/Ss2mXlMjL15/GgI6NKyFt+KiREMuUawP8/PUl/O7d5eQVFHJtvzZ+x5ISLBw/gi4QCLi0NF3yL/46mlvA+U98QWyM8dFtZ1E9vvT73R/MyePpTzN48csNVIuL5fZBKVzbrw0JcVXvSp1QOZZfwLg3vuGTVTu4+6LO3HRWO78jRTwzW+L1kvno/ZspUoYaCbE8MLw7G3Yd5snZ636wvbDQ8a8lWQx89HMmfZHJ8F4t+OyuAdx0VruoLn2AanGxPHNVby7s3pT7P1jNM3My/I4kxUT2SUeRk9Q/pRGXn5rM5C8yubhHs/+/Wdq3m/dxz/SVLN28j54t6zHl2gA9W9bzOW14iY+N4alRvYiP/Za/fZxOXr7jV+d1iMgfblc1Kn6RMvzhos58lr6TCe8sZ8q1AR6dmc4/l2SRVLsaj15+CsN7tSAmRmVWmrjYGB67oifxsTE8PmstuQUF3DWko8rfZyp+kTLUq5nAvT/pyrg3vqH/Xz/FDG45ux3jBnagdvV4v+OFvdgY428jehAfG8PEz9aTm1/I7y/srPL3kYpfxIOLujfjyz672H0olwkXdKJdUi2/I1UpMTHGA8O7kRBrTJm7gbwCxz2XdFH5+0TFL+LB97dzkBNnZtz7k67Ex8bw/LwN5BYUcv+wbjpN5gMVv4hUGjPjDxd1JiEuhmfmrCcvv5CHRvQgVuVfqVT8IlKpzIxfn9+RhLgYnpi1jryCQh65/JRK+wB5UfGLiA/MjNsHpRIfG8PDM9LJK3A8Mapnlbw9dVWk4hcR39x6bgcSYmP4nw9Xk1dQyNNX9o76N79VBv0Ji4ivbj67Hfde0oWZq3Yw9vUl5OQV+B0p4qn4RcR3153ZlgeGd+fTNTu5+dU0juaq/CuSil9EwsKVp7fibz/twbyMXdzw8mKO5Ob7HSliqfhFJGxcEWjJ41f0ZOGG3fzsxUUcOqbyrwgqfhEJK5f2asFTo3vx9aZ9XPPCwhP+FDQ5PhW/iISdi3s055mrerNiy36ufn4h+47k+h0poqj4RSQsnd+1KZOuOZX0HQcZPWUhuw8d8ztSxFDxi0jYGtipCc9fGyAz+xCjpyxg58EcvyNFBBW/iIS1s1OTeOn609i85yijJi9gxwGV/8lS8YtI2DujfSNeuaEPO/bnMHLSfLbuO+p3pCpNxS8iVUKftg147abT2X04lysmzWfzniN+R6qyPBW/mQ01s3QzyzCzCaVsNzN7Krh9mZn19jpXRMSr3q3q88ZNfTltwn1TAAAEx0lEQVSYk8/ISfPZuOuw35GqpDKL38xigYnABUAXYLSZdSkx7AIgJfhrDPBsOeaKiHjWPbkub97cl5z8Qq6YNJ+MnYf8jlTleLk7Zx8gwzmXCWBmbwHDgFXFxgwDXnXOOWCBmdUzs2ZAGw9zRUTKpUvzOrw1pi9XTlnI8Ilf0rRudb8jhUT9mglMHduvwl/HS/G3ADYXe5wFnO5hTAuPcwEwszEU/W+BVq1aeYglItEstUlt3r6lLxM/zSAnPzJu6lanenylvI6X4i/tM9GcxzFe5hY96dxkYDJAIBAodYyISHHtk2rx2MiefseocrwUfxbQstjjZGCrxzEJHuaKiEgl8nJVz2IgxczamlkCMAqYXmLMdODa4NU9fYH9zrltHueKiEglKnPF75zLN7NxwAwgFnjRObfSzMYGtz8HfAhcCGQAR4Drf2xuhRyJiIh4YkUX4oSXQCDg0tLS/I4hIlJlmNkS51zAy1i9c1dEJMqo+EVEooyKX0Qkyqj4RUSiTFj+cNfMsoHvTnB6I2BXCOP4KVKOJVKOA3Qs4ShSjgNO7lhaO+eSvAwMy+I/GWaW5vUn2+EuUo4lUo4DdCzhKFKOAyrvWHSqR0Qkyqj4RUSiTCQW/2S/A4RQpBxLpBwH6FjCUaQcB1TSsUTcOX4REflxkbjiFxGRH6HiFxGJMip+EZEoo+IXEYkyKn4RkSij4hcRiTJePnNXJCyYWUNgdvBhU6AAyA4+7uOcy/Ul2I8wsxuAD51z2/3OIvI9XccvVZKZ3Qsccs49EgZZYp1zBcfZNg8Y55xbWo79xTnn8kMWUKQEneqRiGBmPzOzRWa21MyeMbMYM4szs31m9rCZfW1mM8zsdDP73MwyzezC4NybzGxacHu6md3tcb/3m9kioI+Z/dnMFpvZCjN7zoqMBHoCbwfnJ5hZlpnVC+67r5nNCn59v5lNMrNPgJeCr/FY8LWXmdlNlf+nKpFKxS9Vnpl1A4YDZzjnelJ0CnNUcHNdYKZzrjeQC9wLnAdcDvyl2G76BOf0Bq40s54e9vu1c66Pc24+8KRz7jSge3DbUOfc28BSYKRzrqeHU1G9gEucc9cAY4Cdzrk+wGnArWbW6kT+fERK0jl+iQSDKCrHNDMDqAFsDm476pz7JPj1cmC/cy7fzJYDbYrtY4Zzbi+Amf0b6E/Rv4/j7TcXmFZs/nlm9mugOkX3VF8CfFTO43jPOZcT/HoI0NnMin+jSQE2lXOfIj+g4pdIYMCLzrk//teTZnEUFfT3CoFjxb4u/ve/5A+7XBn7PeqCPyAzs5rA00Bv59wWM7ufom8ApcnnP//TLjnmcIlj+oVzbjYiIaZTPRIJZgFXmFkjKLr65wROiwwxs3rBEh8GfFmO/dag6BvJLjOrDYwotu0gULvY443AqcGvi48raQbwi+A3Gcyso5nVKOcxiZRKK36p8pxzy83sz8AsM4sB8oCxwNZy7GYe8AbQHnjt+6twvOzXObfbzF4BVlD0kaELi21+CXjezI5S9HOEe4EpZrYdWPQjeSYBrYClwdNMOyn6hiRy0nQ5p0S94BUz3Zxzt/udRaQy6FSPiEiU0YpfRCTKaMUvIhJlVPwiIlFGxS8iEmVU/CIiUUbFLyISZf4PTSfQZnL40pkAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data = data[data.Malfunction>0]\n",
"data"
"data['Frequency'].plot()"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fa3b6c51a58>"
]
},
"execution_count": 32,
"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['Count'].plot()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b74a4898>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b7459be0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b74092b0>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b7431940>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b73d9fd0>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b73e5048>],\n",
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b73b2d30>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b7363400>,\n",
" <matplotlib.axes._subplots.AxesSubplot object at 0x7fa3b730ca90>]],\n",
" dtype=object)"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAEWCAYAAABsY4yMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAGolJREFUeJzt3X+0XWWd3/H3h4TAYGwSkhCVhFwUJj8gXeik2HaKYquQWIWxQ5FUXaOLNKUakM5aBdRpFzPjjzDtzMiSYE0n4Ye2ZNA1NVFYwEIKLn8w5EasDlwCQYmEEJOQZCQMgoFv/3h2yMnNTe659+5z9t7P+bzWOiv37HPO3d+7Pznfs8+zn32OIgIzM8vPMVUXYGZmneEGb2aWKTd4M7NMucGbmWXKDd7MLFNu8GZmmXKDNzPLVE83eEn3S/q1pH3FZVOxfL6kfkl7isu9kuZXXa+VQ9IlkgYkvSDpSUnnOPM8SeqTdGeR6XZJN0gaL2mCpG9IekpSSDq36lo7oacbfGF5REwsLnOKZduAi4ATgWnAemBtVQVaeSS9B7gO+BjweuAdwM9w5rm6EdgBvBE4C3gn8PHitu8BHwa2V1Na542vuoA6ioi9wF4ASQJeAU6rtCgryx8DfxIRDxbXn2m5zZnn51Tghoj4NbBd0l3AGRHxMvBFAEmvVFlgJ3kPHr4gaZek7w9+myZpL/Br4EvA56sozsojaRywEJguabOkrcVb9t9quY8zz8v1wCWSTpB0MrAYuKvimrqm1xv81cCbgZOBVcC3JL3lwI0RMRmYBCwHHq6kQivTDOBY0lDMOaS37G8F/ujAHZx5dh4AzgB+BWwF+oFvVlpRF/V0g4+Iv42I5yPipYi4Bfg+8N5B93kB+B/ArZJOqqJOK82Lxb9fiohnI2IX8Bc48yxJOga4G/gb4HWkYytTSMdgekJPN/ghBKAhlh8DnEDa07eGiog9pL24dj5C1Zk334nALNIY/EsR8RxwE4Ne0HPWsw1e0mRJ50s6vpg29SHSjIq7Jb1H0lsljZP0j0h7eXuAgUqLtjLcBFwu6SRJU4ArgW878/wU79B+DvzH4jk+GfgD4P8BSDpO0vHF3ScUvWCoHbzG6tkGTxqL/SywE9gFXA78XkRsAiYDtwF/DzxJmk2xqDgSb832p8AG4HFS834Y+BzOPFf/BlhEep5vBvYD/6m4bRNp2O5k0lDOi8DsCmrsGPkLP8zM8tTLe/BmZllzgzczy5QbvJlZptzgzcwyNexn0UhaA7wP2BERZ7bzS6dNmxZ9fX1jLM1Ga+PGjbsiYvpoHz/SzJ13tcaaNzjzpmk383Y+bOxm4Abg1nZX3tfXR39/f7t3t5JJ2jLGX3EzI8jceVerhLzBmTdKu5kPO0QTEd8Fdo+5ImsMZ957nHmeShuDl7Ss+MKE/p07dx5yW981dxxyfWDuPAbmzmPlZfeNfEXXTkqXHrXglgVVlwAcPW8YOvOVl903uszbkfH/CWc+Bg39f1FW5qU1+IhYFRELI2Lh9OljGg60BnDevceZN49n0ZiZZcoN3swsU8M2eEm3AT8E5hTfgHNp58uyKjnz3uPM8zTsNMmIWNKNQqw+nHnvceZ58hCNmVmm3ODNzDLlBm9mlik3eDOzTLnBm5llyg3ezCxTbvBmZplygzczy5QbvJlZptzgzcwy5QZvZpYpN3gzs0y5wZuZZcoN3swsU27wZmaZcoM3M8uUG7yZWabc4M3MMuUGb2aWKTd4M7NMucGbmWXKDd7MLFNu8GZmmXKDNzPLlBu8mVmm3ODNzDLlBm9mlik3eDOzTLnBm5llyg3ezCxTbvBmZplygzczy5QbvJlZptzgzcwy5QZvZpYpN3gzs0y5wZuZZcoN3swsU27wZmaZcoM3M8uUG7yZWabc4M3MMtVWg5e0SNImSZslXdPpoqx6zry3OO88DdvgJY0DVgKLgfnAEknzO12YVceZ9xbnna929uDPBjZHxM8i4mVgLXBhZ8uyijnz3uK8M6WIOPodpIuARRGxtLj+EeDtEbF80P2WAcuKq3OATcXP04BdZRbdBU2reXC9syNi+mh/WTuZHyXvoeqpu6bVC4fW3PG8i+XOvFojznx8G79UQyw77FUhIlYBqw57sNQfEQvbWE9tNK3mDtQ7bOZHyrtD9XRU0+qF0mse03O8A/V0XNPqhdHV3M4QzVZgVsv1mcC2kazEGseZ9xbnnal2GvwG4HRJp0qaAFwCrO9sWVYxZ95bnHemhh2iiYj9kpYDdwPjgDUR8cgI1jHkW7qaa1rNpdbbg5k3rV4oseYS8i61ni5pWr0wipqHPchqZmbN5DNZzcwy5QZvZpYpN3gzs0y5wZuZZaqdE51GRNJc0mnOJ5NOltgGrI+IgbLX1askiXR6ees2figqOGLuvLvDmfeWsvIudRaNpKuBJaTPsthaLJ5Jmle7NiJWlLayEtXpyTMcSecBNwJPAM8Ui2cCpwEfj4h7uliL8+4CZz52Tcq8zLzLbvCPA2dExG8GLZ8APBIRp5e2spLU6cnTDkkDwOKIeGrQ8lOBOyNiXhdrcd5d4MzHpmmZl5l32WPwrwJvGmL5G4vbKiNpuaR+SS9JurnlpuuBx4F5wKXA1yJiEfAe4HpJ10r6jaR9LZc3d/8veM14Du45tXoGOLbLtdQ2bwBJx0laLWmLpOclPQz8FfDuiFgMPAicC/wL0vZb2fLYOuXuzEdA0tckPSvpV8UL0i0czPw2Ut7vAHZyaOaTJd0iaUdxubaK+ikx77LH4K8EviPpCeDpYtkppFfK5Ud8VHdsAz4LnA/8Vsvy8cC9wOeBr7csb92Yfx0RH+5GkW1YA2yQtJaD23gW6S3y6i7XUue8IWX7NPBO4BfAe0mn4I+T9E5S5u8i7dl9ifQWvlVdcnfmI/MF4NKIeKk4XvB3wEmS9gF/AywFvgV8DvhEy+P+EjgB6ANOIv2dWyLipm4WT4l5l34mq6RjODjWJdIr0YaIeKXUFY2SpM8CMyPio8X1TwEXk8YUryK9ldtH2pi3A8cBp9XkiQ5A8WUMF3DoNl4fEY9WUEut8x5M0rPAi6QnzkvAzaQnz4eBM0lZP1nsvdUmd2c+OpLmkD5r5zngR8AC4FpS5v+O9AUnCyLiMUm7SEMjG4rHfrq4fk4FdZeSd+mzaCLiVdJb30aIiC9IWkfamMeRnuR/C3woIh4tnujvl7QbeBa4ISK+XFnBQBFy15/YQ2lS3pJmAFNIe3BXA28A/jnpyXM58H9J+T9ZPKQ2uTvzkZF0I/BR0rv1h0mfY3896UX9QOZLSDtxZwCPHXho668h/X/outLyjoieupCGaW4+wm1bgXMHLZtPGnMcR/qP8SywpML6JwErSP8hnysuA8WyyVVv37peSMNt9wJfKa7/K9KXJ/xjUhP4CmkMeUndcnfmo95u40jj7X9U5L8aWDHoPt8HPlr8/DXSEM7rSUNOTwIvNTnvnj/RSdIkSSskPUY6ULRO0kCxbHJEPBoR2yLilYj4AWkv4KIKS74d2EN6IZoaEVNJ48h7OfQYghWKIYWvAi8Dn5a0gnRw7XjS3t3zpG8oep7i4FbNcnfmo1Bk9z3gzcCdwAeAKyU9d+A5Dkwm5Q5wBWn47glgHemA7FAHOzuttLx7vsHTsjFJe2kXcvSNGQz9DTjd0hcR10XE9tcKitgeaf7xKRXWVUvF/OfVwAzg94H/zcEnz8SIGEeaMtcPTCQdkBtKlbk787E5j/Qu7fPAxpaG+QIwF3gEICJ2R8SHIuINEXEGqT8+VEG9peXdMw1e0nhJx5Peto2TdLyk8aQj5l8kNXSACcXP1wGnSLpQ0hQlZ5Ne5dd1/y94zRZJVxXjyUAaWy5OQHn6KI/rVV8mTYF9f0S8SPHkAfZKOrN4AZgALAT2RsQegJrl7szbJOkkSZdImihpnKTzSUNt/400XfJMSb9Peo5PBF6OiMeKx75F0tTicYtJ4/afreDPKC/vqsfJujiudS1pL6z1ci1wD7B7iNtWkMZsbyONge0jjYldUfHfMYX04vMYaU90N2l87jrgxKq3c50uwOwiy18X+e0D9heZng78hLQXt4N0gPXelsfWJndnPqJtNR14gNTAfwX8lLSHfhXpXdy7i+34ImmM/Xstj72YNJ36H4AfA+c3Pe+e/8IPSVOAa0hDMycVi39Jmi+9Ioo9ujop5vbOBB6MiH0tyxdFxF3VVVZ/TcwbnPlYNDHzsvLu+QZ/NJI+Ft0/yeGoJF1BOjljADgL+GRErCtu+1FEvK3K+pqsjnmDM++kOmZeZt5u8Ech6RcRUauDWJJ+CvyziNgnqQ/4BvDViLhe0sMR8dZKC2ywOuYNzryT6ph5mXmXfqJT00j6yZFuIo3Z1c24A2/ZIuIpSecC35A0m2pn9zRCA/MGZz4mDcy8tLx7vsGTAj6fdDCjlYAfdL+cYW2XdFZE/BigeJV/H+nzKxZUW1ojNC1vcOZj1bTMS8t72CEaSWuA9wE7IqKt03anTZsWfX19I6nDSrRx48ZdETF9tI8faebOu1pjzRucedO0m3k7e/A3AzcAt7a78r6+Pvr7+9u9u5VM0pYx/oqbGUHmzrtaJeQNzrxR2s182BOdIuK7pHmY1iOcee9x5nkq7UxWScuUvlCjf+fOnYfc1nfNHYdcH5g7j4G581h52X0jX9G1k9KlRy24pR5DrkfLG4bOfOVl940u826q4f8tZ34ENcyqLGVlXlqDj4hVEbEwIhZOnz6m4UBrAOfde5x58/TMZ9GYmfUaN3gzs0wN2+Al3Qb8EJgjaaukSztfllXJmfceZ56nYadJRsSSbhRi9eHMe48zz5OHaMzMMuUGb2aWKTd4M7NMucGbmWXKDd7MLFNu8GZmmXKDNzPLlBu8mVmm3ODNzDLlBm9mlik3eDOzTLnBm5llyg3ezCxTbvBmZplygzczy5QbvJlZptzgzcwy5QZvZpYpN3gzs0y5wZuZZcoN3swsU27wZmaZcoM3M8uUG7yZWabc4M3MMuUGb2aWKTd4M7NMucGbmWXKDd7MLFNu8GZmmXKDNzPLlBu8mVmm3ODNzDLlBm9mlik3eDOzTLnBm5llyg3ezCxTbvBmZplygzczy5QbvJlZptzgzcwy5QZvZpapthq8pEWSNknaLOmaThdl1XPmvcV552nYBi9pHLASWAzMB5ZImt/pwqw6zry3OO98tbMHfzawOSJ+FhEvA2uBCztbllXMmfcW550pRcTR7yBdBCyKiKXF9Y8Ab4+I5YPutwxYVlydA2wqfp4G7Cqz6C5oWs2D650dEdNH+8vayfwoeQ9VT7dVvf5u19DxvIvldc68k+r4t7WV+fg2fpGGWHbYq0JErAJWHfZgqT8iFraxntpoWs0dqHfYzI+Ud4fqGZGq11+XGkZgTM9xaNzfOyJN/tvaGaLZCsxquT4T2NaZcqwmnHlvcd6ZaqfBbwBOl3SqpAnAJcD6zpZlFXPmvcV5Z2rYIZqI2C9pOXA3MA5YExGPjGAdQ76lq7mm1VxqvRlkXvX6oR41tKWEvKFBf+8oNPZvG/Ygq5mZNZPPZDUzy5QbvJlZptzgzcwy5QZvZpapdk50GhFJc0mnOZ9MOlliG7A+IgbKXlcZJIl0qnZrvQ9FjY8+16nmOuRd9faoev3dVofMOymnPEudRSPpamAJ6bMsthaLZ5Lm1a6NiBWlrawEks4DbgSeAJ4pFs8ETgM+HhH3VFXbkdSp5jrkXfX2qHr93VaHzDspuzwjorQL8Dhw7BDLJwBPlLmukuodAPqGWH4qMFB1fXWvuQ55V709ql5/ty91yNx5tn8pewz+VeBNQyx/Y3Fb5SRdImlA0gvAW4C+YvnFxfLngTuAyUM8doKkxyRtHXxbF43n4J5Tq2eAY7tcSx3yrnp7VL3+bqtD5p2UVZ5lj8FfCXxH0hPA08WyU0hvb5Yf8VFdIuk9wHXAB4GHgM8BN0haB1wN/Dmwm/SJeVMlnRQRO1p+xX8GdgATu1r4odYAGySt5eA2nkV6i7y6y7XUIe+qt0fV6++2OmTeSVnlWfqZrJKO4eABCpFeDTdExCulrmgUJP0AWB0Rq1uWzQc+AXyMFO5W0udwPABcEBE/LO53KnAn8IfA/4yImV0u/zVFzRdw6DZeHxGPVlBL5XlXvT2qXn+31SHzTsopz575qILiW2teBP4rsBQ4Hvgmaa/8ZeA+0h78HcD7gRuAORHxQvH4b5NewfcAX6uywZuZtaOX5sHPII2hXQScA5wFLAS+AzwC/A6wDtgPfB34w5bm/gFgfET8nwrqPoSkSZJWFMcCnisuA8Wyw44b5K7q7VH1+q1cueXZSw3+xeLfL0XEsxGxi7QXPxv4L8BLwD8hHUD6CvBVSWdJeh3wZ8DlFdQ8lNtJ7yLOjYipETEVeBewl/TC1Guq3h5Vr9/KlVWePTNEAyDpaeAzEXFrcf0Z0kHT/wX8bkR8oOW+zwN/DNxL+rzs54qbJgCTgJ3AP42Ip7r2B6S6NkXEnJHelquqt0fV67dy5ZZnL+3BA9wEXC7pJElTgBNIjXszcE6xxz5D0vXAccBPgL8jHUU/q7gsBX5Z/Pz0EOvotC2SrpI048CCouarK6qnalVvj6rXb+XKKs9ea/B/Stobf5x0QsPtwI+BFaRmv5F0WvIfAH8SEfdExP6I2H7gQppG+WpxvYpZAx8EpgIPSNojaQ9wf7Hs4grqqdrg7bGbtD1OpDvbw3nkper/T6XqqSGaoRSfqzETeDAi9rUsXxQRd1VXWfskfTUiPlJ1HVWpW4a9nkdOJJ1DmhL602jaxxTQ4w1e0hWkOfADpCGXT0bEuuK2H0XE26qsbyiShvquzH9JmuZJRFzQ3YqqVXWGziMvkh6KiLOLn5eS/m99EzgP+FY07LN2Sv80yYb598DvRMQ+SX3ANyT1RcT1pBMc6mgm8CjwV6RPuhNp9s+fV1lUharO0HnkpfXjCP4DcF5E7JT034EHScO5jdFrY/CDjTvwlr6YDXMusFjSX1DfBr+QdKzgM8DfR8T9wIsR8UBEPFBpZdWoOkPnkZdjJE2RNJU0wrEToDgnZn+1pY1crzf47ZLOOnClaBTvA6YBCyqr6igi4tWI+EvSRyt8RtIN9PY7sUozdB7ZmUR6we4HTpT0BgBJE6nvTt8RDTsGL2kN6QmzIyLObOeXTps2Lfr6+sZenY3Kxo0bd0XE9Krr6AZJM4H9xQynwbf9bkR8v8v1/GvSORWf7uZ6rbMknQDMiIifV13LSLTT4N8B7ANubbfBL1y4MPr7+0soz0ZD0saIWFh1HWZWrWGHaCLiu6S532Zm1iCljcFLWiapX1L/zp07D7mt75o7Drk+MHceA3PnsfKy+8pafWdcO6nqCg6z4JZaHhowsxoqrcFHxKqIWBgRC6dP74nhXzOzWuv1WTRmZtlygzczy9SwDV7SbcAPgTmStkq6tPNlmZnZWA17QkZELOlGIWZmVi4P0ZiZZcoN3swsU27wZmaZcoM3M8uUG7yZWabc4M3MMuUGb2aWKTd4M7NMucGbmWXKDd7MLFNu8GZmmXKDNzPLlBu8mVmm3ODNzDLlBm9mlik3eDOzTLnBm5llyg3ezCxTbvBmZplygzczy5QbvJlZptzgzcwy5QZvZpYpN3gzs0y5wZuZZcoN3swsU27wZmaZcoM3M8uUG7yZWabc4M3MMuUGb2aWKTd4M7NMucGbmWXKDd7MLFNu8GZmmXKDNzPLlBu8mVmm3ODNzDLlBm9mlik3eDOzTLnBm5llyg3ezCxTbTV4SYskbZK0WdI1nS7KzMzGbtgGL2kcsBJYDMwHlkia3+nCzMxsbNrZgz8b2BwRP4uIl4G1wIWdLcvMzMZKEXH0O0gXAYsiYmlx/SPA2yNi+aD7LQOWFVfnAJuKn6cBu8osukR1rW2sdc2OiOllFWNmzTS+jftoiGWHvSpExCpg1WEPlvojYuEoauu4utZW17rMrFnaGaLZCsxquT4T2NaZcszMrCztNPgNwOmSTpU0AbgEWN/ZsszMbKyGHaKJiP2SlgN3A+OANRHxyAjWcdiwTY3Utba61mVmDTLsQVYzM2smn8lqZpYpN3gzs0y5wZuZZcoN3swsU+2c6DQikuaSPsrgZNIJUduA9RExUPa6RkqSSB+90FrbQ+EjzWaWoVJn0Ui6GlhC+ryarcXimaS582sjYkVpKxt5becBNwJPAM+01HYa8PGIuKeq2szMOqHsBv84cEZE/GbQ8gnAIxFxemkrGyFJA8DiiHhq0PJTgTsjYl4lhR2s43zg9zj03cW6iLiryrrMrLnKHqJ5FXgTsGXQ8jcWt1VpPAffVbR6Bji2y7UcQtIXgd8GbuXQdz5XSFocEZ+srDgza6yyG/yVwHckPQE8XSw7hTQMsvyIj+qONcAGSWs5WNss0vDR6sqqSt4bEb89eKGkvwYeB9zgzWzESj+TVdIxHDyQKdIe6YaIeKXUFY1C8UUlF3Bobesj4tGK6/oJsDQiHhq0/GxgdUQsqKYyM2syf1RBDUh6G/Bl4PUcHKKZBfyKdAB4Y1W1mVlz9UyDlzQJ+BTpQOaBL8PYAawDVkTE3qpqO0DSG2h5dxER2ysuycwarJdOdLod2AOcGxFTI2Iq8C5gL/D1SivjtTn6s4vLLGB2sczMbFR6aQ9+U0TMGelt3eA5+mbWCaWfyVpjWyRdBdwSEb8EkDQD+CgHZ9VU5Xrg3Ueaow9UOkffzJqpl4ZoPghMBR6QtEfSbuB+4ETg4ioLo8Zz9M2suXpmiGYwSeeQpnP+tOohEEmfIr3IDDVH//aI+EJVtZlZc/VMg5f0UEScXfy8FPgE8E3gPOBbVX5OTlFTLefom1lz9VKDfzgi3lr8vIF09uhOSa8DHvTJRGaWm14agz9G0hRJU0kvbDsBIuIFYH+VhUmaJGmFpMckPVdcBoplk6uszcyaq5ca/CRgI9APnFicVISkiaQhkSrVeo6+mTVTzwzRHImkE4AZEfHzCmuo7Rx9M2uuXtqDH1JE/EOVzb2wRdJVxbx8IM3RL75Apeo5+mbWUD3f4GuidY7+7kFz9P9tlYWZWXP1/BBN3Un6WETcVHUdZtY8bvA1J+kXEXFK1XWYWfP00mfR1FbxhR9D3gTMOMJtZmZH5QZfDzOA80lTJVsJ+EH3yzGzHLjB18O3gYkR8ePBN0i6v/vlmFkOPAZvZpYpT5M0M8uUG7yZWabc4M3MMuUGb2aWqf8Pelvl1D6SjH4AAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 9 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Inspection graphique des données\n",
"Les vols où aucun incident n'est relevé n'apportant aucun information\n",
"sur l'influence de la température ou de la pression sur les\n",
"dysfonctionnements, nous nous concentrons sur les expériences où au\n",
"moins un joint a été défectueux.\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"#data = data[data.Malfunction>0]\n",
"#data"
]
},
{
......@@ -448,12 +477,12 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
......@@ -705,7 +734,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
"version": "3.6.4"
}
},
"nbformat": 4,
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment