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parent a14563bb
{
"cells": [],
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# <center>Incidence du syndrome grippal"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import isoweek"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nous recuperons les données sur le site via le site en pointant sur un fichier au format .csv Pour la lecture des données ...."
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>202052</td>\n",
" <td>3</td>\n",
" <td>18546</td>\n",
" <td>13789.0</td>\n",
" <td>23303.0</td>\n",
" <td>28</td>\n",
" <td>21.0</td>\n",
" <td>35.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>202051</td>\n",
" <td>3</td>\n",
" <td>21032</td>\n",
" <td>16856.0</td>\n",
" <td>25208.0</td>\n",
" <td>32</td>\n",
" <td>26.0</td>\n",
" <td>38.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>202050</td>\n",
" <td>3</td>\n",
" <td>16845</td>\n",
" <td>13220.0</td>\n",
" <td>20470.0</td>\n",
" <td>26</td>\n",
" <td>20.0</td>\n",
" <td>32.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>202049</td>\n",
" <td>3</td>\n",
" <td>12939</td>\n",
" <td>9923.0</td>\n",
" <td>15955.0</td>\n",
" <td>20</td>\n",
" <td>15.0</td>\n",
" <td>25.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>202048</td>\n",
" <td>3</td>\n",
" <td>13804</td>\n",
" <td>10641.0</td>\n",
" <td>16967.0</td>\n",
" <td>21</td>\n",
" <td>16.0</td>\n",
" <td>26.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
"0 202052 3 18546 13789.0 23303.0 28 21.0 35.0 \n",
"1 202051 3 21032 16856.0 25208.0 32 26.0 38.0 \n",
"2 202050 3 16845 13220.0 20470.0 26 20.0 32.0 \n",
"3 202049 3 12939 9923.0 15955.0 20 15.0 25.0 \n",
"4 202048 3 13804 10641.0 16967.0 21 16.0 26.0 \n",
"\n",
" geo_insee geo_name \n",
"0 FR France \n",
"1 FR France \n",
"2 FR France \n",
"3 FR France \n",
"4 FR France "
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"\n",
"raw_data = pd.read_csv(data_url, skiprows=1)\n",
"raw_data.head()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1882</th>\n",
" <td>198448</td>\n",
" <td>3</td>\n",
" <td>78620</td>\n",
" <td>60634.0</td>\n",
" <td>96606.0</td>\n",
" <td>143</td>\n",
" <td>110.0</td>\n",
" <td>176.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1883</th>\n",
" <td>198447</td>\n",
" <td>3</td>\n",
" <td>72029</td>\n",
" <td>54274.0</td>\n",
" <td>89784.0</td>\n",
" <td>131</td>\n",
" <td>99.0</td>\n",
" <td>163.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1884</th>\n",
" <td>198446</td>\n",
" <td>3</td>\n",
" <td>87330</td>\n",
" <td>67686.0</td>\n",
" <td>106974.0</td>\n",
" <td>159</td>\n",
" <td>123.0</td>\n",
" <td>195.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1885</th>\n",
" <td>198445</td>\n",
" <td>3</td>\n",
" <td>135223</td>\n",
" <td>101414.0</td>\n",
" <td>169032.0</td>\n",
" <td>246</td>\n",
" <td>184.0</td>\n",
" <td>308.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1886</th>\n",
" <td>198444</td>\n",
" <td>3</td>\n",
" <td>68422</td>\n",
" <td>20056.0</td>\n",
" <td>116788.0</td>\n",
" <td>125</td>\n",
" <td>37.0</td>\n",
" <td>213.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"1882 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"1883 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"1884 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"1885 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"1886 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"1882 176.0 FR France \n",
"1883 163.0 FR France \n",
"1884 195.0 FR France \n",
"1885 308.0 FR France \n",
"1886 213.0 FR France "
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_data.tail()\n",
"#raw_data.columns"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On fait une recherche de donnée manquante dans la dataframe.On visuallise les lignes de donnée manquantes"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1650</th>\n",
" <td>198919</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
"1650 198919 3 0 NaN NaN 0 NaN NaN \n",
"\n",
" geo_insee geo_name \n",
"1650 FR France "
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_data[raw_data.isnull().any(axis=1)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nous travaillerons sur une dataframe dont les lignes manquantes seront supprimées, nous testons que sur cette nouvelle dataframe il y a bien aucun elements manquant sur une ligne;"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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"\n",
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" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>202052</td>\n",
" <td>3</td>\n",
" <td>18546</td>\n",
" <td>13789.0</td>\n",
" <td>23303.0</td>\n",
" <td>28</td>\n",
" <td>21.0</td>\n",
" <td>35.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>202051</td>\n",
" <td>3</td>\n",
" <td>21032</td>\n",
" <td>16856.0</td>\n",
" <td>25208.0</td>\n",
" <td>32</td>\n",
" <td>26.0</td>\n",
" <td>38.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>202050</td>\n",
" <td>3</td>\n",
" <td>16845</td>\n",
" <td>13220.0</td>\n",
" <td>20470.0</td>\n",
" <td>26</td>\n",
" <td>20.0</td>\n",
" <td>32.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>202049</td>\n",
" <td>3</td>\n",
" <td>12939</td>\n",
" <td>9923.0</td>\n",
" <td>15955.0</td>\n",
" <td>20</td>\n",
" <td>15.0</td>\n",
" <td>25.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>202048</td>\n",
" <td>3</td>\n",
" <td>13804</td>\n",
" <td>10641.0</td>\n",
" <td>16967.0</td>\n",
" <td>21</td>\n",
" <td>16.0</td>\n",
" <td>26.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
"0 202052 3 18546 13789.0 23303.0 28 21.0 35.0 \n",
"1 202051 3 21032 16856.0 25208.0 32 26.0 38.0 \n",
"2 202050 3 16845 13220.0 20470.0 26 20.0 32.0 \n",
"3 202049 3 12939 9923.0 15955.0 20 15.0 25.0 \n",
"4 202048 3 13804 10641.0 16967.0 21 16.0 26.0 \n",
"\n",
" geo_insee geo_name \n",
"0 FR France \n",
"1 FR France \n",
"2 FR France \n",
"3 FR France \n",
"4 FR France "
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = raw_data.dropna().copy()\n",
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" }\n",
"\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Empty DataFrame\n",
"Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n",
"Index: []"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data[data.isnull().any(axis=1)]"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"year_and_week_int = 198501\n",
"year_and_week_str = str(year_and_week_int)\n",
"year = int(year_and_week_str[:4])\n",
"week = int(year_and_week_str[4:6])\n",
"\n",
"w = isoweek.Week(year,week)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Premeière jour de cette semaine 1985 01"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1984-12-31\n"
]
}
],
"source": [
"print(w.day(0))"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Period('1984-12-31/1985-01-06', 'W-SUN')"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.Period(w.day(0),'W')"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [],
"source": [
"def convert_week(year_and_week_int):\n",
" year_and_week_str = str(year_and_week_int)\n",
" year = int(year_and_week_str[:4])\n",
" week = int(year_and_week_str[4:6])\n",
" w = isoweek.Week(year,week)\n",
" return pd.Period(w.day(0),'W')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On ajoute une nouvelle colonne dans notre jeux de données, cette collonne represente une pérriode.\n",
"On aura notre jeux de données en ordre inverse, nous lui appliquons une fonction de trie pour obtenir un ordre chronologique. "
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" <th>period</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>202052</td>\n",
" <td>3</td>\n",
" <td>18546</td>\n",
" <td>13789.0</td>\n",
" <td>23303.0</td>\n",
" <td>28</td>\n",
" <td>21.0</td>\n",
" <td>35.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>2020-12-21/2020-12-27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>202051</td>\n",
" <td>3</td>\n",
" <td>21032</td>\n",
" <td>16856.0</td>\n",
" <td>25208.0</td>\n",
" <td>32</td>\n",
" <td>26.0</td>\n",
" <td>38.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>2020-12-14/2020-12-20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>202050</td>\n",
" <td>3</td>\n",
" <td>16845</td>\n",
" <td>13220.0</td>\n",
" <td>20470.0</td>\n",
" <td>26</td>\n",
" <td>20.0</td>\n",
" <td>32.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>2020-12-07/2020-12-13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>202049</td>\n",
" <td>3</td>\n",
" <td>12939</td>\n",
" <td>9923.0</td>\n",
" <td>15955.0</td>\n",
" <td>20</td>\n",
" <td>15.0</td>\n",
" <td>25.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>2020-11-30/2020-12-06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>202048</td>\n",
" <td>3</td>\n",
" <td>13804</td>\n",
" <td>10641.0</td>\n",
" <td>16967.0</td>\n",
" <td>21</td>\n",
" <td>16.0</td>\n",
" <td>26.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" <td>2020-11-23/2020-11-29</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
"0 202052 3 18546 13789.0 23303.0 28 21.0 35.0 \n",
"1 202051 3 21032 16856.0 25208.0 32 26.0 38.0 \n",
"2 202050 3 16845 13220.0 20470.0 26 20.0 32.0 \n",
"3 202049 3 12939 9923.0 15955.0 20 15.0 25.0 \n",
"4 202048 3 13804 10641.0 16967.0 21 16.0 26.0 \n",
"\n",
" geo_insee geo_name period \n",
"0 FR France 2020-12-21/2020-12-27 \n",
"1 FR France 2020-12-14/2020-12-20 \n",
"2 FR France 2020-12-07/2020-12-13 \n",
"3 FR France 2020-11-30/2020-12-06 \n",
"4 FR France 2020-11-23/2020-11-29 "
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data['period'] = [convert_week(yw) for yw in data['week']]\n",
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"sorted_data = data.set_index('period').sort_index()"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
" <tr>\n",
" <th>period</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1984-10-29/1984-11-04</th>\n",
" <td>198444</td>\n",
" <td>3</td>\n",
" <td>68422</td>\n",
" <td>20056.0</td>\n",
" <td>116788.0</td>\n",
" <td>125</td>\n",
" <td>37.0</td>\n",
" <td>213.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1984-11-05/1984-11-11</th>\n",
" <td>198445</td>\n",
" <td>3</td>\n",
" <td>135223</td>\n",
" <td>101414.0</td>\n",
" <td>169032.0</td>\n",
" <td>246</td>\n",
" <td>184.0</td>\n",
" <td>308.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1984-11-12/1984-11-18</th>\n",
" <td>198446</td>\n",
" <td>3</td>\n",
" <td>87330</td>\n",
" <td>67686.0</td>\n",
" <td>106974.0</td>\n",
" <td>159</td>\n",
" <td>123.0</td>\n",
" <td>195.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1984-11-19/1984-11-25</th>\n",
" <td>198447</td>\n",
" <td>3</td>\n",
" <td>72029</td>\n",
" <td>54274.0</td>\n",
" <td>89784.0</td>\n",
" <td>131</td>\n",
" <td>99.0</td>\n",
" <td>163.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1984-11-26/1984-12-02</th>\n",
" <td>198448</td>\n",
" <td>3</td>\n",
" <td>78620</td>\n",
" <td>60634.0</td>\n",
" <td>96606.0</td>\n",
" <td>143</td>\n",
" <td>110.0</td>\n",
" <td>176.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 \\\n",
"period \n",
"1984-10-29/1984-11-04 198444 3 68422 20056.0 116788.0 125 \n",
"1984-11-05/1984-11-11 198445 3 135223 101414.0 169032.0 246 \n",
"1984-11-12/1984-11-18 198446 3 87330 67686.0 106974.0 159 \n",
"1984-11-19/1984-11-25 198447 3 72029 54274.0 89784.0 131 \n",
"1984-11-26/1984-12-02 198448 3 78620 60634.0 96606.0 143 \n",
"\n",
" inc100_low inc100_up geo_insee geo_name \n",
"period \n",
"1984-10-29/1984-11-04 37.0 213.0 FR France \n",
"1984-11-05/1984-11-11 184.0 308.0 FR France \n",
"1984-11-12/1984-11-18 123.0 195.0 FR France \n",
"1984-11-19/1984-11-25 99.0 163.0 FR France \n",
"1984-11-26/1984-12-02 110.0 176.0 FR France "
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sorted_data.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
......@@ -16,10 +975,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
"version": "3.6.4"
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