{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#
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": [
"\n",
"\n",
"
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" \n",
" \n",
" week \n",
" indicator \n",
" inc \n",
" inc_low \n",
" inc_up \n",
" inc100 \n",
" inc100_low \n",
" inc100_up \n",
" geo_insee \n",
" geo_name \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 202052 \n",
" 3 \n",
" 18546 \n",
" 13789.0 \n",
" 23303.0 \n",
" 28 \n",
" 21.0 \n",
" 35.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1 \n",
" 202051 \n",
" 3 \n",
" 21032 \n",
" 16856.0 \n",
" 25208.0 \n",
" 32 \n",
" 26.0 \n",
" 38.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 2 \n",
" 202050 \n",
" 3 \n",
" 16845 \n",
" 13220.0 \n",
" 20470.0 \n",
" 26 \n",
" 20.0 \n",
" 32.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 3 \n",
" 202049 \n",
" 3 \n",
" 12939 \n",
" 9923.0 \n",
" 15955.0 \n",
" 20 \n",
" 15.0 \n",
" 25.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 4 \n",
" 202048 \n",
" 3 \n",
" 13804 \n",
" 10641.0 \n",
" 16967.0 \n",
" 21 \n",
" 16.0 \n",
" 26.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
"
\n",
"
"
],
"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": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" \n",
" week \n",
" indicator \n",
" inc \n",
" inc_low \n",
" inc_up \n",
" inc100 \n",
" inc100_low \n",
" inc100_up \n",
" geo_insee \n",
" geo_name \n",
" \n",
" \n",
" \n",
" \n",
" 1882 \n",
" 198448 \n",
" 3 \n",
" 78620 \n",
" 60634.0 \n",
" 96606.0 \n",
" 143 \n",
" 110.0 \n",
" 176.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1883 \n",
" 198447 \n",
" 3 \n",
" 72029 \n",
" 54274.0 \n",
" 89784.0 \n",
" 131 \n",
" 99.0 \n",
" 163.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1884 \n",
" 198446 \n",
" 3 \n",
" 87330 \n",
" 67686.0 \n",
" 106974.0 \n",
" 159 \n",
" 123.0 \n",
" 195.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1885 \n",
" 198445 \n",
" 3 \n",
" 135223 \n",
" 101414.0 \n",
" 169032.0 \n",
" 246 \n",
" 184.0 \n",
" 308.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1886 \n",
" 198444 \n",
" 3 \n",
" 68422 \n",
" 20056.0 \n",
" 116788.0 \n",
" 125 \n",
" 37.0 \n",
" 213.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
"
\n",
"
"
],
"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": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" \n",
" week \n",
" indicator \n",
" inc \n",
" inc_low \n",
" inc_up \n",
" inc100 \n",
" inc100_low \n",
" inc100_up \n",
" geo_insee \n",
" geo_name \n",
" \n",
" \n",
" \n",
" \n",
" 1650 \n",
" 198919 \n",
" 3 \n",
" 0 \n",
" NaN \n",
" NaN \n",
" 0 \n",
" NaN \n",
" NaN \n",
" FR \n",
" France \n",
" \n",
" \n",
"
\n",
"
"
],
"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": [
"\n",
"\n",
"
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" \n",
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" week \n",
" indicator \n",
" inc \n",
" inc_low \n",
" inc_up \n",
" inc100 \n",
" inc100_low \n",
" inc100_up \n",
" geo_insee \n",
" geo_name \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 202052 \n",
" 3 \n",
" 18546 \n",
" 13789.0 \n",
" 23303.0 \n",
" 28 \n",
" 21.0 \n",
" 35.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1 \n",
" 202051 \n",
" 3 \n",
" 21032 \n",
" 16856.0 \n",
" 25208.0 \n",
" 32 \n",
" 26.0 \n",
" 38.0 \n",
" FR \n",
" France \n",
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" 202050 \n",
" 3 \n",
" 16845 \n",
" 13220.0 \n",
" 20470.0 \n",
" 26 \n",
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" 32.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 3 \n",
" 202049 \n",
" 3 \n",
" 12939 \n",
" 9923.0 \n",
" 15955.0 \n",
" 20 \n",
" 15.0 \n",
" 25.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 4 \n",
" 202048 \n",
" 3 \n",
" 13804 \n",
" 10641.0 \n",
" 16967.0 \n",
" 21 \n",
" 16.0 \n",
" 26.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
"
\n",
"
"
],
"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": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" \n",
" week \n",
" indicator \n",
" inc \n",
" inc_low \n",
" inc_up \n",
" inc100 \n",
" inc100_low \n",
" inc100_up \n",
" geo_insee \n",
" geo_name \n",
" \n",
" \n",
" \n",
" \n",
"
\n",
"
"
],
"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": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" \n",
" week \n",
" indicator \n",
" inc \n",
" inc_low \n",
" inc_up \n",
" inc100 \n",
" inc100_low \n",
" inc100_up \n",
" geo_insee \n",
" geo_name \n",
" period \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" 202052 \n",
" 3 \n",
" 18546 \n",
" 13789.0 \n",
" 23303.0 \n",
" 28 \n",
" 21.0 \n",
" 35.0 \n",
" FR \n",
" France \n",
" 2020-12-21/2020-12-27 \n",
" \n",
" \n",
" 1 \n",
" 202051 \n",
" 3 \n",
" 21032 \n",
" 16856.0 \n",
" 25208.0 \n",
" 32 \n",
" 26.0 \n",
" 38.0 \n",
" FR \n",
" France \n",
" 2020-12-14/2020-12-20 \n",
" \n",
" \n",
" 2 \n",
" 202050 \n",
" 3 \n",
" 16845 \n",
" 13220.0 \n",
" 20470.0 \n",
" 26 \n",
" 20.0 \n",
" 32.0 \n",
" FR \n",
" France \n",
" 2020-12-07/2020-12-13 \n",
" \n",
" \n",
" 3 \n",
" 202049 \n",
" 3 \n",
" 12939 \n",
" 9923.0 \n",
" 15955.0 \n",
" 20 \n",
" 15.0 \n",
" 25.0 \n",
" FR \n",
" France \n",
" 2020-11-30/2020-12-06 \n",
" \n",
" \n",
" 4 \n",
" 202048 \n",
" 3 \n",
" 13804 \n",
" 10641.0 \n",
" 16967.0 \n",
" 21 \n",
" 16.0 \n",
" 26.0 \n",
" FR \n",
" France \n",
" 2020-11-23/2020-11-29 \n",
" \n",
" \n",
"
\n",
"
"
],
"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": [
"\n",
"\n",
"
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" \n",
" \n",
" \n",
" week \n",
" indicator \n",
" inc \n",
" inc_low \n",
" inc_up \n",
" inc100 \n",
" inc100_low \n",
" inc100_up \n",
" geo_insee \n",
" geo_name \n",
" \n",
" \n",
" period \n",
" \n",
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" 1984-10-29/1984-11-04 \n",
" 198444 \n",
" 3 \n",
" 68422 \n",
" 20056.0 \n",
" 116788.0 \n",
" 125 \n",
" 37.0 \n",
" 213.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1984-11-05/1984-11-11 \n",
" 198445 \n",
" 3 \n",
" 135223 \n",
" 101414.0 \n",
" 169032.0 \n",
" 246 \n",
" 184.0 \n",
" 308.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1984-11-12/1984-11-18 \n",
" 198446 \n",
" 3 \n",
" 87330 \n",
" 67686.0 \n",
" 106974.0 \n",
" 159 \n",
" 123.0 \n",
" 195.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1984-11-19/1984-11-25 \n",
" 198447 \n",
" 3 \n",
" 72029 \n",
" 54274.0 \n",
" 89784.0 \n",
" 131 \n",
" 99.0 \n",
" 163.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
" 1984-11-26/1984-12-02 \n",
" 198448 \n",
" 3 \n",
" 78620 \n",
" 60634.0 \n",
" 96606.0 \n",
" 143 \n",
" 110.0 \n",
" 176.0 \n",
" FR \n",
" France \n",
" \n",
" \n",
"
\n",
"
"
],
"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": "markdown",
"metadata": {},
"source": [
"Verification des données (cohérence des données).\n",
"Vérification que chaque période se suivent consecutivement dans un ordre chronologique."
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"PeriodIndex(['1984-10-29/1984-11-04', '1984-11-05/1984-11-11',\n",
" '1984-11-12/1984-11-18', '1984-11-19/1984-11-25',\n",
" '1984-11-26/1984-12-02', '1984-12-03/1984-12-09',\n",
" '1984-12-10/1984-12-16', '1984-12-17/1984-12-23',\n",
" '1984-12-24/1984-12-30', '1984-12-31/1985-01-06',\n",
" ...\n",
" '2020-10-19/2020-10-25', '2020-10-26/2020-11-01',\n",
" '2020-11-02/2020-11-08', '2020-11-09/2020-11-15',\n",
" '2020-11-16/2020-11-22', '2020-11-23/2020-11-29',\n",
" '2020-11-30/2020-12-06', '2020-12-07/2020-12-13',\n",
" '2020-12-14/2020-12-20', '2020-12-21/2020-12-27'],\n",
" dtype='period[W-SUN]', name='period', length=1886, freq='W-SUN')"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"periods = sorted_data.index\n",
"periods"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1984-10-29/1984-11-04 1984-11-05/1984-11-11\n",
"1984-11-05/1984-11-11 1984-11-12/1984-11-18\n",
"1984-11-12/1984-11-18 1984-11-19/1984-11-25\n",
"1984-11-19/1984-11-25 1984-11-26/1984-12-02\n",
"1984-11-26/1984-12-02 1984-12-03/1984-12-09\n",
"\n",
"1989-05-01/1989-05-07 1989-05-15/1989-05-21\n"
]
}
],
"source": [
"periods = sorted_data.index\n",
"i = 0\n",
"for p1, p2 in zip(periods[0:],periods[1:]):\n",
" if i < 5 :\n",
" print(p1, p2)\n",
" i = i + 1\n",
" delta = p2.to_timestamp() - p1.end_time\n",
" if delta > pd.Timedelta('1s'):\n",
" print()\n",
" print(p1,p2)\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nous retrouvons bien la semaine manquante dans le jeux de données (celle que nous avons supprimée)"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sorted_data['inc'].plot(figsize=(15, 8)).grid(linestyle='-', linewidth=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sorted_data['inc'][-200:].plot(figsize=(15, 8)).grid(linestyle='-', linewidth=0.5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}