diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb index eb06461fc9c562952b5d5dd540da20c292cba3b0..785007e037b2c119016392d60030fd0491b2d214 100644 --- a/module3/exo3/exercice.ipynb +++ b/module3/exo3/exercice.ipynb @@ -45,7 +45,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -59,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -69,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -1849,7 +1849,7 @@ "[266 rows x 132 columns]" ] }, - "execution_count": 19, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -1893,7 +1893,8 @@ "Cependant, nous ne sommes pas dépendant de ces données, seul les données relatives au pays suivant nous intéresse. \n", "\n", "* Belgique \n", - "* Chine - toutes les provinces sauf Hong-Kong (China), Hong Kong (China, Hong-Kong)\n", + "* Chine - toutes les provinces sauf Hong-Kong (China),\n", + "* Hong Kong \n", "* France métropolitaine\n", "* Allemagne\n", "* Iran\n", @@ -1915,7 +1916,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -2005,7 +2006,7 @@ "[1 rows x 132 columns]" ] }, - "execution_count": 34, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -2020,7 +2021,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -2137,7 +2138,7 @@ "[2 rows x 132 columns]" ] }, - "execution_count": 35, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -2157,6 +2158,1438 @@ "source": [ "Les mêmes étapes sont utilisées pour le reste des pays manquants, sauf pour la Chine qui nécessite une opération spécial. (Voir ci-dessous)" ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Province/StateCountry/RegionLatLong1/22/201/23/201/24/201/25/201/26/201/27/20...5/19/205/20/205/21/205/22/205/23/205/24/205/25/205/26/205/27/205/28/20
23NaNBelgium50.83334.0000000000...55791559835623556511568105709257342574555759257849
116NaNFrance46.22762.2137002333...178428179069179306179645179964179859180166179887180044183309
120NaNGermany51.00009.0000000001...177778178473179021179710179986180328180600181200181524182196
133NaNIran32.000053.0000000000...124603126949129341131652133521135701137724139511141591143849
137NaNItaly43.000012.0000000000...226699227364228006228658229327229858230158230555231139231732
139NaNJapan36.0000138.0000222244...16367163671642416513165361655016581166231665116598
143NaNKorea, South36.0000128.0000112234...11110111221114211165111901120611225112651134411402
169NaNNetherlands52.13265.2913000000...44249444474470044888450644523645445455784576845950
184NaNPortugal39.3999-8.2245000000...29432296602991230200304713062330788310073129231596
201NaNSpain40.0000-4.0000000000...232037232555233037234824235290235772235400236259236259237906
223NaNUnited Kingdom55.3781-3.4360000000...248818248293250908254195257154259559261184265227267240269127
225NaNUS37.0902-95.7129112255...1528568155185315771471600937162261216432461662302168091316991761721753
\n", + "

12 rows × 132 columns

\n", + "
" + ], + "text/plain": [ + " Province/State Country/Region Lat Long 1/22/20 1/23/20 \\\n", + "23 NaN Belgium 50.8333 4.0000 0 0 \n", + "116 NaN France 46.2276 2.2137 0 0 \n", + "120 NaN Germany 51.0000 9.0000 0 0 \n", + "133 NaN Iran 32.0000 53.0000 0 0 \n", + "137 NaN Italy 43.0000 12.0000 0 0 \n", + "139 NaN Japan 36.0000 138.0000 2 2 \n", + "143 NaN Korea, South 36.0000 128.0000 1 1 \n", + "169 NaN Netherlands 52.1326 5.2913 0 0 \n", + "184 NaN Portugal 39.3999 -8.2245 0 0 \n", + "201 NaN Spain 40.0000 -4.0000 0 0 \n", + "223 NaN United Kingdom 55.3781 -3.4360 0 0 \n", + "225 NaN US 37.0902 -95.7129 1 1 \n", + "\n", + " 1/24/20 1/25/20 1/26/20 1/27/20 ... 5/19/20 5/20/20 5/21/20 \\\n", + "23 0 0 0 0 ... 55791 55983 56235 \n", + "116 2 3 3 3 ... 178428 179069 179306 \n", + "120 0 0 0 1 ... 177778 178473 179021 \n", + "133 0 0 0 0 ... 124603 126949 129341 \n", + "137 0 0 0 0 ... 226699 227364 228006 \n", + "139 2 2 4 4 ... 16367 16367 16424 \n", + "143 2 2 3 4 ... 11110 11122 11142 \n", + "169 0 0 0 0 ... 44249 44447 44700 \n", + "184 0 0 0 0 ... 29432 29660 29912 \n", + "201 0 0 0 0 ... 232037 232555 233037 \n", + "223 0 0 0 0 ... 248818 248293 250908 \n", + "225 2 2 5 5 ... 1528568 1551853 1577147 \n", + "\n", + " 5/22/20 5/23/20 5/24/20 5/25/20 5/26/20 5/27/20 5/28/20 \n", + "23 56511 56810 57092 57342 57455 57592 57849 \n", + "116 179645 179964 179859 180166 179887 180044 183309 \n", + "120 179710 179986 180328 180600 181200 181524 182196 \n", + "133 131652 133521 135701 137724 139511 141591 143849 \n", + "137 228658 229327 229858 230158 230555 231139 231732 \n", + "139 16513 16536 16550 16581 16623 16651 16598 \n", + "143 11165 11190 11206 11225 11265 11344 11402 \n", + "169 44888 45064 45236 45445 45578 45768 45950 \n", + "184 30200 30471 30623 30788 31007 31292 31596 \n", + "201 234824 235290 235772 235400 236259 236259 237906 \n", + "223 254195 257154 259559 261184 265227 267240 269127 \n", + "225 1600937 1622612 1643246 1662302 1680913 1699176 1721753 \n", + "\n", + "[12 rows x 132 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "countries_list= list(['China, Hong-Kong', 'Germany', 'Iran', 'Italy', 'Japan', 'Korea, South', 'Netherlands', 'Portugal', 'Spain', 'United Kingdom', 'US'])\n", + "#print(countries_list)\n", + "\n", + "for country in countries_list : \n", + " dataCountries = dataCountries.append(raw_data.loc[(raw_data['Country/Region'] == country) & (raw_data['Province/State'].isnull())])\n", + "\n", + "dataCountries" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "TODO explain" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Province/StateCountry/RegionLatLong1/22/201/23/201/24/201/25/201/26/201/27/20...5/19/205/20/205/21/205/22/205/23/205/24/205/25/205/26/205/27/205/28/20
49AnhuiChina31.8257117.22641.09.015.039.060.070.0...991.0991.0991.0991.0991.0991.0991.0991.0991.0991.0
50BeijingChina40.1824116.414214.022.036.041.068.080.0...593.0593.0593.0593.0593.0593.0593.0593.0593.0593.0
51ChongqingChina30.0572107.87406.09.027.057.075.0110.0...579.0579.0579.0579.0579.0579.0579.0579.0579.0579.0
52FujianChina26.0789117.98741.05.010.018.035.059.0...356.0356.0356.0356.0356.0356.0357.0357.0358.0358.0
53GansuChina37.8099101.05830.02.02.04.07.014.0...139.0139.0139.0139.0139.0139.0139.0139.0139.0139.0
54GuangdongChina23.3417113.424426.032.053.078.0111.0151.0...1590.01590.01590.01591.01592.01592.01592.01592.01592.01592.0
55GuangxiChina23.8298108.78812.05.023.023.036.046.0...254.0254.0254.0254.0254.0254.0254.0254.0254.0254.0
56GuizhouChina26.8154106.87481.03.03.04.05.07.0...147.0147.0147.0147.0147.0147.0147.0147.0147.0147.0
57HainanChina19.1959109.74534.05.08.019.022.033.0...169.0169.0169.0169.0169.0169.0169.0169.0169.0169.0
58HebeiChina39.5490116.13061.01.02.08.013.018.0...328.0328.0328.0328.0328.0328.0328.0328.0328.0328.0
59HeilongjiangChina47.8620127.76150.02.04.09.015.021.0...945.0945.0945.0945.0945.0945.0945.0945.0945.0945.0
60HenanChina33.8820113.61405.05.09.032.083.0128.0...1276.01276.01276.01276.01276.01276.01276.01276.01276.01276.0
61Hong KongChina22.3000114.20000.02.02.05.08.08.0...1055.01055.01055.01065.01065.01065.01065.01065.01066.01066.0
62HubeiChina30.9756112.2707444.0444.0549.0761.01058.01423.0...68135.068135.068135.068135.068135.068135.068135.068135.068135.068135.0
63HunanChina27.6104111.70884.09.024.043.069.0100.0...1019.01019.01019.01019.01019.01019.01019.01019.01019.01019.0
64Inner MongoliaChina44.0935113.94480.00.01.07.07.011.0...216.0216.0216.0217.0217.0227.0232.0232.0232.0232.0
65JiangsuChina32.9711119.45501.05.09.018.033.047.0...653.0653.0653.0653.0653.0653.0653.0653.0653.0653.0
66JiangxiChina27.6140115.72212.07.018.018.036.072.0...937.0937.0937.0937.0937.0937.0937.0937.0937.0937.0
67JilinChina43.6661126.19230.01.03.04.04.06.0...151.0151.0151.0154.0155.0155.0155.0155.0155.0155.0
68LiaoningChina41.2956122.60852.03.04.017.021.027.0...149.0149.0149.0149.0149.0149.0149.0149.0149.0149.0
69MacauChina22.1667113.55001.02.02.02.05.06.0...45.045.045.045.045.045.045.045.045.045.0
70NingxiaChina37.2692106.16551.01.02.03.04.07.0...75.075.075.075.075.075.075.075.075.075.0
71QinghaiChina35.745295.99560.00.00.01.01.06.0...18.018.018.018.018.018.018.018.018.018.0
72ShaanxiChina35.1917108.87010.03.05.015.022.035.0...308.0308.0308.0308.0308.0308.0308.0308.0308.0308.0
73ShandongChina36.3427118.14982.06.015.027.046.075.0...788.0788.0788.0788.0788.0788.0788.0788.0788.0788.0
74ShanghaiChina31.2020121.44919.016.020.033.040.053.0...666.0666.0666.0667.0668.0668.0669.0670.0671.0671.0
75ShanxiChina37.5777112.29221.01.01.06.09.013.0...198.0198.0198.0198.0198.0198.0198.0198.0198.0198.0
76SichuanChina30.6171102.71035.08.015.028.044.069.0...561.0561.0561.0563.0563.0564.0564.0564.0564.0564.0
77TianjinChina39.3054117.32304.04.08.010.014.023.0...192.0192.0192.0192.0192.0192.0192.0192.0192.0192.0
78TibetChina31.692788.09240.00.00.00.00.00.0...1.01.01.01.01.01.01.01.01.01.0
79XinjiangChina41.112985.24010.02.02.03.04.05.0...76.076.076.076.076.076.076.076.076.076.0
80YunnanChina24.9740101.48701.02.05.011.016.026.0...185.0185.0185.0185.0185.0185.0185.0185.0185.0185.0
81ZhejiangChina29.1832120.093410.027.043.062.0104.0128.0...1268.01268.01268.01268.01268.01268.01268.01268.01268.01268.0
1NaNChinaNaNNaN548.0643.0920.01406.02075.02877.0...84063.084063.084063.084081.084084.084095.084102.084103.084106.084106.0
\n", + "

34 rows × 132 columns

\n", + "
" + ], + "text/plain": [ + " Province/State Country/Region Lat Long 1/22/20 1/23/20 \\\n", + "49 Anhui China 31.8257 117.2264 1.0 9.0 \n", + "50 Beijing China 40.1824 116.4142 14.0 22.0 \n", + "51 Chongqing China 30.0572 107.8740 6.0 9.0 \n", + "52 Fujian China 26.0789 117.9874 1.0 5.0 \n", + "53 Gansu China 37.8099 101.0583 0.0 2.0 \n", + "54 Guangdong China 23.3417 113.4244 26.0 32.0 \n", + "55 Guangxi China 23.8298 108.7881 2.0 5.0 \n", + "56 Guizhou China 26.8154 106.8748 1.0 3.0 \n", + "57 Hainan China 19.1959 109.7453 4.0 5.0 \n", + "58 Hebei China 39.5490 116.1306 1.0 1.0 \n", + "59 Heilongjiang China 47.8620 127.7615 0.0 2.0 \n", + "60 Henan China 33.8820 113.6140 5.0 5.0 \n", + "61 Hong Kong China 22.3000 114.2000 0.0 2.0 \n", + "62 Hubei China 30.9756 112.2707 444.0 444.0 \n", + "63 Hunan China 27.6104 111.7088 4.0 9.0 \n", + "64 Inner Mongolia China 44.0935 113.9448 0.0 0.0 \n", + "65 Jiangsu China 32.9711 119.4550 1.0 5.0 \n", + "66 Jiangxi China 27.6140 115.7221 2.0 7.0 \n", + "67 Jilin China 43.6661 126.1923 0.0 1.0 \n", + "68 Liaoning China 41.2956 122.6085 2.0 3.0 \n", + "69 Macau China 22.1667 113.5500 1.0 2.0 \n", + "70 Ningxia China 37.2692 106.1655 1.0 1.0 \n", + "71 Qinghai China 35.7452 95.9956 0.0 0.0 \n", + "72 Shaanxi China 35.1917 108.8701 0.0 3.0 \n", + "73 Shandong China 36.3427 118.1498 2.0 6.0 \n", + "74 Shanghai China 31.2020 121.4491 9.0 16.0 \n", + "75 Shanxi China 37.5777 112.2922 1.0 1.0 \n", + "76 Sichuan China 30.6171 102.7103 5.0 8.0 \n", + "77 Tianjin China 39.3054 117.3230 4.0 4.0 \n", + "78 Tibet China 31.6927 88.0924 0.0 0.0 \n", + "79 Xinjiang China 41.1129 85.2401 0.0 2.0 \n", + "80 Yunnan China 24.9740 101.4870 1.0 2.0 \n", + "81 Zhejiang China 29.1832 120.0934 10.0 27.0 \n", + "1 NaN China NaN NaN 548.0 643.0 \n", + "\n", + " 1/24/20 1/25/20 1/26/20 1/27/20 ... 5/19/20 5/20/20 5/21/20 \\\n", + "49 15.0 39.0 60.0 70.0 ... 991.0 991.0 991.0 \n", + "50 36.0 41.0 68.0 80.0 ... 593.0 593.0 593.0 \n", + "51 27.0 57.0 75.0 110.0 ... 579.0 579.0 579.0 \n", + "52 10.0 18.0 35.0 59.0 ... 356.0 356.0 356.0 \n", + "53 2.0 4.0 7.0 14.0 ... 139.0 139.0 139.0 \n", + "54 53.0 78.0 111.0 151.0 ... 1590.0 1590.0 1590.0 \n", + "55 23.0 23.0 36.0 46.0 ... 254.0 254.0 254.0 \n", + "56 3.0 4.0 5.0 7.0 ... 147.0 147.0 147.0 \n", + "57 8.0 19.0 22.0 33.0 ... 169.0 169.0 169.0 \n", + "58 2.0 8.0 13.0 18.0 ... 328.0 328.0 328.0 \n", + "59 4.0 9.0 15.0 21.0 ... 945.0 945.0 945.0 \n", + "60 9.0 32.0 83.0 128.0 ... 1276.0 1276.0 1276.0 \n", + "61 2.0 5.0 8.0 8.0 ... 1055.0 1055.0 1055.0 \n", + "62 549.0 761.0 1058.0 1423.0 ... 68135.0 68135.0 68135.0 \n", + "63 24.0 43.0 69.0 100.0 ... 1019.0 1019.0 1019.0 \n", + "64 1.0 7.0 7.0 11.0 ... 216.0 216.0 216.0 \n", + "65 9.0 18.0 33.0 47.0 ... 653.0 653.0 653.0 \n", + "66 18.0 18.0 36.0 72.0 ... 937.0 937.0 937.0 \n", + "67 3.0 4.0 4.0 6.0 ... 151.0 151.0 151.0 \n", + "68 4.0 17.0 21.0 27.0 ... 149.0 149.0 149.0 \n", + "69 2.0 2.0 5.0 6.0 ... 45.0 45.0 45.0 \n", + "70 2.0 3.0 4.0 7.0 ... 75.0 75.0 75.0 \n", + "71 0.0 1.0 1.0 6.0 ... 18.0 18.0 18.0 \n", + "72 5.0 15.0 22.0 35.0 ... 308.0 308.0 308.0 \n", + "73 15.0 27.0 46.0 75.0 ... 788.0 788.0 788.0 \n", + "74 20.0 33.0 40.0 53.0 ... 666.0 666.0 666.0 \n", + "75 1.0 6.0 9.0 13.0 ... 198.0 198.0 198.0 \n", + "76 15.0 28.0 44.0 69.0 ... 561.0 561.0 561.0 \n", + "77 8.0 10.0 14.0 23.0 ... 192.0 192.0 192.0 \n", + "78 0.0 0.0 0.0 0.0 ... 1.0 1.0 1.0 \n", + "79 2.0 3.0 4.0 5.0 ... 76.0 76.0 76.0 \n", + "80 5.0 11.0 16.0 26.0 ... 185.0 185.0 185.0 \n", + "81 43.0 62.0 104.0 128.0 ... 1268.0 1268.0 1268.0 \n", + "1 920.0 1406.0 2075.0 2877.0 ... 84063.0 84063.0 84063.0 \n", + "\n", + " 5/22/20 5/23/20 5/24/20 5/25/20 5/26/20 5/27/20 5/28/20 \n", + "49 991.0 991.0 991.0 991.0 991.0 991.0 991.0 \n", + "50 593.0 593.0 593.0 593.0 593.0 593.0 593.0 \n", + "51 579.0 579.0 579.0 579.0 579.0 579.0 579.0 \n", + "52 356.0 356.0 356.0 357.0 357.0 358.0 358.0 \n", + "53 139.0 139.0 139.0 139.0 139.0 139.0 139.0 \n", + "54 1591.0 1592.0 1592.0 1592.0 1592.0 1592.0 1592.0 \n", + "55 254.0 254.0 254.0 254.0 254.0 254.0 254.0 \n", + "56 147.0 147.0 147.0 147.0 147.0 147.0 147.0 \n", + "57 169.0 169.0 169.0 169.0 169.0 169.0 169.0 \n", + "58 328.0 328.0 328.0 328.0 328.0 328.0 328.0 \n", + "59 945.0 945.0 945.0 945.0 945.0 945.0 945.0 \n", + "60 1276.0 1276.0 1276.0 1276.0 1276.0 1276.0 1276.0 \n", + "61 1065.0 1065.0 1065.0 1065.0 1065.0 1066.0 1066.0 \n", + "62 68135.0 68135.0 68135.0 68135.0 68135.0 68135.0 68135.0 \n", + "63 1019.0 1019.0 1019.0 1019.0 1019.0 1019.0 1019.0 \n", + "64 217.0 217.0 227.0 232.0 232.0 232.0 232.0 \n", + "65 653.0 653.0 653.0 653.0 653.0 653.0 653.0 \n", + "66 937.0 937.0 937.0 937.0 937.0 937.0 937.0 \n", + "67 154.0 155.0 155.0 155.0 155.0 155.0 155.0 \n", + "68 149.0 149.0 149.0 149.0 149.0 149.0 149.0 \n", + "69 45.0 45.0 45.0 45.0 45.0 45.0 45.0 \n", + "70 75.0 75.0 75.0 75.0 75.0 75.0 75.0 \n", + "71 18.0 18.0 18.0 18.0 18.0 18.0 18.0 \n", + "72 308.0 308.0 308.0 308.0 308.0 308.0 308.0 \n", + "73 788.0 788.0 788.0 788.0 788.0 788.0 788.0 \n", + "74 667.0 668.0 668.0 669.0 670.0 671.0 671.0 \n", + "75 198.0 198.0 198.0 198.0 198.0 198.0 198.0 \n", + "76 563.0 563.0 564.0 564.0 564.0 564.0 564.0 \n", + "77 192.0 192.0 192.0 192.0 192.0 192.0 192.0 \n", + "78 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n", + "79 76.0 76.0 76.0 76.0 76.0 76.0 76.0 \n", + "80 185.0 185.0 185.0 185.0 185.0 185.0 185.0 \n", + "81 1268.0 1268.0 1268.0 1268.0 1268.0 1268.0 1268.0 \n", + "1 84081.0 84084.0 84095.0 84102.0 84103.0 84106.0 84106.0 \n", + "\n", + "[34 rows x 132 columns]" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# For china the data have to be summed between region in order to get the results for the whole country.\n", + "dataChina = raw_data.loc[(raw_data['Country/Region'] == 'China')]\n", + "\n", + "#print(dataChina)\n", + "\n", + "#let's use df.sum() to sum rows \n", + "col_list= list(dataChina)\n", + "col_list.remove(\"Province/State\")\n", + "col_list.remove(\"Country/Region\")\n", + "col_list.remove(\"Lat\")\n", + "col_list.remove(\"Long\")\n", + "\n", + "\n", + "\n", + "for col in col_list: \n", + " dataChina.at['1', col] = dataChina[col].sum()\n", + "\n", + "\n", + "dataChina.at['1', \"Country/Region\"] = \"China\"\n", + "\n", + "dataChina" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": {