From b0437603d6f956269ecab3250465c48d46deee7f Mon Sep 17 00:00:00 2001 From: dca34f41fee2efa24adbe57b0fcf3009 Date: Tue, 9 Jun 2020 19:56:44 +0000 Subject: [PATCH] exercise done --- module3/exo3/exercice.ipynb | 1007 +---------------------------------- 1 file changed, 9 insertions(+), 998 deletions(-) diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb index a41d677..7f39a69 100644 --- a/module3/exo3/exercice.ipynb +++ b/module3/exo3/exercice.ipynb @@ -1851,274 +1851,12 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Province/State Country/Region 1/22/20 \\\n", - "0 NaN Afghanistan 0 \n", - "1 NaN Albania 0 \n", - "2 NaN Algeria 0 \n", - "3 NaN Andorra 0 \n", - "4 NaN Angola 0 \n", - "5 NaN Antigua and Barbuda 0 \n", - "6 NaN Argentina 0 \n", - "7 NaN Armenia 0 \n", - "8 Australian Capital Territory Australia 0 \n", - "9 New South Wales Australia 0 \n", - "10 Northern Territory Australia 0 \n", - "11 Queensland Australia 0 \n", - "12 South Australia Australia 0 \n", - "13 Tasmania Australia 0 \n", - "14 Victoria Australia 0 \n", - "15 Western Australia Australia 0 \n", - "16 NaN Austria 0 \n", - "17 NaN Azerbaijan 0 \n", - "18 NaN Bahamas 0 \n", - "19 NaN Bahrain 0 \n", - "20 NaN Bangladesh 0 \n", - "21 NaN Barbados 0 \n", - "22 NaN Belarus 0 \n", - "23 NaN Belgium 0 \n", - "24 NaN Benin 0 \n", - "25 NaN Bhutan 0 \n", - "26 NaN Bolivia 0 \n", - "27 NaN Bosnia and Herzegovina 0 \n", - "28 NaN Brazil 0 \n", - "29 NaN Brunei 0 \n", - ".. ... ... ... \n", - "236 NaN Timor-Leste 0 \n", - "237 NaN Belize 0 \n", - "238 NaN Laos 0 \n", - "239 NaN Libya 0 \n", - "240 NaN West Bank and Gaza 0 \n", - "241 NaN Guinea-Bissau 0 \n", - "242 NaN Mali 0 \n", - "243 NaN Saint Kitts and Nevis 0 \n", - "244 Northwest Territories Canada 0 \n", - "245 Yukon Canada 0 \n", - "246 NaN Kosovo 0 \n", - "247 NaN Burma 0 \n", - "248 Anguilla United Kingdom 0 \n", - "249 British Virgin Islands United Kingdom 0 \n", - "250 Turks and Caicos Islands United Kingdom 0 \n", - "251 NaN MS Zaandam 0 \n", - "252 NaN Botswana 0 \n", - "253 NaN Burundi 0 \n", - "254 NaN Sierra Leone 0 \n", - "255 Bonaire, Sint Eustatius and Saba Netherlands 0 \n", - "256 NaN Malawi 0 \n", - "257 Falkland Islands (Malvinas) United Kingdom 0 \n", - "258 Saint Pierre and Miquelon France 0 \n", - "259 NaN South Sudan 0 \n", - "260 NaN Western Sahara 0 \n", - "261 NaN Sao Tome and Principe 0 \n", - "262 NaN Yemen 0 \n", - "263 NaN Comoros 0 \n", - "264 NaN Tajikistan 0 \n", - "265 NaN Lesotho 0 \n", - "\n", - " 1/23/20 1/24/20 1/25/20 1/26/20 1/27/20 1/28/20 1/29/20 ... \\\n", - "0 0 0 0 0 0 0 0 ... \n", - "1 0 0 0 0 0 0 0 ... \n", - "2 0 0 0 0 0 0 0 ... \n", - "3 0 0 0 0 0 0 0 ... \n", - "4 0 0 0 0 0 0 0 ... \n", - "5 0 0 0 0 0 0 0 ... \n", - "6 0 0 0 0 0 0 0 ... \n", - "7 0 0 0 0 0 0 0 ... \n", - "8 0 0 0 0 0 0 0 ... \n", - "9 0 0 0 3 4 4 4 ... \n", - "10 0 0 0 0 0 0 0 ... \n", - "11 0 0 0 0 0 0 1 ... \n", - "12 0 0 0 0 0 0 0 ... \n", - "13 0 0 0 0 0 0 0 ... \n", - "14 0 0 0 1 1 1 1 ... \n", - "15 0 0 0 0 0 0 0 ... \n", - "16 0 0 0 0 0 0 0 ... \n", - "17 0 0 0 0 0 0 0 ... \n", - "18 0 0 0 0 0 0 0 ... \n", - "19 0 0 0 0 0 0 0 ... \n", - "20 0 0 0 0 0 0 0 ... \n", - "21 0 0 0 0 0 0 0 ... \n", - "22 0 0 0 0 0 0 0 ... \n", - "23 0 0 0 0 0 0 0 ... \n", - "24 0 0 0 0 0 0 0 ... \n", - "25 0 0 0 0 0 0 0 ... \n", - "26 0 0 0 0 0 0 0 ... \n", - "27 0 0 0 0 0 0 0 ... \n", - "28 0 0 0 0 0 0 0 ... \n", - "29 0 0 0 0 0 0 0 ... \n", - ".. ... ... ... ... ... ... ... ... \n", - "236 0 0 0 0 0 0 0 ... \n", - "237 0 0 0 0 0 0 0 ... \n", - "238 0 0 0 0 0 0 0 ... \n", - "239 0 0 0 0 0 0 0 ... \n", - "240 0 0 0 0 0 0 0 ... \n", - "241 0 0 0 0 0 0 0 ... \n", - "242 0 0 0 0 0 0 0 ... \n", - "243 0 0 0 0 0 0 0 ... \n", - "244 0 0 0 0 0 0 0 ... \n", - "245 0 0 0 0 0 0 0 ... \n", - "246 0 0 0 0 0 0 0 ... \n", - "247 0 0 0 0 0 0 0 ... \n", - "248 0 0 0 0 0 0 0 ... \n", - "249 0 0 0 0 0 0 0 ... \n", - "250 0 0 0 0 0 0 0 ... \n", - "251 0 0 0 0 0 0 0 ... \n", - "252 0 0 0 0 0 0 0 ... \n", - "253 0 0 0 0 0 0 0 ... \n", - "254 0 0 0 0 0 0 0 ... \n", - "255 0 0 0 0 0 0 0 ... \n", - "256 0 0 0 0 0 0 0 ... \n", - "257 0 0 0 0 0 0 0 ... \n", - "258 0 0 0 0 0 0 0 ... \n", - "259 0 0 0 0 0 0 0 ... \n", - "260 0 0 0 0 0 0 0 ... \n", - "261 0 0 0 0 0 0 0 ... \n", - "262 0 0 0 0 0 0 0 ... \n", - "263 0 0 0 0 0 0 0 ... \n", - "264 0 0 0 0 0 0 0 ... \n", - "265 0 0 0 0 0 0 0 ... \n", - "\n", - " 5/30/20 5/31/20 6/1/20 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 \\\n", - "0 14525 15205 15750 16509 17267 18054 18969 19551 20342 \n", - "1 1122 1137 1143 1164 1184 1197 1212 1232 1246 \n", - "2 9267 9394 9513 9626 9733 9831 9935 10050 10154 \n", - "3 764 764 765 844 851 852 852 852 852 \n", - "4 84 86 86 86 86 86 86 88 91 \n", - "5 25 26 26 26 26 26 26 26 26 \n", - "6 16214 16851 17415 18319 19268 20197 21037 22020 22794 \n", - "7 8927 9282 9492 10009 10524 11221 11817 12364 13130 \n", - "8 107 107 107 107 107 107 107 108 108 \n", - "9 3095 3098 3104 3104 3106 3110 3110 3109 3112 \n", - "10 29 29 29 29 29 29 29 29 29 \n", - "11 1058 1058 1059 1059 1060 1060 1061 1061 1062 \n", - "12 440 440 440 440 440 440 440 440 440 \n", - "13 228 228 228 228 228 228 228 228 228 \n", - "14 1649 1653 1663 1670 1678 1681 1681 1685 1687 \n", - "15 586 589 591 592 592 592 596 599 599 \n", - "16 16685 16731 16733 16759 16771 16805 16843 16898 16902 \n", - "17 5246 5494 5662 5935 6260 6522 6860 7239 7553 \n", - "18 102 102 102 102 102 102 102 103 103 \n", - "19 10793 11398 11871 12311 12815 13296 13835 14383 14763 \n", - "20 44608 47153 49534 52445 55140 57563 60391 63026 65769 \n", - "21 92 92 92 92 92 92 92 92 92 \n", - "22 41658 42556 43403 44255 45116 45981 46868 47751 48630 \n", - "23 58186 58381 58517 58615 58685 58767 58907 59072 59226 \n", - "24 224 232 243 244 244 261 261 261 261 \n", - "25 33 43 43 47 47 47 48 48 59 \n", - "26 9592 9982 10531 10991 11638 12245 12728 13358 13643 \n", - "27 2494 2510 2524 2535 2551 2594 2606 2606 2606 \n", - "28 498440 514849 526447 555383 584016 614941 645771 672846 691758 \n", - "29 141 141 141 141 141 141 141 141 141 \n", - ".. ... ... ... ... ... ... ... ... ... \n", - "236 24 24 24 24 24 24 24 24 24 \n", - "237 18 18 18 18 18 18 19 19 19 \n", - "238 19 19 19 19 19 19 19 19 19 \n", - "239 130 156 168 182 196 209 239 256 256 \n", - "240 447 448 449 451 457 464 464 464 472 \n", - "241 1256 1256 1339 1339 1339 1339 1368 1368 1368 \n", - "242 1250 1265 1315 1351 1386 1461 1485 1523 1533 \n", - "243 15 15 15 15 15 15 15 15 15 \n", - "244 5 5 5 5 5 5 5 5 5 \n", - "245 11 11 11 11 11 11 11 11 11 \n", - "246 1064 1064 1064 1064 1142 1142 1142 1142 1142 \n", - "247 224 224 228 232 233 236 236 240 242 \n", - "248 3 3 3 3 3 3 3 3 3 \n", - "249 8 8 8 8 8 8 8 8 8 \n", - "250 12 12 12 12 12 12 12 12 12 \n", - "251 9 9 9 9 9 9 9 9 9 \n", - "252 35 35 38 40 40 40 40 40 40 \n", - "253 63 63 63 63 63 63 63 83 83 \n", - "254 852 861 865 896 909 914 929 946 969 \n", - "255 6 6 7 7 7 7 7 7 7 \n", - "256 279 284 336 358 369 393 409 409 438 \n", - "257 13 13 13 13 13 13 13 13 13 \n", - "258 1 1 1 1 1 1 1 1 1 \n", - "259 994 994 994 994 994 994 994 994 1317 \n", - "260 9 9 9 9 9 9 9 9 9 \n", - "261 479 483 484 484 484 485 499 499 513 \n", - "262 310 323 354 399 419 453 469 482 484 \n", - "263 106 106 106 132 132 132 132 141 141 \n", - "264 3807 3930 4013 4100 4191 4289 4370 4453 4529 \n", - "265 2 2 2 2 4 4 4 4 4 \n", - "\n", - " 6/8/20 \n", - "0 20917 \n", - "1 1263 \n", - "2 10265 \n", - "3 852 \n", - "4 92 \n", - "5 26 \n", - "6 23620 \n", - "7 13325 \n", - "8 108 \n", - "9 3114 \n", - "10 29 \n", - "11 1062 \n", - "12 440 \n", - "13 228 \n", - "14 1687 \n", - "15 599 \n", - "16 16968 \n", - "17 7876 \n", - "18 103 \n", - "19 15417 \n", - "20 68504 \n", - "21 92 \n", - "22 49453 \n", - "23 59348 \n", - "24 288 \n", - "25 59 \n", - "26 13949 \n", - "27 2704 \n", - "28 707412 \n", - "29 141 \n", - ".. ... \n", - "236 24 \n", - "237 19 \n", - "238 19 \n", - "239 332 \n", - "240 473 \n", - "241 1389 \n", - "242 1547 \n", - "243 15 \n", - "244 5 \n", - "245 11 \n", - "246 1263 \n", - "247 244 \n", - "248 3 \n", - "249 8 \n", - "250 12 \n", - "251 9 \n", - "252 42 \n", - "253 83 \n", - "254 1001 \n", - "255 7 \n", - "256 443 \n", - "257 13 \n", - "258 1 \n", - "259 1604 \n", - "260 9 \n", - "261 513 \n", - "262 496 \n", - "263 141 \n", - "264 4609 \n", - "265 4 \n", - "\n", - "[266 rows x 141 columns]\n" - ] - } - ], + "outputs": [], "source": [ "df = pd.DataFrame(raw_data)\n", "\n", "df_total=df.drop(columns=['Lat', 'Long'])\n", - "df=df_total\n", - "\n", - "print(df)" + "df=df_total" ] }, { @@ -2132,270 +1870,9 @@ "cell_type": "code", "execution_count": 5, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Province/State Country/Region 1/22/20 1/23/20 \\\n", - "23 NaN Belgium 0 0 \n", - "49 Anhui China 1 9 \n", - "50 Beijing China 14 22 \n", - "51 Chongqing China 6 9 \n", - "52 Fujian China 1 5 \n", - "53 Gansu China 0 2 \n", - "54 Guangdong China 26 32 \n", - "55 Guangxi China 2 5 \n", - "56 Guizhou China 1 3 \n", - "57 Hainan China 4 5 \n", - "58 Hebei China 1 1 \n", - "59 Heilongjiang China 0 2 \n", - "60 Henan China 5 5 \n", - "61 Hong Kong China 0 2 \n", - "62 Hubei China 444 444 \n", - "63 Hunan China 4 9 \n", - "64 Inner Mongolia China 0 0 \n", - "65 Jiangsu China 1 5 \n", - "66 Jiangxi China 2 7 \n", - "67 Jilin China 0 1 \n", - "68 Liaoning China 2 3 \n", - "69 Macau China 1 2 \n", - "70 Ningxia China 1 1 \n", - "71 Qinghai China 0 0 \n", - "72 Shaanxi China 0 3 \n", - "73 Shandong China 2 6 \n", - "74 Shanghai China 9 16 \n", - "75 Shanxi China 1 1 \n", - "76 Sichuan China 5 8 \n", - "77 Tianjin China 4 4 \n", - ".. ... ... ... ... \n", - "111 New Caledonia France 0 0 \n", - "112 Reunion France 0 0 \n", - "113 Saint Barthelemy France 0 0 \n", - "114 St Martin France 0 0 \n", - "115 Martinique France 0 0 \n", - "116 NaN France 0 0 \n", - "120 NaN Germany 0 0 \n", - "133 NaN Iran 0 0 \n", - "137 NaN Italy 0 0 \n", - "139 NaN Japan 2 2 \n", - "166 Aruba Netherlands 0 0 \n", - "167 Curacao Netherlands 0 0 \n", - "168 Sint Maarten Netherlands 0 0 \n", - "169 NaN Netherlands 0 0 \n", - "184 NaN Portugal 0 0 \n", - "201 NaN Spain 0 0 \n", - "217 Bermuda United Kingdom 0 0 \n", - "218 Cayman Islands United Kingdom 0 0 \n", - "219 Channel Islands United Kingdom 0 0 \n", - "220 Gibraltar United Kingdom 0 0 \n", - "221 Isle of Man United Kingdom 0 0 \n", - "222 Montserrat United Kingdom 0 0 \n", - "223 NaN United Kingdom 0 0 \n", - "225 NaN US 1 1 \n", - "248 Anguilla United Kingdom 0 0 \n", - "249 British Virgin Islands United Kingdom 0 0 \n", - "250 Turks and Caicos Islands United Kingdom 0 0 \n", - "255 Bonaire, Sint Eustatius and Saba Netherlands 0 0 \n", - "257 Falkland Islands (Malvinas) United Kingdom 0 0 \n", - "258 Saint Pierre and Miquelon France 0 0 \n", - "\n", - " 1/24/20 1/25/20 1/26/20 1/27/20 1/28/20 1/29/20 ... 5/30/20 \\\n", - "23 0 0 0 0 0 0 ... 58186 \n", - "49 15 39 60 70 106 152 ... 991 \n", - "50 36 41 68 80 91 111 ... 593 \n", - "51 27 57 75 110 132 147 ... 579 \n", - "52 10 18 35 59 80 84 ... 358 \n", - "53 2 4 7 14 19 24 ... 139 \n", - "54 53 78 111 151 207 277 ... 1593 \n", - "55 23 23 36 46 51 58 ... 254 \n", - "56 3 4 5 7 9 9 ... 147 \n", - "57 8 19 22 33 40 43 ... 169 \n", - "58 2 8 13 18 33 48 ... 328 \n", - "59 4 9 15 21 33 38 ... 945 \n", - "60 9 32 83 128 168 206 ... 1276 \n", - "61 2 5 8 8 8 10 ... 1082 \n", - "62 549 761 1058 1423 3554 3554 ... 68135 \n", - "63 24 43 69 100 143 221 ... 1019 \n", - "64 1 7 7 11 15 16 ... 232 \n", - "65 9 18 33 47 70 99 ... 653 \n", - "66 18 18 36 72 109 109 ... 937 \n", - "67 3 4 4 6 8 9 ... 155 \n", - "68 4 17 21 27 34 39 ... 149 \n", - "69 2 2 5 6 7 7 ... 45 \n", - "70 2 3 4 7 11 12 ... 75 \n", - "71 0 1 1 6 6 6 ... 18 \n", - "72 5 15 22 35 46 56 ... 308 \n", - "73 15 27 46 75 95 130 ... 792 \n", - "74 20 33 40 53 66 96 ... 672 \n", - "75 1 6 9 13 27 27 ... 198 \n", - "76 15 28 44 69 90 108 ... 564 \n", - "77 8 10 14 23 24 27 ... 192 \n", - ".. ... ... ... ... ... ... ... ... \n", - "111 0 0 0 0 0 0 ... 19 \n", - "112 0 0 0 0 0 0 ... 471 \n", - "113 0 0 0 0 0 0 ... 6 \n", - "114 0 0 0 0 0 0 ... 41 \n", - "115 0 0 0 0 0 0 ... 200 \n", - "116 2 3 3 3 4 5 ... 185616 \n", - "120 0 0 0 1 4 4 ... 183189 \n", - "133 0 0 0 0 0 0 ... 148950 \n", - "137 0 0 0 0 0 0 ... 232664 \n", - "139 2 2 4 4 7 7 ... 16716 \n", - "166 0 0 0 0 0 0 ... 101 \n", - "167 0 0 0 0 0 0 ... 19 \n", - "168 0 0 0 0 0 0 ... 77 \n", - "169 0 0 0 0 0 0 ... 46257 \n", - "184 0 0 0 0 0 0 ... 32203 \n", - "201 0 0 0 0 0 0 ... 239228 \n", - "217 0 0 0 0 0 0 ... 140 \n", - "218 0 0 0 0 0 0 ... 141 \n", - "219 0 0 0 0 0 0 ... 560 \n", - "220 0 0 0 0 0 0 ... 169 \n", - "221 0 0 0 0 0 0 ... 336 \n", - "222 0 0 0 0 0 0 ... 11 \n", - "223 0 0 0 0 0 0 ... 272826 \n", - "225 2 2 5 5 5 5 ... 1770165 \n", - "248 0 0 0 0 0 0 ... 3 \n", - "249 0 0 0 0 0 0 ... 8 \n", - "250 0 0 0 0 0 0 ... 12 \n", - "255 0 0 0 0 0 0 ... 6 \n", - "257 0 0 0 0 0 0 ... 13 \n", - "258 0 0 0 0 0 0 ... 1 \n", - "\n", - " 5/31/20 6/1/20 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 \\\n", - "23 58381 58517 58615 58685 58767 58907 59072 59226 \n", - "49 991 991 991 991 991 991 991 991 \n", - "50 593 593 593 594 594 594 594 594 \n", - "51 579 579 579 579 579 579 579 579 \n", - "52 358 358 358 358 358 358 359 359 \n", - "53 139 139 139 139 139 139 139 139 \n", - "54 1595 1596 1597 1598 1598 1601 1602 1602 \n", - "55 254 254 254 254 254 254 254 254 \n", - "56 147 147 147 147 147 147 147 147 \n", - "57 169 169 169 169 169 169 170 170 \n", - "58 328 328 328 328 328 328 328 328 \n", - "59 945 945 945 947 947 947 947 947 \n", - "60 1276 1276 1276 1276 1276 1276 1276 1276 \n", - "61 1084 1087 1093 1093 1099 1102 1105 1106 \n", - "62 68135 68135 68135 68135 68135 68135 68135 68135 \n", - "63 1019 1019 1019 1019 1019 1019 1019 1019 \n", - "64 235 235 235 235 235 235 235 235 \n", - "65 653 653 653 653 653 653 653 653 \n", - "66 937 937 937 932 932 932 932 932 \n", - "67 155 155 155 155 155 155 155 155 \n", - "68 149 149 149 149 149 149 149 149 \n", - "69 45 45 45 45 45 45 45 45 \n", - "70 75 75 75 75 75 75 75 75 \n", - "71 18 18 18 18 18 18 18 18 \n", - "72 308 309 309 309 309 309 311 311 \n", - "73 792 792 792 792 792 792 792 792 \n", - "74 672 673 673 673 677 677 677 678 \n", - "75 198 198 198 198 198 198 198 198 \n", - "76 575 577 577 577 578 578 578 581 \n", - "77 192 192 192 192 192 192 193 193 \n", - ".. ... ... ... ... ... ... ... ... \n", - "111 19 20 20 20 20 20 20 20 \n", - "112 471 473 477 478 479 480 480 480 \n", - "113 6 6 6 6 6 6 6 6 \n", - "114 41 41 41 41 41 41 41 41 \n", - "115 200 200 200 200 200 202 202 202 \n", - "116 185851 185952 184980 188836 185986 186538 187067 187360 \n", - "120 183410 183594 183879 184121 184472 184924 185450 185750 \n", - "133 151466 154445 157562 160696 164270 167156 169425 171789 \n", - "137 232997 233197 233515 233836 234013 234531 234801 234998 \n", - "139 16751 16787 16837 16867 16911 16958 17000 17039 \n", - "166 101 101 101 101 101 101 101 101 \n", - "167 19 19 20 21 21 21 21 21 \n", - "168 77 77 77 77 77 77 77 77 \n", - "169 46442 46545 46647 46733 46942 47152 47335 47574 \n", - "184 32500 32700 32895 33261 33592 33969 34351 34693 \n", - "201 239479 239638 239932 240326 240660 240978 241310 241550 \n", - "217 140 141 141 141 141 141 141 141 \n", - "218 141 150 151 156 160 164 164 164 \n", - "219 560 560 560 561 561 561 563 563 \n", - "220 170 170 172 173 173 174 175 176 \n", - "221 336 336 336 336 336 336 336 336 \n", - "222 11 11 11 11 11 11 11 11 \n", - "223 274762 276332 277985 279856 281661 283311 284868 286194 \n", - "225 1790172 1811020 1831821 1851520 1872660 1897380 1920061 1943647 \n", - "248 3 3 3 3 3 3 3 3 \n", - "249 8 8 8 8 8 8 8 8 \n", - "250 12 12 12 12 12 12 12 12 \n", - "255 6 7 7 7 7 7 7 7 \n", - "257 13 13 13 13 13 13 13 13 \n", - "258 1 1 1 1 1 1 1 1 \n", - "\n", - " 6/8/20 \n", - "23 59348 \n", - "49 991 \n", - "50 594 \n", - "51 579 \n", - "52 359 \n", - "53 139 \n", - "54 1604 \n", - "55 254 \n", - "56 147 \n", - "57 170 \n", - "58 328 \n", - "59 947 \n", - "60 1276 \n", - "61 1107 \n", - "62 68135 \n", - "63 1019 \n", - "64 235 \n", - "65 653 \n", - "66 932 \n", - "67 155 \n", - "68 149 \n", - "69 45 \n", - "70 75 \n", - "71 18 \n", - "72 311 \n", - "73 792 \n", - "74 678 \n", - "75 198 \n", - "76 582 \n", - "77 193 \n", - ".. ... \n", - "111 20 \n", - "112 481 \n", - "113 6 \n", - "114 41 \n", - "115 202 \n", - "116 187458 \n", - "120 186109 \n", - "133 173832 \n", - "137 235278 \n", - "139 17060 \n", - "166 101 \n", - "167 21 \n", - "168 77 \n", - "169 47739 \n", - "184 34885 \n", - "201 241717 \n", - "217 141 \n", - "218 171 \n", - "219 564 \n", - "220 176 \n", - "221 336 \n", - "222 11 \n", - "223 287399 \n", - "225 1960897 \n", - "248 3 \n", - "249 8 \n", - "250 12 \n", - "255 7 \n", - "257 13 \n", - "258 1 \n", - "\n", - "[68 rows x 141 columns]\n" - ] - } - ], + "outputs": [], "source": [ - "df=df.drop(df[(df['Country/Region'] != 'Belgium') & (df['Country/Region'] != 'China') & (df['Country/Region'] != 'France') & (df['Country/Region'] != 'Germany') & (df['Country/Region'] != 'Iran') & (df['Country/Region'] != 'Italy') & (df['Country/Region'] != 'Japan') & (df['Country/Region'] != 'Korea South') & (df['Country/Region'] != 'Netherlands') & (df['Country/Region'] != 'Portugal') & (df['Country/Region'] != 'Spain') & (df['Country/Region'] != 'United Kingdom') & (df['Country/Region'] != 'US')].index)\n", - "print(df)" + "df=df.drop(df[(df['Country/Region'] != 'Belgium') & (df['Country/Region'] != 'China') & (df['Country/Region'] != 'France') & (df['Country/Region'] != 'Germany') & (df['Country/Region'] != 'Iran') & (df['Country/Region'] != 'Italy') & (df['Country/Region'] != 'Japan') & (df['Country/Region'] != 'Korea South') & (df['Country/Region'] != 'Netherlands') & (df['Country/Region'] != 'Portugal') & (df['Country/Region'] != 'Spain') & (df['Country/Region'] != 'United Kingdom') & (df['Country/Region'] != 'US')].index)\n" ] }, { @@ -2410,265 +1887,6 @@ "execution_count": 6, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Province/State Country/Region 1/22/20 1/23/20 \\\n", - "23 NaN Belgium 0 0 \n", - "49 Anhui China 1 9 \n", - "50 Beijing China 14 22 \n", - "51 Chongqing China 6 9 \n", - "52 Fujian China 1 5 \n", - "53 Gansu China 0 2 \n", - "54 Guangdong China 26 32 \n", - "55 Guangxi China 2 5 \n", - "56 Guizhou China 1 3 \n", - "57 Hainan China 4 5 \n", - "58 Hebei China 1 1 \n", - "59 Heilongjiang China 0 2 \n", - "60 Henan China 5 5 \n", - "61 Hong Kong Hong Kong 0 2 \n", - "62 Hubei China 444 444 \n", - "63 Hunan China 4 9 \n", - "64 Inner Mongolia China 0 0 \n", - "65 Jiangsu China 1 5 \n", - "66 Jiangxi China 2 7 \n", - "67 Jilin China 0 1 \n", - "68 Liaoning China 2 3 \n", - "69 Macau China 1 2 \n", - "70 Ningxia China 1 1 \n", - "71 Qinghai China 0 0 \n", - "72 Shaanxi China 0 3 \n", - "73 Shandong China 2 6 \n", - "74 Shanghai China 9 16 \n", - "75 Shanxi China 1 1 \n", - "76 Sichuan China 5 8 \n", - "77 Tianjin China 4 4 \n", - ".. ... ... ... ... \n", - "111 New Caledonia France 0 0 \n", - "112 Reunion France 0 0 \n", - "113 Saint Barthelemy France 0 0 \n", - "114 St Martin France 0 0 \n", - "115 Martinique France 0 0 \n", - "116 NaN France 0 0 \n", - "120 NaN Germany 0 0 \n", - "133 NaN Iran 0 0 \n", - "137 NaN Italy 0 0 \n", - "139 NaN Japan 2 2 \n", - "166 Aruba Netherlands 0 0 \n", - "167 Curacao Netherlands 0 0 \n", - "168 Sint Maarten Netherlands 0 0 \n", - "169 NaN Netherlands 0 0 \n", - "184 NaN Portugal 0 0 \n", - "201 NaN Spain 0 0 \n", - "217 Bermuda United Kingdom 0 0 \n", - "218 Cayman Islands United Kingdom 0 0 \n", - "219 Channel Islands United Kingdom 0 0 \n", - "220 Gibraltar United Kingdom 0 0 \n", - "221 Isle of Man United Kingdom 0 0 \n", - "222 Montserrat United Kingdom 0 0 \n", - "223 NaN United Kingdom 0 0 \n", - "225 NaN US 1 1 \n", - "248 Anguilla United Kingdom 0 0 \n", - "249 British Virgin Islands United Kingdom 0 0 \n", - "250 Turks and Caicos Islands United Kingdom 0 0 \n", - "255 Bonaire, Sint Eustatius and Saba Netherlands 0 0 \n", - "257 Falkland Islands (Malvinas) United Kingdom 0 0 \n", - "258 Saint Pierre and Miquelon France 0 0 \n", - "\n", - " 1/24/20 1/25/20 1/26/20 1/27/20 1/28/20 1/29/20 ... 5/30/20 \\\n", - "23 0 0 0 0 0 0 ... 58186 \n", - "49 15 39 60 70 106 152 ... 991 \n", - "50 36 41 68 80 91 111 ... 593 \n", - "51 27 57 75 110 132 147 ... 579 \n", - "52 10 18 35 59 80 84 ... 358 \n", - "53 2 4 7 14 19 24 ... 139 \n", - "54 53 78 111 151 207 277 ... 1593 \n", - "55 23 23 36 46 51 58 ... 254 \n", - "56 3 4 5 7 9 9 ... 147 \n", - "57 8 19 22 33 40 43 ... 169 \n", - "58 2 8 13 18 33 48 ... 328 \n", - "59 4 9 15 21 33 38 ... 945 \n", - "60 9 32 83 128 168 206 ... 1276 \n", - "61 2 5 8 8 8 10 ... 1082 \n", - "62 549 761 1058 1423 3554 3554 ... 68135 \n", - "63 24 43 69 100 143 221 ... 1019 \n", - "64 1 7 7 11 15 16 ... 232 \n", - "65 9 18 33 47 70 99 ... 653 \n", - "66 18 18 36 72 109 109 ... 937 \n", - "67 3 4 4 6 8 9 ... 155 \n", - "68 4 17 21 27 34 39 ... 149 \n", - "69 2 2 5 6 7 7 ... 45 \n", - "70 2 3 4 7 11 12 ... 75 \n", - "71 0 1 1 6 6 6 ... 18 \n", - "72 5 15 22 35 46 56 ... 308 \n", - "73 15 27 46 75 95 130 ... 792 \n", - "74 20 33 40 53 66 96 ... 672 \n", - "75 1 6 9 13 27 27 ... 198 \n", - "76 15 28 44 69 90 108 ... 564 \n", - "77 8 10 14 23 24 27 ... 192 \n", - ".. ... ... ... ... ... ... ... ... \n", - "111 0 0 0 0 0 0 ... 19 \n", - "112 0 0 0 0 0 0 ... 471 \n", - "113 0 0 0 0 0 0 ... 6 \n", - "114 0 0 0 0 0 0 ... 41 \n", - "115 0 0 0 0 0 0 ... 200 \n", - "116 2 3 3 3 4 5 ... 185616 \n", - "120 0 0 0 1 4 4 ... 183189 \n", - "133 0 0 0 0 0 0 ... 148950 \n", - "137 0 0 0 0 0 0 ... 232664 \n", - "139 2 2 4 4 7 7 ... 16716 \n", - "166 0 0 0 0 0 0 ... 101 \n", - "167 0 0 0 0 0 0 ... 19 \n", - "168 0 0 0 0 0 0 ... 77 \n", - "169 0 0 0 0 0 0 ... 46257 \n", - "184 0 0 0 0 0 0 ... 32203 \n", - "201 0 0 0 0 0 0 ... 239228 \n", - "217 0 0 0 0 0 0 ... 140 \n", - "218 0 0 0 0 0 0 ... 141 \n", - "219 0 0 0 0 0 0 ... 560 \n", - "220 0 0 0 0 0 0 ... 169 \n", - "221 0 0 0 0 0 0 ... 336 \n", - "222 0 0 0 0 0 0 ... 11 \n", - "223 0 0 0 0 0 0 ... 272826 \n", - "225 2 2 5 5 5 5 ... 1770165 \n", - "248 0 0 0 0 0 0 ... 3 \n", - "249 0 0 0 0 0 0 ... 8 \n", - "250 0 0 0 0 0 0 ... 12 \n", - "255 0 0 0 0 0 0 ... 6 \n", - "257 0 0 0 0 0 0 ... 13 \n", - "258 0 0 0 0 0 0 ... 1 \n", - "\n", - " 5/31/20 6/1/20 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 \\\n", - "23 58381 58517 58615 58685 58767 58907 59072 59226 \n", - "49 991 991 991 991 991 991 991 991 \n", - "50 593 593 593 594 594 594 594 594 \n", - "51 579 579 579 579 579 579 579 579 \n", - "52 358 358 358 358 358 358 359 359 \n", - "53 139 139 139 139 139 139 139 139 \n", - "54 1595 1596 1597 1598 1598 1601 1602 1602 \n", - "55 254 254 254 254 254 254 254 254 \n", - "56 147 147 147 147 147 147 147 147 \n", - "57 169 169 169 169 169 169 170 170 \n", - "58 328 328 328 328 328 328 328 328 \n", - "59 945 945 945 947 947 947 947 947 \n", - "60 1276 1276 1276 1276 1276 1276 1276 1276 \n", - "61 1084 1087 1093 1093 1099 1102 1105 1106 \n", - "62 68135 68135 68135 68135 68135 68135 68135 68135 \n", - "63 1019 1019 1019 1019 1019 1019 1019 1019 \n", - "64 235 235 235 235 235 235 235 235 \n", - "65 653 653 653 653 653 653 653 653 \n", - "66 937 937 937 932 932 932 932 932 \n", - "67 155 155 155 155 155 155 155 155 \n", - "68 149 149 149 149 149 149 149 149 \n", - "69 45 45 45 45 45 45 45 45 \n", - "70 75 75 75 75 75 75 75 75 \n", - "71 18 18 18 18 18 18 18 18 \n", - "72 308 309 309 309 309 309 311 311 \n", - "73 792 792 792 792 792 792 792 792 \n", - "74 672 673 673 673 677 677 677 678 \n", - "75 198 198 198 198 198 198 198 198 \n", - "76 575 577 577 577 578 578 578 581 \n", - "77 192 192 192 192 192 192 193 193 \n", - ".. ... ... ... ... ... ... ... ... \n", - "111 19 20 20 20 20 20 20 20 \n", - "112 471 473 477 478 479 480 480 480 \n", - "113 6 6 6 6 6 6 6 6 \n", - "114 41 41 41 41 41 41 41 41 \n", - "115 200 200 200 200 200 202 202 202 \n", - "116 185851 185952 184980 188836 185986 186538 187067 187360 \n", - "120 183410 183594 183879 184121 184472 184924 185450 185750 \n", - "133 151466 154445 157562 160696 164270 167156 169425 171789 \n", - "137 232997 233197 233515 233836 234013 234531 234801 234998 \n", - "139 16751 16787 16837 16867 16911 16958 17000 17039 \n", - "166 101 101 101 101 101 101 101 101 \n", - "167 19 19 20 21 21 21 21 21 \n", - "168 77 77 77 77 77 77 77 77 \n", - "169 46442 46545 46647 46733 46942 47152 47335 47574 \n", - "184 32500 32700 32895 33261 33592 33969 34351 34693 \n", - "201 239479 239638 239932 240326 240660 240978 241310 241550 \n", - "217 140 141 141 141 141 141 141 141 \n", - "218 141 150 151 156 160 164 164 164 \n", - "219 560 560 560 561 561 561 563 563 \n", - "220 170 170 172 173 173 174 175 176 \n", - "221 336 336 336 336 336 336 336 336 \n", - "222 11 11 11 11 11 11 11 11 \n", - "223 274762 276332 277985 279856 281661 283311 284868 286194 \n", - "225 1790172 1811020 1831821 1851520 1872660 1897380 1920061 1943647 \n", - "248 3 3 3 3 3 3 3 3 \n", - "249 8 8 8 8 8 8 8 8 \n", - "250 12 12 12 12 12 12 12 12 \n", - "255 6 7 7 7 7 7 7 7 \n", - "257 13 13 13 13 13 13 13 13 \n", - "258 1 1 1 1 1 1 1 1 \n", - "\n", - " 6/8/20 \n", - "23 59348 \n", - "49 991 \n", - "50 594 \n", - "51 579 \n", - "52 359 \n", - "53 139 \n", - "54 1604 \n", - "55 254 \n", - "56 147 \n", - "57 170 \n", - "58 328 \n", - "59 947 \n", - "60 1276 \n", - "61 1107 \n", - "62 68135 \n", - "63 1019 \n", - "64 235 \n", - "65 653 \n", - "66 932 \n", - "67 155 \n", - "68 149 \n", - "69 45 \n", - "70 75 \n", - "71 18 \n", - "72 311 \n", - "73 792 \n", - "74 678 \n", - "75 198 \n", - "76 582 \n", - "77 193 \n", - ".. ... \n", - "111 20 \n", - "112 481 \n", - "113 6 \n", - "114 41 \n", - "115 202 \n", - "116 187458 \n", - "120 186109 \n", - "133 173832 \n", - "137 235278 \n", - "139 17060 \n", - "166 101 \n", - "167 21 \n", - "168 77 \n", - "169 47739 \n", - "184 34885 \n", - "201 241717 \n", - "217 141 \n", - "218 171 \n", - "219 564 \n", - "220 176 \n", - "221 336 \n", - "222 11 \n", - "223 287399 \n", - "225 1960897 \n", - "248 3 \n", - "249 8 \n", - "250 12 \n", - "255 7 \n", - "257 13 \n", - "258 1 \n", - "\n", - "[68 rows x 141 columns]\n" - ] - }, { "name": "stderr", "output_type": "stream", @@ -2679,8 +1897,7 @@ } ], "source": [ - "df=df.set_value(df[(df['Province/State'] == 'Hong Kong')].index, 'Country/Region', 'Hong Kong')\n", - "print(df)" + "df=df.set_value(df[(df['Province/State'] == 'Hong Kong')].index, 'Country/Region', 'Hong Kong')\n" ] }, { @@ -2694,153 +1911,7 @@ "cell_type": "code", "execution_count": 7, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Province/State Country/Region 1/22/20 1/23/20 1/24/20 1/25/20 \\\n", - "23 NaN Belgium 0 0 0 0 \n", - "49 Anhui China 1 9 15 39 \n", - "50 Beijing China 14 22 36 41 \n", - "51 Chongqing China 6 9 27 57 \n", - "52 Fujian China 1 5 10 18 \n", - "53 Gansu China 0 2 2 4 \n", - "54 Guangdong China 26 32 53 78 \n", - "55 Guangxi China 2 5 23 23 \n", - "56 Guizhou China 1 3 3 4 \n", - "57 Hainan China 4 5 8 19 \n", - "58 Hebei China 1 1 2 8 \n", - "59 Heilongjiang China 0 2 4 9 \n", - "60 Henan China 5 5 9 32 \n", - "61 Hong Kong Hong Kong 0 2 2 5 \n", - "62 Hubei China 444 444 549 761 \n", - "63 Hunan China 4 9 24 43 \n", - "64 Inner Mongolia China 0 0 1 7 \n", - "65 Jiangsu China 1 5 9 18 \n", - "66 Jiangxi China 2 7 18 18 \n", - "67 Jilin China 0 1 3 4 \n", - "68 Liaoning China 2 3 4 17 \n", - "69 Macau China 1 2 2 2 \n", - "70 Ningxia China 1 1 2 3 \n", - "71 Qinghai China 0 0 0 1 \n", - "72 Shaanxi China 0 3 5 15 \n", - "73 Shandong China 2 6 15 27 \n", - "74 Shanghai China 9 16 20 33 \n", - "75 Shanxi China 1 1 1 6 \n", - "76 Sichuan China 5 8 15 28 \n", - "77 Tianjin China 4 4 8 10 \n", - "78 Tibet China 0 0 0 0 \n", - "79 Xinjiang China 0 2 2 3 \n", - "80 Yunnan China 1 2 5 11 \n", - "81 Zhejiang China 10 27 43 62 \n", - "116 NaN France 0 0 2 3 \n", - "120 NaN Germany 0 0 0 0 \n", - "133 NaN Iran 0 0 0 0 \n", - "137 NaN Italy 0 0 0 0 \n", - "139 NaN Japan 2 2 2 2 \n", - "169 NaN Netherlands 0 0 0 0 \n", - "184 NaN Portugal 0 0 0 0 \n", - "201 NaN Spain 0 0 0 0 \n", - "223 NaN United Kingdom 0 0 0 0 \n", - "225 NaN US 1 1 2 2 \n", - "\n", - " 1/26/20 1/27/20 1/28/20 1/29/20 ... 5/30/20 5/31/20 6/1/20 \\\n", - "23 0 0 0 0 ... 58186 58381 58517 \n", - "49 60 70 106 152 ... 991 991 991 \n", - "50 68 80 91 111 ... 593 593 593 \n", - "51 75 110 132 147 ... 579 579 579 \n", - "52 35 59 80 84 ... 358 358 358 \n", - "53 7 14 19 24 ... 139 139 139 \n", - "54 111 151 207 277 ... 1593 1595 1596 \n", - "55 36 46 51 58 ... 254 254 254 \n", - "56 5 7 9 9 ... 147 147 147 \n", - "57 22 33 40 43 ... 169 169 169 \n", - "58 13 18 33 48 ... 328 328 328 \n", - "59 15 21 33 38 ... 945 945 945 \n", - "60 83 128 168 206 ... 1276 1276 1276 \n", - "61 8 8 8 10 ... 1082 1084 1087 \n", - "62 1058 1423 3554 3554 ... 68135 68135 68135 \n", - "63 69 100 143 221 ... 1019 1019 1019 \n", - "64 7 11 15 16 ... 232 235 235 \n", - "65 33 47 70 99 ... 653 653 653 \n", - "66 36 72 109 109 ... 937 937 937 \n", - "67 4 6 8 9 ... 155 155 155 \n", - "68 21 27 34 39 ... 149 149 149 \n", - "69 5 6 7 7 ... 45 45 45 \n", - "70 4 7 11 12 ... 75 75 75 \n", - "71 1 6 6 6 ... 18 18 18 \n", - "72 22 35 46 56 ... 308 308 309 \n", - "73 46 75 95 130 ... 792 792 792 \n", - "74 40 53 66 96 ... 672 672 673 \n", - "75 9 13 27 27 ... 198 198 198 \n", - "76 44 69 90 108 ... 564 575 577 \n", - "77 14 23 24 27 ... 192 192 192 \n", - "78 0 0 0 0 ... 1 1 1 \n", - "79 4 5 10 13 ... 76 76 76 \n", - "80 16 26 44 55 ... 185 185 185 \n", - "81 104 128 173 296 ... 1268 1268 1268 \n", - "116 3 3 4 5 ... 185616 185851 185952 \n", - "120 0 1 4 4 ... 183189 183410 183594 \n", - "133 0 0 0 0 ... 148950 151466 154445 \n", - "137 0 0 0 0 ... 232664 232997 233197 \n", - "139 4 4 7 7 ... 16716 16751 16787 \n", - "169 0 0 0 0 ... 46257 46442 46545 \n", - "184 0 0 0 0 ... 32203 32500 32700 \n", - "201 0 0 0 0 ... 239228 239479 239638 \n", - "223 0 0 0 0 ... 272826 274762 276332 \n", - "225 5 5 5 5 ... 1770165 1790172 1811020 \n", - "\n", - " 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 6/8/20 \n", - "23 58615 58685 58767 58907 59072 59226 59348 \n", - "49 991 991 991 991 991 991 991 \n", - "50 593 594 594 594 594 594 594 \n", - "51 579 579 579 579 579 579 579 \n", - "52 358 358 358 358 359 359 359 \n", - "53 139 139 139 139 139 139 139 \n", - "54 1597 1598 1598 1601 1602 1602 1604 \n", - "55 254 254 254 254 254 254 254 \n", - "56 147 147 147 147 147 147 147 \n", - "57 169 169 169 169 170 170 170 \n", - "58 328 328 328 328 328 328 328 \n", - "59 945 947 947 947 947 947 947 \n", - "60 1276 1276 1276 1276 1276 1276 1276 \n", - "61 1093 1093 1099 1102 1105 1106 1107 \n", - "62 68135 68135 68135 68135 68135 68135 68135 \n", - "63 1019 1019 1019 1019 1019 1019 1019 \n", - "64 235 235 235 235 235 235 235 \n", - "65 653 653 653 653 653 653 653 \n", - "66 937 932 932 932 932 932 932 \n", - "67 155 155 155 155 155 155 155 \n", - "68 149 149 149 149 149 149 149 \n", - "69 45 45 45 45 45 45 45 \n", - "70 75 75 75 75 75 75 75 \n", - "71 18 18 18 18 18 18 18 \n", - "72 309 309 309 309 311 311 311 \n", - "73 792 792 792 792 792 792 792 \n", - "74 673 673 677 677 677 678 678 \n", - "75 198 198 198 198 198 198 198 \n", - "76 577 577 578 578 578 581 582 \n", - "77 192 192 192 192 193 193 193 \n", - "78 1 1 1 1 1 1 1 \n", - "79 76 76 76 76 76 76 76 \n", - "80 185 185 185 185 185 185 185 \n", - "81 1268 1268 1268 1268 1268 1268 1268 \n", - "116 184980 188836 185986 186538 187067 187360 187458 \n", - "120 183879 184121 184472 184924 185450 185750 186109 \n", - "133 157562 160696 164270 167156 169425 171789 173832 \n", - "137 233515 233836 234013 234531 234801 234998 235278 \n", - "139 16837 16867 16911 16958 17000 17039 17060 \n", - "169 46647 46733 46942 47152 47335 47574 47739 \n", - "184 32895 33261 33592 33969 34351 34693 34885 \n", - "201 239932 240326 240660 240978 241310 241550 241717 \n", - "223 277985 279856 281661 283311 284868 286194 287399 \n", - "225 1831821 1851520 1872660 1897380 1920061 1943647 1960897 \n", - "\n", - "[44 rows x 141 columns]\n" - ] - } - ], + "outputs": [], "source": [ "fr=df[(df['Country/Region']=='France')]\n", "fr=fr['Province/State']\n", @@ -2856,10 +1927,7 @@ "\n", "df=df.drop(fr.index)\n", "df=df.drop(ne.index)\n", - "df=df.drop(uk.index)\n", - "\n", - "\n", - "print(df)\n" + "df=df.drop(uk.index)\n" ] }, { @@ -2873,68 +1941,11 @@ "cell_type": "code", "execution_count": 8, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 1/22/20 1/23/20 1/24/20 1/25/20 1/26/20 1/27/20 1/28/20 \\\n", - "Country/Region \n", - "Belgium 0 0 0 0 0 0 0 \n", - "China 548 641 918 1401 2067 2869 5501 \n", - "France 0 0 2 3 3 3 4 \n", - "Germany 0 0 0 0 0 1 4 \n", - "Hong Kong 0 2 2 5 8 8 8 \n", - "Iran 0 0 0 0 0 0 0 \n", - "Italy 0 0 0 0 0 0 0 \n", - "Japan 2 2 2 2 4 4 7 \n", - "Netherlands 0 0 0 0 0 0 0 \n", - "Portugal 0 0 0 0 0 0 0 \n", - "Spain 0 0 0 0 0 0 0 \n", - "US 1 1 2 2 5 5 5 \n", - "United Kingdom 0 0 0 0 0 0 0 \n", - "\n", - " 1/29/20 1/30/20 1/31/20 ... 5/30/20 5/31/20 6/1/20 \\\n", - "Country/Region ... \n", - "Belgium 0 0 0 ... 58186 58381 58517 \n", - "China 6077 8131 9790 ... 83046 83062 83067 \n", - "France 5 5 5 ... 185616 185851 185952 \n", - "Germany 4 4 5 ... 183189 183410 183594 \n", - "Hong Kong 10 10 12 ... 1082 1084 1087 \n", - "Iran 0 0 0 ... 148950 151466 154445 \n", - "Italy 0 0 2 ... 232664 232997 233197 \n", - "Japan 7 11 15 ... 16716 16751 16787 \n", - "Netherlands 0 0 0 ... 46257 46442 46545 \n", - "Portugal 0 0 0 ... 32203 32500 32700 \n", - "Spain 0 0 0 ... 239228 239479 239638 \n", - "US 5 5 7 ... 1770165 1790172 1811020 \n", - "United Kingdom 0 0 2 ... 272826 274762 276332 \n", - "\n", - " 6/2/20 6/3/20 6/4/20 6/5/20 6/6/20 6/7/20 6/8/20 \n", - "Country/Region \n", - "Belgium 58615 58685 58767 58907 59072 59226 59348 \n", - "China 83068 83067 83072 83075 83081 83085 83088 \n", - "France 184980 188836 185986 186538 187067 187360 187458 \n", - "Germany 183879 184121 184472 184924 185450 185750 186109 \n", - "Hong Kong 1093 1093 1099 1102 1105 1106 1107 \n", - "Iran 157562 160696 164270 167156 169425 171789 173832 \n", - "Italy 233515 233836 234013 234531 234801 234998 235278 \n", - "Japan 16837 16867 16911 16958 17000 17039 17060 \n", - "Netherlands 46647 46733 46942 47152 47335 47574 47739 \n", - "Portugal 32895 33261 33592 33969 34351 34693 34885 \n", - "Spain 239932 240326 240660 240978 241310 241550 241717 \n", - "US 1831821 1851520 1872660 1897380 1920061 1943647 1960897 \n", - "United Kingdom 277985 279856 281661 283311 284868 286194 287399 \n", - "\n", - "[13 rows x 139 columns]\n" - ] - } - ], + "outputs": [], "source": [ "df.drop('Province/State', axis = 1, inplace = True)\n", "grouped=df.groupby('Country/Region')\n", - "df=grouped.sum()\n", - "print(df)" + "df=grouped.sum()" ] }, { -- 2.18.1