{"id":31815,"date":"2023-01-24T22:41:36","date_gmt":"2023-01-24T17:11:36","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/"},"modified":"2023-01-24T22:41:36","modified_gmt":"2023-01-24T17:11:36","slug":"solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/","title":{"rendered":"[Solved] How to compute the ratio of Recovered Cases to Confirmed Cases for each nation using pandas in 8 lines [closed]"},"content":{"rendered":"

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Computing the ratio<\/h2>\n

Since there are multiple regions in a country, there are duplicated values in the Country_Region<\/code> column. Therefore, I use groupby<\/code> to sum the total cases of a nation.<\/p>\n

ratio = df.groupby(\"Country_Region\")[[\"Recovered\", \"Confirmed\"]].sum()\nratio[\"Ratio\"] = ratio[\"Recovered\"] \/ ratio[\"Confirmed\"]\n<\/code><\/pre>\n
Let’s get the first five nations.<\/p>\n
>>> ratio.head()\n\n                Recovered  Confirmed     Ratio\nCountry_Region                                \nAfghanistan         41727      52513  0.794603\nAlbania             33634      58316  0.576754\nAlgeria             67395      99897  0.674645\nAndorra              7463       8117  0.919428\nAngola              11146      17568  0.634449\n<\/code><\/pre>\n
Getting the countries with the highest ratio<\/h2>\n
Then, you can filter out the ten countries with the highest ratio with Series.nlargest<\/code><\/a>.<\/p>\n
>>> ratio.nlargest(10, \"Ratio\")\n\n                  Recovered  Confirmed     Ratio\nCountry_Region                                  \nMarshall Islands          4          4  1.000000\nSamoa                     2          2  1.000000\nVanuatu                   1          1  1.000000\nSingapore             58449      58629  0.996930\nEl Salvador           45960      46515  0.988068\nQatar                141556     144042  0.982741\nDjibouti               5735       5840  0.982021\nDiamond Princess        699        712  0.981742\nGabon                  9388       9571  0.980880\nGhana                 53758      54930  0.978664\n<\/code><\/pre>\n<\/p><\/div>\n
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            <\/span> <\/p><\/div>\n<\/div>\n
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solved How to compute the ratio of Recovered Cases to Confirmed Cases for each nation using pandas in 8 lines [closed] <\/p>\n","protected":false},"excerpt":{"rendered":"
[ad_1] Computing the ratio Since there are multiple regions in a country, there are duplicated values in the Country_Region column. Therefore, I use groupby to sum the total cases of a nation. ratio = df.groupby(“Country_Region”)[[“Recovered”, “Confirmed”]].sum() ratio[“Ratio”] = ratio[“Recovered”] \/ ratio[“Confirmed”] Let’s get the first five nations. >>> ratio.head() Recovered Confirmed Ratio Country_Region Afghanistan 41727 … Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[320],"tags":[415,349],"class_list":["post-31815","post","type-post","status-publish","format-standard","hentry","category-solved","tag-pandas","tag-python"],"yoast_head":"\n[Solved] How to compute the ratio of Recovered Cases to Confirmed Cases for each nation using pandas in 8 lines [closed] - JassWeb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] How to compute the ratio of Recovered Cases to Confirmed Cases for each nation using pandas in 8 lines [closed] - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] Computing the ratio Since there are multiple regions in a country, there are duplicated values in the Country_Region column. Therefore, I use groupby to sum the total cases of a nation. ratio = df.groupby("Country_Region")[["Recovered", "Confirmed"]].sum() ratio["Ratio"] = ratio["Recovered"] \/ ratio["Confirmed"] Let’s get the first five nations. >>> ratio.head() Recovered Confirmed Ratio Country_Region Afghanistan 41727 ... Read more\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/\" \/>\n<meta property=\"og:site_name\" content=\"JassWeb\" \/>\n<meta property=\"article:published_time\" content=\"2023-01-24T17:11:36+00:00\" \/>\n<meta name=\"author\" content=\"Kirat\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Kirat\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/\"},\"author\":{\"name\":\"Kirat\",\"@id\":\"https:\/\/jassweb.com\/solved\/#\/schema\/person\/65c9c7b7958150c0dc8371fa35dd7c31\"},\"headline\":\"[Solved] How to compute the ratio of Recovered Cases to Confirmed Cases for each nation using pandas in 8 lines [closed]\",\"datePublished\":\"2023-01-24T17:11:36+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/\"},\"wordCount\":98,\"publisher\":{\"@id\":\"https:\/\/jassweb.com\/solved\/#organization\"},\"keywords\":[\"pandas\",\"python\"],\"articleSection\":[\"Solved\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/\",\"url\":\"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/\",\"name\":\"[Solved] How to compute the ratio of Recovered Cases to Confirmed Cases for each nation using pandas in 8 lines [closed] - 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JassWeb","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/jassweb.com\/solved\/solved-how-to-compute-the-ratio-of-recovered-cases-to-confirmed-cases-for-each-nation-using-pandas-in-8-lines-closed\/","og_locale":"en_US","og_type":"article","og_title":"[Solved] How to compute the ratio of Recovered Cases to Confirmed Cases for each nation using pandas in 8 lines [closed] - JassWeb","og_description":"[ad_1] Computing the ratio Since there are multiple regions in a country, there are duplicated values in the Country_Region column. Therefore, I use groupby to sum the total cases of a nation. ratio = df.groupby(\"Country_Region\")[[\"Recovered\", \"Confirmed\"]].sum() ratio[\"Ratio\"] = ratio[\"Recovered\"] \/ ratio[\"Confirmed\"] Let’s get the first five nations. >>> ratio.head() Recovered Confirmed Ratio Country_Region Afghanistan 41727 ... 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