{"id":8022,"date":"2022-09-11T12:39:45","date_gmt":"2022-09-11T07:09:45","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/"},"modified":"2022-09-11T12:39:45","modified_gmt":"2022-09-11T07:09:45","slug":"solved-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/","title":{"rendered":"[Solved] Merge rows with same names and sum other values in other column rows [duplicate]"},"content":{"rendered":"

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We could first group_by<\/code> country<\/code><\/p>\n

and then use summarise<\/code> with across<\/code><\/p>\n

library(dplyr)\ndf %>% \n  group_by(country) %>% \n  summarise(across(everything(), sum))\n<\/code><\/pre>\n
Output:<\/p>\n
 country new_persons_vac~ total_persons_v~ new_persons_ful~ total_persons_f~ new_vaccine_dos~ total_vaccine_d~\n   <chr>              <dbl>            <dbl>            <dbl>            <dbl>            <dbl>            <dbl>\n 1 Afghan~           294056          8452317           163535          2313338           457591         10765655\n 2 Albania           601152         27639676           465433         18105836           459226         45745512\n 3 Andorra            40569           360995            25838           144358            58535           506402\n 4 Angola            371996          9545624           559633          4688357           931629         14233981\n 5 Anguil~             3206            73046             6847            48524            10053           121570\n 6 Antigu~             5232           770379            26084           485839            31316          1256218\n 7 Argent~         65820302       3858592405         16136889        917220373         81957191       4775812778\n 8 Armenia           138306           426851            58214           135848           196520           562699\n 9 Aruba              55435          4907836            52549          3439184           107984          8347020\n10 Austra~         14227655        811027845          5722445        163311327         19238830        974339172\n# ... with 183 more rows\n<\/code><\/pre>\n
head of data:<\/p>\n
df <- structure(list(country = c(\"Brazil\", \"Brazil\", \"Brazil\", \"Brazil\", \n\"Brazil\", \"Brazil\"), new_persons_vaccinated = c(1, 1, 1, 1, 1, \n1), total_persons_vaccinated = c(1, 1, 1, 2, 1, 1), new_persons_fully_vaccinated = c(0, \n0, 0, 0, 0, 0), total_persons_fully_vaccinated = c(0, 0, 0, 0, \n0, 0), new_vaccine_doses_administered = c(1, 1, 1, 1, 1, 1), \n    total_vaccine_doses_administered = c(1, 1, 1, 2, 1, 1)), row.names = c(NA, \n-6L), class = c(\"tbl_df\", \"tbl\", \"data.frame\"))\n<\/code><\/pre>\n<\/p><\/div>\n
<\/div>\n<\/div>\n
            7<\/span> <\/p><\/div>\n<\/div>\n
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solved Merge rows with same names and sum other values in other column rows [duplicate] <\/p>\n","protected":false},"excerpt":{"rendered":"
[ad_1] We could first group_by country and then use summarise with across library(dplyr) df %>% group_by(country) %>% summarise(across(everything(), sum)) Output: country new_persons_vac~ total_persons_v~ new_persons_ful~ total_persons_f~ new_vaccine_dos~ total_vaccine_d~ <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Afghan~ 294056 8452317 163535 2313338 457591 10765655 2 Albania 601152 27639676 465433 18105836 459226 45745512 3 Andorra 40569 360995 25838 … 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":[321],"class_list":["post-8022","post","type-post","status-publish","format-standard","hentry","category-solved","tag-r"],"yoast_head":"\n[Solved] Merge rows with same names and sum other values in other column rows [duplicate] - 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-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] Merge rows with same names and sum other values in other column rows [duplicate] - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] We could first group_by country and then use summarise with across library(dplyr) df %>% group_by(country) %>% summarise(across(everything(), sum)) Output: country new_persons_vac~ total_persons_v~ new_persons_ful~ total_persons_f~ new_vaccine_dos~ total_vaccine_d~ <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Afghan~ 294056 8452317 163535 2313338 457591 10765655 2 Albania 601152 27639676 465433 18105836 459226 45745512 3 Andorra 40569 360995 25838 ... Read more\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jassweb.com\/solved\/solved-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/\" \/>\n<meta property=\"og:site_name\" content=\"JassWeb\" \/>\n<meta property=\"article:published_time\" content=\"2022-09-11T07:09:45+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-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/jassweb.com\/solved\/solved-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/\"},\"author\":{\"name\":\"Kirat\",\"@id\":\"https:\/\/jassweb.com\/solved\/#\/schema\/person\/65c9c7b7958150c0dc8371fa35dd7c31\"},\"headline\":\"[Solved] Merge rows with same names and sum other values in other column rows [duplicate]\",\"datePublished\":\"2022-09-11T07:09:45+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/jassweb.com\/solved\/solved-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/\"},\"wordCount\":43,\"publisher\":{\"@id\":\"https:\/\/jassweb.com\/solved\/#organization\"},\"keywords\":[\"r\"],\"articleSection\":[\"Solved\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jassweb.com\/solved\/solved-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/\",\"url\":\"https:\/\/jassweb.com\/solved\/solved-merge-rows-with-same-names-and-sum-other-values-in-other-column-rows-duplicate\/\",\"name\":\"[Solved] Merge rows with same names and sum other values in other column rows [duplicate] - 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