{"id":20665,"date":"2022-11-10T11:30:29","date_gmt":"2022-11-10T06:00:29","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-how-to-count-the-numbers-based-on-two-columns\/"},"modified":"2022-11-10T11:30:29","modified_gmt":"2022-11-10T06:00:29","slug":"solved-how-to-count-the-numbers-based-on-two-columns","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-how-to-count-the-numbers-based-on-two-columns\/","title":{"rendered":"[Solved] how to count the numbers based on two columns"},"content":{"rendered":"

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The table<\/code> command does what you want:<\/p>\n

table(df$V1, df$V2, useNA = \"ifany\")\n<\/code><\/pre>\n
Table will work on all distinct values. If you want blanks \"\"<\/code> to be equivalent to missing values NA<\/code>, you need to make that change in your data:<\/p>\n
df[df == \"\"] = NA\n<\/code><\/pre>\n
Similarly, if the 1 x<\/code> or 2 x<\/code> doesn’t matter, get rid of them. Maybe add a new column<\/p>\n
df$goodname = gsub(pattern = \"^[0-9]+ x \", replacement = \"\", x = df$V1)\n\ntable(df$goodname, df$V2, useNA = \"ifany\")\n            BUX1_T10963 BUX1_T10964 BUX1_T10965 BUX1_T10966 BUX2_T10076\n  Bruit (U)           3           5           3           5           1\n  TAMAN (M)           0           0           1           0           0\n  TIKIam(T)           0           0           0           3           0\n  <NA>                0           4           1           2           0\n<\/code><\/pre>\n
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Pulling out the quantity into its own column and tabulating:<\/p>\n
library(stringr)\n# extract the number\ndf$quantity = as.numeric(str_extract(df$V1, \"^[0-9]+\"))\n# any missing values assume to be 1\ndf$quantity[is.na(df$quantity)] = 1\n\nlibrary(reshape2)\ndcast(data = df, formula = goodname ~ V2, value.var = \"quantity\", fun.aggregate = sum, na.rm = T)\n#    goodname BUX1_T10963 BUX1_T10964 BUX1_T10965 BUX1_T10966 BUX2_T10076\n# 1 Bruit (U)           5           9           4           6           2\n# 2 TAMAN (M)           0           0           1           0           0\n# 3 TIKIam(T)           0           0           0           6           0\n# 4      <NA>           0           4           1           2           0\n<\/code><\/pre>\n<\/p><\/div>\n
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solved how to count the numbers based on two columns <\/p>\n","protected":false},"excerpt":{"rendered":"
[ad_1] The table command does what you want: table(df$V1, df$V2, useNA = “ifany”) Table will work on all distinct values. If you want blanks “” to be equivalent to missing values NA, you need to make that change in your data: df[df == “”] = NA Similarly, if the 1 x or 2 x doesn’t … 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-20665","post","type-post","status-publish","format-standard","hentry","category-solved","tag-r"],"yoast_head":"\n[Solved] how to count the numbers based on two columns - 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-count-the-numbers-based-on-two-columns\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] how to count the numbers based on two columns - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] The table command does what you want: table(df$V1, df$V2, useNA = "ifany") Table will work on all distinct values. 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If you want blanks \"\" to be equivalent to missing values NA, you need to make that change in your data: df[df == \"\"] = NA Similarly, if the 1 x or 2 x doesn’t ... 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