{"id":13365,"date":"2022-10-03T20:58:16","date_gmt":"2022-10-03T15:28:16","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-selecting-column-sequences-and-creating-variables\/"},"modified":"2022-10-03T20:58:16","modified_gmt":"2022-10-03T15:28:16","slug":"solved-selecting-column-sequences-and-creating-variables","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-selecting-column-sequences-and-creating-variables\/","title":{"rendered":"[Solved] Selecting column sequences and creating variables"},"content":{"rendered":"

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We could split<\/code> the dataset (‘df’) with ‘1416’ columns to equal size ‘118’ columns by creating a grouping index with gl<\/code> <\/p>\n

 lst <- setNames(lapply(split(1:ncol(df), as.numeric(gl(ncol(df), 118,\n            ncol(df)))), function(i) df[,i]), paste0('site', 1:12))\n<\/code><\/pre>\n
Or you can create the ‘lst’ without using the split<\/code><\/p>\n
 lst <- setNames(lapply(seq(1, ncol(df), by = 118), \n            function(i) df[i:(i+117)]), paste0('site', 1:12))\n<\/code><\/pre>\n
If we need to create 12 dataset objects in the global environment, list2env<\/code> is an option (I would prefer to work within the ‘lst’ itself) <\/p>\n
 list2env(lst, envir=.GlobalEnv)\n<\/code><\/pre>\n
Using a small dataset (‘df1’) with ‘8’ columns<\/p>\n
  lst1 <- setNames(lapply(split(1:ncol(df1), as.numeric(gl(ncol(df1), \n         2, ncol(df1)))), function(i) df1[,i]), paste0('site', 1:4))\n  list2env(lst1, envir=.GlobalEnv)\n\n  head(site1,3)\n  #  V1 V2\n  #1  6 12\n  #2  4  7\n  #3 14 14\n\n head(site4,3)\n #  V7 V8\n #1 10  2\n #2  5  4\n #3  5  0\n<\/code><\/pre>\n
data<\/h3>\n
set.seed(24)\ndf1 <- as.data.frame(matrix(sample(0:20, 8*10, replace=TRUE), ncol=8))\n<\/code><\/pre>\n<\/p><\/div>\n
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            3<\/span> <\/p><\/div>\n<\/div>\n
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solved Selecting column sequences and creating variables <\/p>\n","protected":false},"excerpt":{"rendered":"
[ad_1] We could split the dataset (‘df’) with ‘1416’ columns to equal size ‘118’ columns by creating a grouping index with gl lst <- setNames(lapply(split(1:ncol(df), as.numeric(gl(ncol(df), 118, ncol(df)))), function(i) df[,i]), paste0(‘site’, 1:12)) Or you can create the ‘lst’ without using the split lst <- setNames(lapply(seq(1, ncol(df), by = 118), function(i) df[i:(i+117)]), paste0(‘site’, 1:12)) If we … 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":[461,321,3510],"class_list":["post-13365","post","type-post","status-publish","format-standard","hentry","category-solved","tag-dataframe","tag-r","tag-seq"],"yoast_head":"\n[Solved] Selecting column sequences and creating variables - 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-selecting-column-sequences-and-creating-variables\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] Selecting column sequences and creating variables - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] We could split the dataset (‘df’) with ‘1416’ columns to equal size ‘118’ columns by creating a grouping index with gl lst <- setNames(lapply(split(1:ncol(df), as.numeric(gl(ncol(df), 118, ncol(df)))), function(i) df[,i]), paste0('site', 1:12)) Or you can create the ‘lst’ without using the split lst <- setNames(lapply(seq(1, ncol(df), by = 118), function(i) df[i:(i+117)]), paste0('site', 1:12)) If we ... 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