使用 mutate_at 创建新变量，同时保留原始变量

您可以为传递给 .funs 的列表中的函数命名，以创建带有后缀名称的新变量.dataframe %>% mutate_at(vars(contains('oo')), .funs = list(cat = ~ntile(., 2)))# 小费:6 x 5你好 ooooHH 啊哈 hello_cat ooooHH_cat<dbl><dbl><dbl><int><int>1 1 1 200 1 12 2 1 400 1 13 3 1 120 1 14 4 2 300 2 25 5 2 100 2 26 6 2 100 2 2如果您希望将其作为前缀，则可以使用 rename_at 来更改名称.数据帧%>%mutate_at(vars(contains('oo')), .funs = list(cat = ~ntile(., 2))) %>%rename_at( vars( contains( "_cat") ), list( ~paste("cat", gsub("_cat", "", .), sep = "_") ) )# 小费:6 x 5你好 ooooHH ahaaa cat_helloo cat_ooooHH<dbl><dbl><dbl><int><int>1 1 1 200 1 12 2 1 400 1 13 3 1 120 1 14 4 2 300 2 25 5 2 100 2 26 6 2 100 2 2带有 funs() 的先前代码来自 dplyr 的早期版本:数据帧%>%mutate_at(vars(contains('oo')), .funs = funs(cat = ntile(., 2))) %>%rename_at( vars( contains( "_cat") ), funs( paste("cat", gsub("_cat", "", .), sep = "_") ) )Consider this simple example:library(dplyr)dataframe <- data_frame(helloo = c(1,2,3,4,5,6), ooooHH = c(1,1,1,2,2,2), ahaaa = c(200,400,120,300,100,100))# A tibble: 6 x 3 helloo ooooHH ahaaa <dbl> <dbl> <dbl>1 1 1 2002 2 1 4003 3 1 1204 4 2 3005 5 2 1006 6 2 100Here I want to apply the function ntile to all the columns that contains oo, but I would like these new columns to be called cat + the corresponding column.I know I can do thisdataframe %>% mutate_at(vars(contains('oo')), .funs = funs(ntile(., 2)))# A tibble: 6 x 3 helloo ooooHH ahaaa <int> <int> <dbl>1 1 1 2002 1 1 4003 1 1 1204 2 2 3005 2 2 1006 2 2 100But what I need is this# A tibble: 8 x 5 helloo ooooHH ahaaa cat_helloo cat_ooooHH <dbl> <dbl> <dbl> <int> <int>1 1 1 200 1 12 2 1 400 1 13 3 1 120 1 14 4 2 300 2 25 5 2 100 2 26 5 2 100 2 27 6 2 100 2 28 6 2 100 2 2Is there a solution that does NOT require to store the intermediate data, and merge back to the original dataframe? 解决方案 Update 2020-06 for dplyr 1.0.0Starting in dplyr 1.0.0, the across() function supersedes the "scoped variants" of functions such as mutate_at(). The code should look pretty familiar within across(), which is nested inside mutate(). Adding a name to the function(s) you give in the list adds the function name as a suffix.dataframe %>% mutate( across(contains('oo'), .fns = list(cat = ~ntile(., 2))) )# A tibble: 6 x 5 helloo ooooHH ahaaa helloo_cat ooooHH_cat <dbl> <dbl> <dbl> <int> <int>1 1 1 200 1 12 2 1 400 1 13 3 1 120 1 14 4 2 300 2 25 5 2 100 2 26 6 2 100 2 2Changing the new columns names is a little easier in 1.0.0 with the .names argument in across(). Here is an example of adding the function name as a prefix instead of a suffix. This uses glue syntax.dataframe %>% mutate( across(contains('oo'), .fns = list(cat = ~ntile(., 2)), .names = "{fn}_{col}" ) )# A tibble: 6 x 5 helloo ooooHH ahaaa cat_helloo cat_ooooHH <dbl> <dbl> <dbl> <int> <int>1 1 1 200 1 12 2 1 400 1 13 3 1 120 1 14 4 2 300 2 25 5 2 100 2 26 6 2 100 2 2Original answer with mutate_at()Edited to reflect changes in dplyr. As of dplyr 0.8.0, funs() is deprecated and list() with ~ should be used instead.You can give names to the functions to the list you pass to .funs to make new variables with the names as suffixes attached.dataframe %>% mutate_at(vars(contains('oo')), .funs = list(cat = ~ntile(., 2)))# A tibble: 6 x 5 helloo ooooHH ahaaa helloo_cat ooooHH_cat <dbl> <dbl> <dbl> <int> <int>1 1 1 200 1 12 2 1 400 1 13 3 1 120 1 14 4 2 300 2 25 5 2 100 2 26 6 2 100 2 2If you want it as a prefix instead, you could then use rename_at to change the names.dataframe %>% mutate_at(vars(contains('oo')), .funs = list(cat = ~ntile(., 2))) %>% rename_at( vars( contains( "_cat") ), list( ~paste("cat", gsub("_cat", "", .), sep = "_") ) )# A tibble: 6 x 5 helloo ooooHH ahaaa cat_helloo cat_ooooHH <dbl> <dbl> <dbl> <int> <int>1 1 1 200 1 12 2 1 400 1 13 3 1 120 1 14 4 2 300 2 25 5 2 100 2 26 6 2 100 2 2Previous code with funs() from earlier versions of dplyr:dataframe %>% mutate_at(vars(contains('oo')), .funs = funs(cat = ntile(., 2))) %>% rename_at( vars( contains( "_cat") ), funs( paste("cat", gsub("_cat", "", .), sep = "_") ) ) 这篇关于使用 mutate_at 创建新变量，同时保留原始变量的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！