基于R中的模式合并列 [英] Coalesce columns based on pattern in R

问题描述

我在R中组合了数据集，并且每个数据集可能对同一数据使用不同的列名。我需要使用正则表达式来标识需要合并的列的名称，然后通过合并来运行该列名称列表。

I have combined data sets in R, and each data set may use a different column name for the same data. I need to use a regular expression to identify the names of the columns I need to combine, and then run that list of column names through coalesce.

我知道正确的正则表达式表达式来标识我的列，我知道如何将列名称手动写入合并函数以组合这些列，但是我不知道如何自动合并用正则表达式标识的列。

I know the proper regex expression to identify my columns, and I know how to manually write the column names into the coalesce function to combine these columns, but I do not know how to automatically coalesce columns identified with a regular expression.

sample = data.frame("PIDno" = c('a', NA, NA), "PINID" = c(NA, 'b', NA), "ParcelId" = c(NA, NA, 'c'))

PID_search = paste("sample$",grep("*PID*|*PIN*|*PARCEL*",colnames(sample),ignore.case = TRUE, value = TRUE),sep = "")

sample$PID_combine = coalesce(sample$'PIDno',
                              sample$'PINID',
                              sample$'ParcelId')

推荐答案

我们可以使用 tidyverse 。选定的列将被转换为字符，其中 mutate_at ，然后是 coalesce mutate

We can use tidyverse. The selected columns are converted to character with mutate_at, then coalesce those columns in mutate

library(tidyverse)
sample %>%
    mutate_at(vars(matches("PID|PIN|Parcel")), as.character) %>% 
    mutate(new = coalesce(!!! select(., matches("PID|PIN|Parcel"))))
#    PIDno PINID ParcelId new
#1     a  <NA>     <NA>   a
#2  <NA>     b     <NA>   b
#3  <NA>  <NA>        c   c

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