相对于向量A转换向量B的大小写

I have 2 data frames, for which I want to harmonize the column names. Some variables are different in respect to upper/lower case, some variables have already the same name, and some variables are unique. I want to keep the names of my first data frame, i.e. the variable names of the second data frame should be converted to the upper/lower cases of the first data frame. For that reason, the typical toupper or tolower functions do not work.

我有2个数据框,我想要协调列名。有些变量在大写/小写方面有所不同,有些变量已经有了相同的名称,有些变量是唯一的。我想保留我的第一个数据帧的名称,即第二个数据帧的变量名称应该转换为第一个数据帧的大/小的情况。出于这个原因,典型的toupper或tolower功能不起作用。

Consider the following reproducible example:

考虑以下可重现的示例:

# Data frame A
df_a <- data.frame(Col1 = rnorm(5),
                   cOL2 = rnorm(5),
                   col3 = rnorm(5),
                   COL4 = rnorm(5),
                   unique_a = rnorm(5))

# Data frame B
df_b <- data.frame(COL1 = rnorm(5), # Should be converted to Col1
                   COL2 = rnorm(5), # Should be converted to cOL2
                   col3 = rnorm(5), # Should be kept as it is
                   COL4 = rnorm(5), # Should be kept as it is
                   unique_b = rnorm(5)) # Should be kept as it is

# Vectors of column names
vec_a <- colnames(df_a)
vec_b <- colnames(df_b)

# If there is a match, vec_b should be converted to vec_a
# The final result shoul look as follows:
# vec_b
# [1] "Col1"     "cOL2"     "col3"     "COL4"     "unique_b"

Question: How could I convert the matching column names of data frame B to the column names of data frame A?

问题:如何将数据框B的匹配列名转换为数据框A的列名?

2 个解决方案

#1

You could use plyr::mapvalues:

你可以使用plyr :: mapvalues:

plyr::mapvalues(x = tolower(names(df_b)), 
                from = tolower(names(df_a)), 
                to = names(df_a), 
                warn_missing = FALSE)

#2

One option is to use match on the names that are converted to a single case and then do the assignment

一种选择是对转换为单个案例的名称使用匹配,然后执行分配

i1 <- match(toupper(vec_a), toupper(vec_b), nomatch = 0)
i2 <- match(toupper(vec_b), toupper(vec_a), nomatch = 0)
names(df_b)[i2] <- names(df_a)[i1]
names(df_b)
#[1] "Col1"     "cOL2"     "col3"     "COL4"     "unique_b"

#1