如何使用 R 中的映射文件更改多个数据框中的列名称？

Question

我有一个循环遍历多年数据的脚本，一次一年。 每一年的数据都由多个数据帧组成，这些数据帧被放置在一个名为all_input的列表中。 在循环的开始（数据读入之后），我试图在处理的rest之前以相同的格式获取所有年份的数据。

我遇到的问题是列名不统一。 我想保留的每个 dataframe 中包含 5 列，我希望它们被称为total_emissions uom tribal_name st_usps_cd和description 。 在某些数据框中，它们已经具有这些名称，而在另一些数据框中，它们具有各种名称，例如pollutant.desc或pollutant_desc 。

我目前的做法是这样的：

# Create a mapping file for the column names
    header_map <- data.frame(orignal_col = c( "pollutant_desc", "pollutant.desc", "emissions.uom", "total.emissions", "tribal.name", "state" ), 
                               new_col = c( "description", "description", "uom", "total_emissions", "tribal_name", "st_usps_cd" ), stringsAsFactors = FALSE)

    # change the column names
    lapply(all_input, function(x) {
      names(x)[match(header_map$orignal_col, names(x))] <- header_map$new_col
      x
    }) -> all_input

这将创建一个 header 映射文件，如下所示：

original_col         new_col
pollutant_desc       description
pollutant.desc       description
emissions.uom        uom
total.emissions      total_emissions
tribal.name          tribal_name
state                st_usps_cd

我得到的错误如下：

Error in names(x)[match(header_map$orignal_col, names(x))] <- header_map$new_col : 
  NAs are not allowed in subscripted assignments

我知道，因为处理具有不同列名的新年份数据时，我必须手动将条目添加到 header 文件中，但是我怎样才能让它工作呢？

假样本数据。 df1 和 df2 代表“2017”数据的格式，其中多列需要更改名称，但当前名称在数据帧之间保持一致。 df3 表示“2011”数据，其中所有列名都应如此。 df4 代表“2014”数据，其中唯一需要更改的列是pollutant_desc 。 请注意，每个 dataframe 中都有多余的列是不需要的，可以忽略。 提醒一下，这些数据帧并不是同时读取的。 循环按年份进行，因此 df1 和 df2 （在列表all_input中）将被格式化和处理。 然后删除所有数据，并使用未来几年的数据框创建一个新的all_input列表，这些数据框将具有不同的列名。 代码必须在不改变的情况下使用多年。

> dput(df1)
structure(list(total.emissions = structure(1:2, .Label = c("100", 
"300"), class = "factor"), emissions.uom = structure(1:2, .Label = c("LB", 
"TON"), class = "factor"), international = c(TRUE, TRUE), hours = structure(2:1, .Label = c("17", 
"3"), class = "factor"), tribal.name = structure(2:1, .Label = c("FLLK", 
"SUWJG"), class = "factor"), state = structure(1:2, .Label = c("AK", 
"MN"), class = "factor"), pollutant.desc = structure(1:2, .Label = c("Methane", 
"NO2"), class = "factor"), policy = c(TRUE, FALSE)), class = "data.frame", row.names = c(NA, 
-2L))

> dput(df2)
structure(list(total.emissions = structure(2:1, .Label = c("20", 
"400"), class = "factor"), emissions.uom = structure(c(1L, 1L
), .Label = "TON", class = "factor"), international = c(FALSE, 
TRUE), hours = structure(2:1, .Label = c("1", "8"), class = "factor"), 
    tribal.name = structure(2:1, .Label = c("SOSD", "WMFJU"), class = "factor"), 
    state = structure(2:1, .Label = c("SD", "WY"), class = "factor"), 
    pollutant.desc = structure(1:2, .Label = c("CO2", "SO2"), class = "factor"), 
    policy = c(FALSE, FALSE)), class = "data.frame", row.names = c(NA, 
-2L))

> dput(df3)
structure(list(total_emissions = structure(2:1, .Label = c("200", 
"30"), class = "factor"), uom = structure(c(1L, 1L), .Label = "TON", class = "factor"), 
    boundaries = structure(2:1, .Label = c("N", "Y"), class = "factor"), 
    tribal_name = structure(2:1, .Label = c("SOSD", "WMFJU"), class = "factor"), 
    st_usps_cd = structure(2:1, .Label = c("ID", "KS"), class = "factor"), 
    description = structure(c(1L, 1L), .Label = "SO2", class = "factor"), 
    policy = c(FALSE, TRUE), time = structure(1:2, .Label = c("17", 
    "7"), class = "factor")), class = "data.frame", row.names = c(NA, 
-2L))

> dput(df4)
structure(list(total_emissions = structure(2:1, .Label = c("700", 
"75"), class = "factor"), uom = structure(c(1L, 1L), .Label = "LB", class = "factor"), 
    tribal_name = structure(1:2, .Label = c("SSJY", "WNCOPS"), class = "factor"), 
    st_usps_cd = structure(1:2, .Label = c("MO", "NY"), class = "factor"), 
    pollutant_desc = structure(2:1, .Label = c("CO2", "Methane"
    ), class = "factor"), boundaries = structure(c(1L, 1L), .Label = "N", class = "factor"), 
    policy = c(FALSE, FALSE), time = structure(1:2, .Label = c("2", 
    "3"), class = "factor")), class = "data.frame", row.names = c(NA, 
-2L))

谢谢！

Answer 1

尝试这个：

list_of_frames1 <- list(df1, df2, df3, df4)
list_of_frames2 <- lapply(list_of_frames1, function(x) {
  nms <- intersect(names(x), header_map$orignal_col)
  names(x)[ match(nms, names(x)) ] <- header_map$new_col[ match(nms, header_map$orignal_col) ]
  x
})