将数据框的行与一些因子列绑定

Bind rows of data frames with some factor columns

我想创建一个 dplyr::bind_rows 的升级版本,当我们试图合并的 dfs 中存在因子列时,它可以避免 Unequal factor levels: coercing to character 警告(它也可能有非因子列)。这是一个例子:

df1 <- dplyr::data_frame(age = 1:3, gender = factor(c("male", "female", "female")), district = factor(c("north", "south", "west")))
df2 <- dplyr::data_frame(age = 4:6, gender = factor(c("male", "neutral", "neutral")), district = factor(c("central", "north", "east")))

然后 bind_rows_with_factor_columns(df1, df2) returns(没有警告):

dplyr::data_frame(
  age = 1:6,
  gender = factor(c("male", "female", "female", "male", "neutral", "neutral")),
  district = factor(c("north", "south", "west", "central", "north", "east"))
)

这是我目前的情况:

bind_rows_with_factor_columns <- function(...) {
  factor_columns <- purrr::map(..., function(df) {
      colnames(dplyr::select_if(df, is.factor))
  })

  if (length(unique(factor_columns)) > 1) {
      stop("All factor columns in dfs must have the same column names")
  }

  df_list <- purrr::map(..., function (df) {
    purrr::map_if(df, is.factor, as.character) %>% dplyr::as_data_frame()
  })

  dplyr::bind_rows(df_list) %>%
    purrr::map_at(factor_columns[[1]], as.factor) %>%
    dplyr::as_data_frame()
}

我想知道是否有人对如何合并 forcats 包有任何想法,以潜在地避免必须将因素强制转换为角色,或者是否有人有任何一般性的建议来提高这个同时的性能保持相同的功能(我想坚持 tidyverse 语法)。谢谢!

根据朋友的一个很好的解决方案来回答我自己的问题:

bind_rows_with_factor_columns <- function(...) {
  purrr::pmap_df(list(...), function(...) {
    cols_to_bind <- list(...)
    if (all(purrr::map_lgl(cols_to_bind, is.factor))) {
      forcats::fct_c(cols_to_bind)
    } else {
      unlist(cols_to_bind)
    }
  })
}

使用 dplyr::bind_rows 并抑制警告,然后将所有新字符列转换回因子可能更简单。这具有按列名称绑定 data.frames 的优点(允许对列进行不同的排序并包含额外的列),并且在有时将因子变量记录为字符时仍然有效。

library(tidyverse)

bind_rows_keep_factors <- function(...) {
  ## Identify all factors
  factors <- unique(unlist(
    map(list(...), ~ select_if(..., is.factor) %>% names())
  ))
  ## Bind dataframes, convert characters back to factors
  suppressWarnings(bind_rows(...)) %>% 
    mutate_at(vars(one_of(factors)), factor)  
}

dat1 <- tibble(
  id = 1:2,
  fruit = factor(c("banana", "apple"))
)

dat2 <- tibble(
  id = 3:4,
  fruit = c("pear", "banana"),
  taste = c("Mmmm", "yum")
)

bind_rows_keep_factors(dat1, dat2)
# A tibble: 4 x 3
     id fruit  taste
  <int> <fct>  <chr>
1     1 banana NA   
2     2 apple  NA   
3     3 pear   Mmmm 
4     4 banana yum 

当然,因子水平的顺序被打乱了(恢复为字母顺序)。