我想创建一个dplyr :: bind_rows的suped-up版本,它避免了Unequal因子级别:当我们尝试组合的dfs中存在因子列时(可能还有非因子列),强制转换为字符警告.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)返回(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"))
)
这是我到目前为止所拥有的:
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,可能避免不得不强迫因素到字符,或者如果有人有任何建议通常提高性能,同时保持相同的功能(我喜欢坚持整齐的语法).谢谢!
最佳答案 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)
}
})
}