r - 基于现有数据帧为 read_csv 创建 col_types 字符串规范

Question

我有一个 data.frame 或 tibble，它在一个脚本中写入 CSV 文件。在另一个脚本中，相同的 CSV 文件被读入 data.frame 或 tibble。使用 read_csv() , 与 col_types=参数，我可以指定要读入的列类型。这是一个例子:

# Create an example dataframe
df <- tibble::tibble(a=1L
                     , b=1.0
                     , c="a"
                     , d=TRUE
                     , e=lubridate::ymd_hms("2019-03-19T13:15:18Z")
                     , f=lubridate::ymd("2019-03-19")
                     , g=factor("a"))

# Write csv to file
readr::write_csv(df, "temp.csv")

# read it back in, supplying a col_types string spec
readr::read_csv("temp.csv", col_types="idclTDf")
#> # A tibble: 1 x 7
#>       a     b c     d     e                   f          g    
#>   <int> <dbl> <chr> <lgl> <dttm>              <date>     <fct>
#> 1     1     1 a     TRUE  2019-03-19 13:15:18 2019-03-19 a

创建于 2019-03-19 由 reprex package (v0.2.1)

问题是我需要知道 col_types= read_csv() 上的参数函数(或者让它猜测，我不想这样做)。我想要的是某种方式来获取原始 df并且，在我写出来之前，生成 col_types来自 df 的字符串可用于重新读取转储的 CSV 的对象。也就是说，我想要一些可以创建 "idclTDf" 的对象。字符串给定 data.frame 作为参数。

我看到这里有一个功能请求(我已经添加了我的两分钱): https://github.com/tidyverse/readr/issues/895 .

Answer 1

我确实有一个解决方案，它有效，但我认为它非常不完整且没有强化。这是我对解决方案的尝试。

# https://github.com/tidyverse/readr/issues/895
# Create function to take a tibble and return a character string that can be used in `readr::read_csv()`
# as the `col_types` argument to re-read this back into a dataframe after it had been written out
# by `write_csv()`.

get_col_types_short <- function(.df) {
    # Get column classes from input dataframe
    lst_col_classes__ <- purrr::map(.df, ~ class(.x))

    # Map classes to known single-character col_types indicator
    vl_col_class_char__ <- purrr::map_chr(lst_col_classes__, function(.e) {
        dplyr::case_when(
              "logical" %in% .e   ~ "l"
            , "integer" %in% .e   ~ "i"
            , "numeric" %in% .e   ~ "d"
            , "double" %in% .e    ~ "d"
            , "character" %in% .e ~ "c"
            , "factor" %in% .e    ~ "f"
            , "Date" %in% .e      ~ "D"
            , "POSIXct" %in% .e   ~ "T"
            , TRUE                ~ "c"
        )
    })

    # Return vector of single-character col_type indicator.
    # Element name is the source column it came from.
    vl_col_class_char__
}

# Test it:
df <- tibble::tibble(a=1L
                     , b=1.0
                     , c="a"
                     , d=TRUE
                     , e=lubridate::ymd_hms("2019-03-19T13:15:18Z")
                     , f=lubridate::ymd("2019-03-19")
                     , g=factor("a"))

v__ <- get_col_types_short(df)

# Show what is actually returned
v__
#>   a   b   c   d   e   f   g 
#> "i" "d" "c" "l" "T" "D" "f"

# Collapse it to show how to use it
paste(v__, collapse="")
#> [1] "idclTDf"


# Write csv to file
readr::write_csv(df, "temp.csv")

# read it back in, using the above col_types string spec
readr::read_csv("temp.csv", col_types=paste(v__, collapse=""))
#> # A tibble: 1 x 7
#>       a     b c     d     e                   f          g    
#>   <int> <dbl> <chr> <lgl> <dttm>              <date>     <fct>
#> 1     1     1 a     TRUE  2019-03-19 13:15:18 2019-03-19 a

创建于 2019-03-19 由 reprex package (v0.2.1)