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[英]readr (or other packages from tidyverse) with data.frame instead of tibble
[英]Apply readr col_cpec to data.frame, independently of reading from file
我有一個data.frame
tibble
,我需要對其應用許多類型更新。 我有一個描述所需類型的readr
:: col_spec
object,但由於數據並非源自 csv 文件,因此我無法使用read_csv(..., col_types=cspec)
將更改應用於指定的列。
由於col_spec
是一種精確設計用於指定所需數據類型的數據結構,因此我仍將其直接用作 function 的輸入,為我應用更改,而不是編寫長的自定義腳本來應用不同的列。 請參見以下示例:
library(tidyverse)
# Subset starwars to get sw (comparable to my input data)
sw <- starwars %>%
select(name, height, ends_with("_color")) %>%
slice(c(1,4,5,19))
sw
#> # A tibble: 4 × 5
#> name height hair_color skin_color eye_color
#> <chr> <int> <chr> <chr> <chr>
#> 1 Luke Skywalker 172 blond fair blue
#> 2 Darth Vader 202 none white yellow
#> 3 Leia Organa 150 brown light brown
#> 4 Yoda 66 white green brown
# The col_spec that I have
cspec <- cols(
hair_color = col_factor(c("brown", "blond", "white", "none")),
skin_color = col_factor(c( "green", "light", "fair", "white")),
eye_color = col_factor(c("blue", "brown", "yellow"))
)
# I would like to apply the col_spec directly to sw
# A not so great workaround is to use a tempfile
tf <- tempfile()
sw %>% write_csv(tf)
sw_fct <- read_csv(tf, col_types=cspec)
# This is more or less the result I am after:
# But note how info on other columns (height) is lost in the roundtrip
sw_fct
#> # A tibble: 4 × 5
#> name height hair_color skin_color eye_color
#> <chr> <dbl> <fct> <fct> <fct>
#> 1 Luke Skywalker 172 blond fair blue
#> 2 Darth Vader 202 none white yellow
#> 3 Leia Organa 150 brown light brown
#> 4 Yoda 66 white green brown
我們可以通過遍歷cols
從對象中提取元素來做到這一點
library(readr)
library(purrr)
sw[names(cspec$cols)] <- imap(cspec$cols, ~ parse_factor(sw[[.y]],
levels = .x$levels, ordered = .x$ordered, include_na = .x$include_na))
- 檢查輸出
> sw
# A tibble: 4 × 5
name height hair_color skin_color eye_color
<chr> <int> <fct> <fct> <fct>
1 Luke Skywalker 172 blond fair blue
2 Darth Vader 202 none white yellow
3 Leia Organa 150 brown light brown
4 Yoda 66 white green brown
> str(sw)
tibble [4 × 5] (S3: tbl_df/tbl/data.frame)
$ name : chr [1:4] "Luke Skywalker" "Darth Vader" "Leia Organa" "Yoda"
$ height : int [1:4] 172 202 150 66
$ hair_color: Factor w/ 4 levels "brown","blond",..: 2 4 1 3
$ skin_color: Factor w/ 4 levels "green","light",..: 3 4 2 1
$ eye_color : Factor w/ 3 levels "blue","brown",..: 1 3 2 2
如果我們還需要'spec'的attr
,請進行賦值
attr(sw, "spec") <- cspec
- 檢查str
> str(sw)
tibble [4 × 5] (S3: tbl_df/tbl/data.frame)
$ name : chr [1:4] "Luke Skywalker" "Darth Vader" "Leia Organa" "Yoda"
$ height : int [1:4] 172 202 150 66
$ hair_color: Factor w/ 4 levels "brown","blond",..: 2 4 1 3
$ skin_color: Factor w/ 4 levels "green","light",..: 3 4 2 1
$ eye_color : Factor w/ 3 levels "blue","brown",..: 1 3 2 2
- attr(*, "spec")=
.. cols(
.. hair_color = col_factor(levels = c("brown", "blond", "white", "none"), ordered = FALSE, include_na = FALSE),
.. skin_color = col_factor(levels = c("green", "light", "fair", "white"), ordered = FALSE, include_na = FALSE),
.. eye_color = col_factor(levels = c("blue", "brown", "yellow"), ordered = FALSE, include_na = FALSE)
.. )
這個答案將@akrun 的解決方案包裝成一個函數,供那些可能不太熟悉 purrr 的人使用。
apply_col_spec <- function(d, cspec, set_spec_attribute=FALSE) {
# A bit of input checking
if (!all(inherits(d, "data.frame"), inherits(cspec, "col_spec"),
is.logical(set_spec_attribute))) {
stop("apply_col_spec(): wrong input types")
}
if (!all(sapply(cspec$cols, inherits, "collector_factor"))) {
stop("apply_col_spec(): only implemented for factor columns")
}
# Do the actual application of the col_spec
d[names(cspec$cols)] <- imap(cspec$cols, ~ parse_factor(d[[.y]],
levels = .x$levels, ordered = .x$ordered, include_na = .x$include_na))
# If requested, set col_spec as an attribute, for consistency with readr
if (set_spec_attribute) {
attr(d, "spec") <- cspec
}
d
}
並在問題中定義的變量上運行該函數會產生預期的結果:
> apply_col_spec(sw, cspec)
# A tibble: 4 × 5
name height hair_color skin_color eye_color
<chr> <int> <fct> <fct> <fct>
1 Luke Skywalker 172 blond fair blue
2 Darth Vader 202 none white yellow
3 Leia Organa 150 brown light brown
4 Yoda 66 white green brown
實現這一點的另一種方法,回想起來似乎更好,是使用readr::type_convert()
function。 這個 function 與下面的apply_col_spec()
function 具有幾乎完全相同的行為,並與readr
一起收縮包裝。
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