是否可以在cols_only()函数中使用tidyselect帮助程序？

Question

我有这样一个.csv文件(除了真正的.csv文件有更多的列外)：

library(tidyverse)

tibble(id1 = c("a", "b"),
       id2 = c("c", "d"),
       data1 = c(1, 2),
       data2 = c(3, 4),
       data1s = c(5, 6), 
       data2s = c(7, 8)) %>% 
  write_csv("df.csv")

我只想要id1，id2，data1和data2。

我可以这么做：

df <- read_csv("df.csv", 
               col_names = TRUE,
               cols_only(id1 = col_character(),
                         id2 =  col_character(),
                         data1 = col_integer(),
                         data2 = col_integer()))

但是，如前所述，我的真实数据集有更多的列，所以我希望使用tidyselect帮助程序只读取指定的列并确保指定的格式。

我试过这个：

df2 <- read_csv("df.csv",
         col_names = TRUE,
         cols_only(starts_with("id") = col_character(),
                   starts_with("data") & !ends_with("s") =  col_integer()))

但是错误消息表明语法有问题。是否有可能以这种方式使用tidyselect助手？

Answer 1

我的建议在一定程度上是围绕着房子的，但它基本上允许你在“规则”而不是明确的基础上定制阅读规范。

library(tidyverse)

tibble(id1 = c("a", "b"),
       id2 = c("c", "d"),
       data1 = c(1, 2),
       data2 = c(3, 4),
       data1s = c(5, 6), 
       data2s = c(7, 8)) %>% 
  write_csv("df.csv")

# read only 1 row to make a spec from with minimal read; really just to get the colnames
df_spec <- spec(read_csv("df.csv", 
               col_names = TRUE,
        n_max = 1))

#alter the spec with base R functions startsWith / endsWith etc.
df_spec$cols <- imap(df_spec$cols,~{if(startsWith(.y,"id")){
  col_character()
} else if(startsWith(.y,"data") &
                                       !endsWith(.y,"s")){
  col_integer()
} else {
  col_skip()
}})

df <- read_csv("df.csv",
               col_types = df_spec$cols)