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批量更改数据框? 如何将操作列表应用于多个数据帧?

[英]Changing dataframes in bulk? How to apply a list of operations to multiple dataframes?

So, I have 6 data frames, all look like this (with different values):所以,我有 6 个数据框,都看起来像这样(具有不同的值): 在此处输入图像描述

Now I want to create a new column in all the data frames for the country.现在我想在该国家/地区的所有数据框中创建一个新列。 Then I want to convert it into a long df.然后我想把它转换成一个长的df。 This is how I am going about it.这就是我要做的事情。

dlist<- list(child_mortality,fertility,income_capita,life_expectancy,population)

convertlong <- function(trial){
  trial$country <- rownames(trial)
  trial <- melt(trial)
  colnames(trial)<- c("country","year",trial)
}

for(i in dlist){
 convertlong(i)
}

After running this I get:运行后我得到:

Using country as id variables
Error in names(x) <- value : 
  'names' attribute [5] must be the same length as the vector [3]

That's all, it doesn't do the operations on the data frames.就是这样,它不对数据帧进行操作。 I am pretty sure I'm taking a stupid mistake, but I looked online on forums and cannot figure it out.我很确定我犯了一个愚蠢的错误,但是我在论坛上在线查看并无法弄清楚。

maybe you can replace也许你可以更换

trial$country <- rownames(trial)

by经过

trial <- cbind(trial, rownames(trial))

Here's a tidyverse attempt -这是一个tidyverse的尝试 -

library(tidyverse)

#Put the dataframes in a named list. 
dlist<- dplyr::lst(child_mortality, fertility, 
                   income_capita, life_expectancy,population)
#lst is not a typo!!

#Write a function which creates a new column with rowname
#and get's the data in long format
#The column name for 3rd column is passed separately (`col`).
convertlong <- function(trial, col){
  trial %>%
    rownames_to_column('country') %>%
    pivot_longer(cols = -country, names_to = 'year', values_to = col)
}

#Use `imap` to pass dataframe as well as it's name to the function. 
dlist <- imap(dlist, convertlong)

#If you want the changes to be reflected for dataframes in global environment.
list2env(dlist, .GlobalEnv)

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