使用 pivot_longer 将数据重塑为多列答案

【问题标题】：reshape data into multiple columns using pivot_longer使用 pivot_longer 将数据重塑为多列
【发布时间】：2021-04-21 18:17:27
【问题描述】：

我正在使用pivot_longer 将我的数据从宽格式改成长格式，变成多个值列。我知道有相关的问题（Pivot_longer 6 columns to 3 columns 或Tidy dataset with pivot_longer: Multiple columns into two columns），但到目前为止我找不到解决方案，可能是因为我的两列将属于不同的类别，第一列是POSIXct，第二列是@ 987654325@.

这是一个最小的工作示例：

    structure(list(compid = c("AT9130162999", "AT9090003478", "AT9070005375", 
"AT9130048156"), iso2c = c("AT", "AT", "AT", "AT"), nace4 = c("7010", 
"4211", "2452", "7010"), lastyear = c("2018", "2019", "2019", 
"2019"), `Closing date
                          Last avail. yr` = structure(c(1546214400, 
1577750400, 1585612800, 1577750400), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 1` = structure(c(1514678400, 
1546214400, 1553990400, 1546214400), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 2` = structure(c(NA, 
1514678400, 1522454400, 1514678400), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 3` = structure(c(NA, 
1483142400, 1490918400, 1483142400), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 4` = structure(c(NA, 
1451520000, 1459382400, 1451520000), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 5` = structure(c(NA, 
1419984000, 1427760000, 1419984000), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 6` = structure(c(NA, 
1388448000, 1396224000, 1388448000), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 7` = structure(c(NA, 
1356912000, 1364688000, 1356912000), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 8` = structure(c(NA, 
1325289600, 1333152000, 1325289600), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), `Closing date
                          Year - 9` = structure(c(NA, 
1293753600, 1301529600, 1293753600), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), operatinginc_last = c(NA, 482813, -94300, NA), operatinginc_year1 = c(NA, 
423482, 780400, NA), operatinginc_year2 = c(NA, 404694, 1210300, 
NA), ebit_last = c(1060000, 482813, -94300, 351292), ebit_year1 = c(1501000, 
423482, 780400, 331415), ebit_year2 = c(NA, 404694, 1210300, 
305492), operatingrev_last = c(28463000, 15842418, 13009700, 
11742884), operatingrev_year1 = c(NA, 13734462, 13146300, 10682889
), operatingrev_year2 = c(NA, 13734462, 13146300, 10682889)), row.names = c(NA, 
-4L), class = c("tbl_df", "tbl", "data.frame"))

到目前为止，我已经尝试过：

df_l <- df %>%  
pivot_longer(., cols = -(starts_with(c("compid","iso2c","nace4","lastyear","Closing"))), 
               values_to = "value", values_drop_na=T, names_sep = "_", names_to = c("variable","year"))

但现在我还想重塑所有以Closing 开头的列。我该怎么做（最好用pivot_longer一步完成）？

然后，预期的输出应包括 variable、year 和 value 列，还应包括 closingdate 和 date 列：

 compid    iso2c   nace4   lastyear   `closingdate             ~ `date              ~`variable      ~`year       ~ `value
   <chr>  <chr> <chr> <chr>    <dttm>              <dttm>              <dttm>              <dttm>             
 1 AT913~ AT    7010  2018    `Closing date Last avail. yr` 2018-12-31 ebit  last            28463000                 
 2 AT913~ AT    7010  2018    `Closing date Year - 1`       2017-12-31 ebit  year1           15362687  
 2 AT913~ AT    7010  2018    `Closing date Year - 1`       2016-12-31 ebit  year2           404694

【问题讨论】：

标签： r reshape

【解决方案1】：

我不知道您将如何在一次调用 pivot_longer 中做到这一点，因为您有不同的变量和不同的方案。而且您还想转向更长的结束日期变量。所以这里是在两次调用中，对结束变量进行了一些清理。

library(tidyverse)

df_l <-   pivot_longer(df, cols = starts_with("Closing"), 
                       values_to = "date", values_drop_na=T,  names_to = c("closing")) %>%
  pivot_longer(., cols = contains("_"), 
               values_to = "value", values_drop_na=T, names_sep = '_', names_to = c("variable",'year')) %>%
  mutate(closing = str_remove_all(closing,'Closing date') %>% 
           str_remove_all(.,'[:cntrl:]') %>%
           str_squish() %>%
           str_trim())

【讨论】：