将宽数据透视为长数据的R函数

kmbjn2e3 于 2023-02-06 发布在其他

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拜托，我有这么宽的数据，我想把它透视成长数据。

Country     MDA     BI  MDA Last Year   BI Last Year    Month
Netherland  230     280     234     789     June
Scotland    100     340     456     234     June
UK          100     100     768     567     June
USA         200     780     765     123     June
Ireland     100     890     675     987     June
Nigeria     500     560     234     876     June

我使用了pivot_longer()函数，但似乎没有正确使用它。我希望输出为以下格式。

Country     Cur_Year Prod_Cat_new   Prev_Year   Prod_cat_old    Month
Netherland  230 MDA         234 MDA Last Year           June
Scotland    100 MDA         456 MDA Last Year           June
UK          100 MDA         768 MDA Last Year           June
USA         200 MDA         765 MDA Last Year           June
Ireland     100 MDA         675 MDA Last Year           June
Nigeria     500 MDA         234 MDA Last Year           June
Netherland  280 BI          789 BI Last Year            June
Scotland    340 BI          234 BI Last Year            June
UK          100 BI          567 BI Last Year            June
USA         780 BI          123 BI Last Year            June
Ireland     890 BI          987 BI Last Year            June
Nigeria     560 BI          876 BI Last Year            June

r

来源：https://stackoverflow.com/questions/75314968/r-function-for-pivot-wide-data-to-long-data

1条答案

按热度按时间

q1qsirdb1#

使用pivot_longer将其整形为长型，并从Prod_cat列创建这些Prod_cat_new、Prod_cat_old

library(dplyr)
library(stringr)
library(tidyr)
pivot_longer(df1, cols = matches("_"), names_to = c("Prod_cat", ".value"), 
   names_sep = "_") %>%
   mutate(Prod_cat_new = str_c(Prod_cat, '_new'),
    Prod_cat_old = str_c(Prod_cat, '_old'), Prod_cat = NULL) %>% 
  select(Country, new, Prod_cat_new, old, Prod_cat_old, Month)

输出

# A tibble: 12 × 6
   Country      new Prod_cat_new   old Prod_cat_old Month
   <chr>      <int> <chr>        <int> <chr>        <chr>
 1 Netherland   230 MDA_new        234 MDA_old      June 
 2 Netherland   280 SDA_new        789 SDA_old      June 
 3 Scotland     100 MDA_new        456 MDA_old      June 
 4 Scotland     340 SDA_new        234 SDA_old      June 
 5 UK           100 MDA_new        768 MDA_old      June 
 6 UK           100 SDA_new        567 SDA_old      June 
 7 USA          200 MDA_new        765 MDA_old      June 
 8 USA          780 SDA_new        123 SDA_old      June 
 9 Ireland      100 MDA_new        675 MDA_old      June 
10 Ireland      890 SDA_new        987 SDA_old      June 
11 Nigeria      500 MDA_new        234 MDA_old      June 
12 Nigeria      560 SDA_new        876 SDA_old      June

数据

df1 <- structure(list(Country = c("Netherland", "Scotland", "UK", "USA", 
"Ireland", "Nigeria"), MDA_new = c(230L, 100L, 100L, 200L, 100L, 
500L), SDA_new = c(280L, 340L, 100L, 780L, 890L, 560L), MDA_old = c(234L, 
456L, 768L, 765L, 675L, 234L), SDA_old = c(789L, 234L, 567L, 
123L, 987L, 876L), Month = c("June", "June", "June", "June", 
"June", "June")), class = "data.frame", row.names = c(NA, -6L
))

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将宽数据透视为长数据的R函数

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