如何用NA来pivot_wider多个成对变量？

68bkxrlz  于 2023-04-03  发布在  其他
关注(0)|答案(2)|浏览(108)

我只是有一个截断和subseted df与一个成对的一组3个变量，每个看起来像这样;

structure(list(UID = c("20210521-3", "20210521-1", "20210521-4", 
"20210526-59", "20210526-11", "20210526-62", "20210526-12", "20210526-46", 
"20210526-13", "20210526-44", "20210526-33", "20210526-14", "20210526-9", 
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    76, 76, 72, 72, 72, 72, 76, 72, 72, 72, 69, 76, 72, 72, 76, 
    76, 76, 76, 69, 69, 65), Check1.Survival = structure(c(1L, 
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    2L, 2L, 2L, 2L, 2L, 2L), levels = c("alive", "dead"), class = "factor"), 
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    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, 2L, 
    NA, NA, NA, NA, 1L, NA, 2L, NA, 2L, NA, 2L, 2L, NA, NA, 2L, 
    2L, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, 1L, NA, NA, NA, NA, NA, NA, NA, NA, NA
    ), levels = c("alive", "dead"), class = "factor"), Check3.Survival = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, NA, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    1L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1L, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA), levels = c("alive", "dead"), class = "factor")), row.names = c(NA, 
-232L), class = c("tbl_df", "tbl", "data.frame"))

“DaysX”前缀与“CheckX”前缀配对。我只需要一个长的df（或tibble）与这些变量配对。
我试过了

test<-out %>%
  pivot_longer(
    cols = c(Days1:Days10, Check1.Survival:Check10.Survival),
    names_to = c(".value", "rating"),
    names_pattern = "([a-z]+)_*(.+)") %>%
  rename(Days = ays, Survival = heck)

但变量不是成对的。我也试过了，

test2<-out%>%
  pivot_longer(
    c(-UID, -Cross, -Rep, -Garden),
    names_to = c(".value", "item"), 
    names_sep = "_"
  ) %>% 
  select(-item)

但这似乎根本不能改变df。我知道我错过了一些超级简单的东西。

r

2条答案

按热度按时间
5tmbdcev

5tmbdcev1#

下面是一个Liner：

library(tidyr)
pivot_longer(df, cols=tidyr::matches(".+\\d.*"), 
              names_pattern = "(\\D+)(\\d)", names_to = c(".value", "num"))

# A tibble: 696 × 7
  UID         Cross      Rep   Garden   num    Days Check
  <chr>       <chr>      <chr> <chr>    <chr> <dbl> <fct>
1 20210521-3  NTBG X SDZ A     Limahuli 1        17 alive
2 20210521-3  NTBG X SDZ A     Limahuli 2        59 alive
3 20210521-3  NTBG X SDZ A     Limahuli 3        72 alive
4 20210521-1  NTBG X SDZ B     NA       1        17 alive
5 20210521-1  NTBG X SDZ B     NA       2        59 alive
6 20210521-1  NTBG X SDZ B     NA       3        79 alive
7 20210521-4  NTBG X SDZ C     NA       1        17 alive
8 20210521-4  NTBG X SDZ C     NA       2        59 alive
9 20210521-4  NTBG X SDZ C     NA       3        79 alive
10 20210526-59 SDZ X UCBG A     NA       1        17 alive

解析正则表达式：

  • matches（“.+\d.”）-以多个字符（.+）开头，后跟数字（\d），以0或多个字符（.）结尾
  • （\D+）（\d）-分为2部分，第一部分至少有1个非数字“（\D+）”，第二部分为单个数字“（\d）”
  • names_to = c（“.value”，“num”）-从前面的name_pattern中取出两部分，使用第一部分创建列名'. value'。然后取出第二部分并将其放置在名为的列中：“数字”
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sycxhyv7

sycxhyv72#

我无法想象你想要的结果这是您的示例数据的预期结果吗？

df %>%
  pivot_longer(starts_with("Check"),
               names_pattern = "(.*\\d)\\.(.*)",
               names_to = c("Check",".value"),
               names_prefix = "Check") %>%
  pivot_longer(starts_with("Days"),
               names_to = "Day",
               names_prefix = "Days") %>%
  filter(Check == Day)
#> # A tibble: 696 × 8
#>    UID         Cross      Rep   Garden   Check Survival Day   value
#>    <chr>       <chr>      <chr> <chr>    <chr> <fct>    <chr> <dbl>
#>  1 20210521-3  NTBG X SDZ A     Limahuli 1     alive    1        17
#>  2 20210521-3  NTBG X SDZ A     Limahuli 2     alive    2        59
#>  3 20210521-3  NTBG X SDZ A     Limahuli 3     alive    3        72
#>  4 20210521-1  NTBG X SDZ B     <NA>     1     alive    1        17
#>  5 20210521-1  NTBG X SDZ B     <NA>     2     alive    2        59
#>  6 20210521-1  NTBG X SDZ B     <NA>     3     alive    3        79
#>  7 20210521-4  NTBG X SDZ C     <NA>     1     alive    1        17
#>  8 20210521-4  NTBG X SDZ C     <NA>     2     alive    2        59
#>  9 20210521-4  NTBG X SDZ C     <NA>     3     alive    3        79
#> 10 20210526-59 SDZ X UCBG A     <NA>     1     alive    1        17
#> # … with 686 more rows

创建于2023-03-31带有reprex v2.0.2

赞(0）分享  回复(0）举报  2023-04-03
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