将pivot_longer与数百个变量一起使用[重复]

Question

我有宽格式的大型数据集（287 个变量的 1200 个观测值），其中大多数变量在 10 年范围内随时间变化，少数变量随时间变化。时变变量标签不遵循特定模式，除了以 2011 到 2020 之间的年份结尾之外。

我想以长格式重塑它，但我很难弄清楚如何以相当快的方式做到这一点。

这是一个具有可比较特征的简单数据框：

#Packages
library(dplyr)
library(tidyr)

#Reproducibility
set.seed(123)

#Generate data frame
wide <- as.data.frame(matrix(runif(n=60, min=0, max=10), nrow=5))

#Naming rows and columns
names(wide) = c("day2011", 
               "night2011", 
               "in_between2011",
               "day2012", 
               "night2012", 
               "in_between2012",
               "day2013", 
               "night2013", 
               "in_between2013",
               "house",
               "tree",
               "dog"
               )
wide$id <-  c("red", "blue", "yellow", "black", "green")

我正在慢慢地努力做到这一点，但我不确定它在大型数据集上是否可持续：

long_day <- pivot_longer(data = wide,
                     cols = starts_with("day"),
                     #cols_vary = "slowest",
                     names_to = "year",
                     values_to = "Day") %>%
  select(-(night2011:in_between2013)) %>%
  mutate(year = gsub("day", "", year))
      
long_night <- pivot_longer(data = wide,
                         cols = starts_with("night"),
                         #cols_vary = "slowest",
                         names_to = "year",
                         values_to = "Night") %>%
  select(-(day2011:in_between2013))%>%
  mutate(year = gsub("night", "", year))   

long_24 <- full_join(long_day, long_night, by = c("id", "year", "house", "dog", "tree"))

Answer 1

用途：

wide %>%
   pivot_longer(matches('20(1[1-9]|20)$'),
                names_to = c('.value', 'year'),
                names_pattern = "(.*?)(\\d+)")

# A tibble: 15 × 8
   house  tree   dog id     year    day night in_between
   <dbl> <dbl> <dbl> <chr>  <chr> <dbl> <dbl>      <dbl>
 1  1.39 0.458  2.07 red    2011  2.88  0.456       9.57
 2  1.39 0.458  2.07 red    2012  9.00  8.90        7.09
 3  1.39 0.458  2.07 red    2013  9.63  4.78        1.43
 4  2.33 4.42   1.28 blue   2011  7.88  5.28        4.53
 5  2.33 4.42   1.28 blue   2012  2.46  6.93        5.44
 6  2.33 4.42   1.28 blue   2013  9.02  7.58        4.15
 7  4.66 7.99   7.53 yellow 2011  4.09  8.92        6.78
 8  4.66 7.99   7.53 yellow 2012  0.421 6.41        5.94
 9  4.66 7.99   7.53 yellow 2013  6.91  2.16        4.14
10  2.66 1.22   8.95 black  2011  8.83  5.51        5.73
11  2.66 1.22   8.95 black  2012  3.28  9.94        2.89
12  2.66 1.22   8.95 black  2013  7.95  3.18        3.69
13  8.58 5.61   3.74 green  2011  9.40  4.57        1.03
14  8.58 5.61   3.74 green  2012  9.55  6.56        1.47
15  8.58 5.61   3.74 green  2013  0.246 2.32        1.52