pivot_longer()并合并兩個資料集

我有兩個資料集。第一個是

issue_1_t1 <- c(10, 20, 30, 40)
issue_2_t1 <- c(10, 20, 30, 10)
issue_1_t2 <- c(10, 20, 30, 40)
issue_2_t2 <- c(10, 20, 30, 10)
issue_1_t3 <- c(10, 20, 30, 40)
issue_2_t3 <- c(10, 20, 30, 10)
area <- c(area1, area2, area3, area4)
area2 <- c(area10, area20, area30, area40)
df <- data.frame(issue_1_t1, issue_2_t1, issue_1_t2, issue_2_t2, issue_1_t3, issue_2_t3)

我想重新配置這些，以便它們形成以下內容：

area    area2   issue1   issue2
area1   area10  10       10
area2   area20  20       20
area3   area30  30       30
area4   area40  40       40
area1   area10  10       10
area2   area20  20       20
area3   area30  30       30
area4   area40  40       40
area1   area10  10       10
area2   area20  20       20
area3   area30  30       30
area4   area40  40       40

到目前為止，我只能按時間段將資料集分成兩個資料集，然后將它們堆疊在一起。我想知道是否有一種只需要一行代碼的更有效的方法。

uj5u.com熱心網友回復：

你可以試試

library(dplyr)
library(reshape2)
library(tidyr)

df %>%
  melt %>%
  mutate(time = str_sub(variable, -1),
         issue = paste0("issue", str_split(variable, "_", simplify = T)[,2])) %>%
  select(time, issue, value) %>%
  group_by(issue) %>%
  arrange(issue) %>%
  mutate(n = 1, n = cumsum(n)) %>%
  pivot_wider(values_from = value, names_from = issue) %>%
  mutate(area = rep(area, max(n)/length(area)), area2 = rep(area2, max(n)/length(area2))) %>%
  select(-time, -n)

   issue1 issue2 area  area2 
    <dbl>  <dbl> <chr> <chr> 
 1     10     10 area1 area10
 2     20     20 area2 area20
 3     30     30 area3 area30
 4     40     10 area4 area40
 5     10     10 area1 area10
 6     20     20 area2 area20
 7     30     30 area3 area30
 8     40     10 area4 area40
 9     10     10 area1 area10
10     20     20 area2 area20
11     30     30 area3 area30
12     40     10 area4 area40

uj5u.com熱心網友回復：

我認為共享的資料不完整，有語法錯誤。我不明白你說的兩個資料集是什么意思（當只有一個時df），但我認為你擁有的是這樣的 -

issue_1_t1 <- c(10, 20, 30, 40)
issue_2_t1 <- c(10, 20, 30, 10)
issue_1_t2 <- c(10, 20, 30, 40)
issue_2_t2 <- c(10, 20, 30, 10)
issue_1_t3 <- c(10, 20, 30, 40)
issue_2_t3 <- c(10, 20, 30, 10)
area <- c("area1", "area2", "area3", "area4")
area2 <- c("area10", "area20", "area30", "area40")
df <- data.frame(area, area2, issue_1_t1, issue_2_t1, issue_1_t2, 
                 issue_2_t2, issue_1_t3, issue_2_t3)
df

#   area  area2 issue_1_t1 issue_2_t1 issue_1_t2 issue_2_t2 issue_1_t3 issue_2_t3
#1 area1 area10         10         10         10         10         10         10
#2 area2 area20         20         20         20         20         20         20
#3 area3 area30         30         30         30         30         30         30
#4 area4 area40         40         10         40         10         40         10

您可以使用pivot_longerfromtidyr使其具有所需的形狀。

tidyr::pivot_longer(df, 
                    cols = starts_with('issue'), 
                    names_to = '.value', 
                    names_pattern = '(issue_\\d )')

#    area  area2  issue_1 issue_2
#   <chr> <chr>    <dbl>   <dbl>
# 1 area1 area10      10      10
# 2 area1 area10      10      10
# 3 area1 area10      10      10
# 4 area2 area20      20      20
# 5 area2 area20      20      20
# 6 area2 area20      20      20
# 7 area3 area30      30      30
# 8 area3 area30      30      30
# 9 area3 area30      30      30
#10 area4 area40      40      10
#11 area4 area40      40      10
#12 area4 area40      40      10

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