R中的多行到一行

Question

在 R 中，我有一个包含多个值的数据框。我想要一个数据框，将数据框转换为只有一行包含所有值的数据框。我有一个这样的数据框：

df <- data.frame(A = c("time", "time", "time"),
                 B = c("place", "place", "place"),
                 C = c(NA, 1, NA),
                 D = c(NA, NA, 2),
                 E = c(3, NA, NA),
                 `F` = c(4,4, NA),
                 G = c(NA, 5, NA))

     A     B  C  D  E  F  G
1 time place NA NA  3  4 NA
2 time place  1 NA NA  4  5
3 time place NA  2 NA NA NA

我想要这样的数据框：

     A     B C D E F G
1 time place 1 2 3 4 5

我尝试像这里一样使用重塑函数：

并尝试了独特的功能，但我丢失了很多数据：Selecting unique rows in matrix using R

Answer 1

您可以将 na.omit() 与摘要一起使用，a la:

library(tidyverse)

df %>% group_by(A, B) %>% 
       summarise(C = mean(na.omit(C)),
                 D = mean(na.omit(D)),
                 E = mean(na.omit(E)),
                 F = mean(na.omit(F)),
                 G = mean(na.omit(G)))

您的示例数据在每列 C-G 中只有唯一值，因此根据您的评论，我使用 mean() 来获取非 NA 观察值的平均值。

数据：

df <- structure(list(A = c("time", "time", "time"), B = c("place",
"place", "place"), C = c(NA, 1L, NA), D = c(NA, NA, 2L), E = c(3L,
NA, NA), F = c(4L, 4L, NA), G = c(NA, 5L, NA)), class = "data.frame", row.names = c(NA,
-3L))

Answer 2

使用 colMeans 解决不同值的解决方案：

1.Create 测试数据

df <- structure(list(
  A = c("time", "time", "time"), 
  B = c("place", "place", "place"), 
  C = c(NA, 1L, NA), 
  D = c(NA, NA, 2L), 
  E= c(3L, NA, NA), 
  F = c(4L, 4L, NA), 
  G = c(NA, 5L, NA)), 
  row.names = c(NA, -3L),
  class = c("data.table", "data.frame"))

2.Use 前两列为 unique，其余为 colMeans，转换为 data.frame:

cbind(unique(df[, 1:2]), as.data.frame.list(colMeans(df[,3:7], na.rm = TRUE)))

Returns:

      A     B C D E F G
1: time place 1 2 3 4 5

Answer 3

我们可以按 'A'、'B' 和 select 第一个非 NA 元素 across 其他列

分组

library(dplyr)
df1 %>%
     group_by(A, B) %>%
     summarise(across(everything(), ~ .[order(is.na(.))][1]), .groups = 'drop')

-输出

# A tibble: 1 x 8
#  A     B         C     D     E     F     G H    
#  <chr> <chr> <int> <int> <int> <int> <int> <lgl>
#1 time  place     1     2     3     4     5 NA

或 coalesce

library(purrr)
df1 %>%
    group_by(A, B) %>% 
    summarise(across(everything(), ~ reduce(., coalesce)), .groups = 'drop')

数据

df1 <- structure(list(A = c("time", "time", "time"), B = c("place", 
"place", "place"), C = c(NA, 1L, NA), D = c(NA, NA, 2L), E = c(3L, 
NA, NA), F = c(4L, NA, NA), G = c(NA, 5L, NA), H = c(NA, NA, 
NA)), class = "data.frame", row.names = c(NA, -3L))

R中的多行到一行

Multiples rows to one row in R

r

rows

dplyr

数据