我想将一个长的数据框重塑成一个宽的数据框。也就是说,我想从这里开始:
file label val1 val2
1 red A 12 3
2 red B 4 2
3 red C 5 8
4 green A 3 3
5 green B 6 5
6 green C 9 6
7 blue A 3 3
8 blue B 1 2
9 blue C 4 6
对此:
file value1_A value1_B value1_C value2_A value2_B value2_C
1 red 12 4 5 3 2 8
2 green 3 6 9 3 5 6
3 blue 3 1 4 3 2 6
到目前为止,我最大的尝试是:
library(tidyverse)
dat <-
structure(list(file = structure(c(3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 1L),
.Label = c("blue", "green", "red"),
class = "factor"),
label = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L),
.Label = c("A", "B", "C"),
class = "factor"),
val1 = c(12L, 4L, 5L, 3L, 6L, 9L, 3L, 1L, 4L),
val2 = c(3L, 2L, 8L, 3L, 5L, 6L, 3L, 2L, 6L)),
class = "data.frame", row.names = c(NA, -9L))
dat %>%
group_by(file) %>%
mutate(values1 = paste('value1', label, sep='_'),
values2 = paste('value2', label, sep='_')) %>%
spread(values1, val1) %>%
spread(values2, val2) %>%
select(-label)
# # A tibble: 9 x 7
# # Groups: file [3]
# file value1_A value1_B value1_C value2_A value2_B value2_C
# <fct> <int> <int> <int> <int> <int> <int>
# 1 blue 3 NA NA 3 NA NA
# 2 blue NA 1 NA NA 2 NA
# 3 blue NA NA 4 NA NA 6
# 4 green 3 NA NA 3 NA NA
# 5 green NA 6 NA NA 5 NA
# 6 green NA NA 9 NA NA 6
# 7 red 12 NA NA 3 NA NA
# 8 red NA 4 NA NA 2 NA
# 9 red NA NA 5 NA NA 8
输出不令人满意,因为应排的一行占据了三行,并带有多个“ NA”。这似乎是由于两次使用spread
造成的,但是我不知道还有什么其他方法可以达到我想要的结果。非常感谢您提供有关此操作的建议。
非常感谢, -R
答案 0 :(得分:3)
这是一种方式
library(tidyverse)
dat %>%
# first move to long form so we can
# see the original column names as strings
gather("variable_name", "value", contains("val")) %>%
# create the new column names from the variable name and the label
mutate(new_column_name = paste(variable_name, label, sep="_")) %>%
# get rid of the pieces we used to make the column names
select(-label, -variable_name) %>%
# now spread
spread(new_column_name, value)
答案 1 :(得分:3)
这是data.table
的方式。只需一行代码...
library( data.table )
dcast( setDT( dat ), file ~ label, value.var = c("val1", "val2"))
# file val1_A val1_B val1_C val2_A val2_B val2_C
# 1: blue 3 1 4 3 2 6
# 2: green 3 6 9 3 5 6
# 3: red 12 4 5 3 2 8