[英]Pivot all columns wider (except ID columns) using pivot_wider() in R/tidyverse
I'm trying to transform a data frame from long to wide in R
.我正在尝试在
R
数据框从长数据框转换为宽数据框。 I am trying to pivot all columns wider (excepting columns that uniquely identify observations) using pivot_wider()
.我正在尝试使用
pivot_wider()
。 Here is a minimal working example:这是一个最小的工作示例:
library("tidyr")
set.seed(12345)
sampleSize <- 10
timepoints <- 3
raters <- 2
data_long <- data.frame(ID = rep(1:sampleSize, each = timepoints * raters),
time = rep(1:timepoints, times = sampleSize * raters),
rater = rep(c("a","b"), times = sampleSize * timepoints),
v1 = sample.int(99, sampleSize * timepoints * raters, replace = TRUE),
v2 = sample.int(99, sampleSize * timepoints * raters, replace = TRUE),
v3 = sample.int(99, sampleSize * timepoints * raters, replace = TRUE),
v100 = sample.int(99, sampleSize * timepoints * raters, replace = TRUE),
vA = sample.int(99, sampleSize * timepoints * raters, replace = TRUE),
vB = sample.int(99, sampleSize * timepoints * raters, replace = TRUE),
vC = sample.int(99, sampleSize * timepoints * raters, replace = TRUE),
vZZ = sample.int(99, sampleSize * timepoints * raters, replace = TRUE))
Here are the data:以下是数据:
> tibble(data_long)
# A tibble: 60 x 11
ID time rater v1 v2 v3 v100 vA vB vC vZZ
<int> <int> <chr> <int> <int> <int> <int> <int> <int> <int> <int>
1 1 1 a 14 56 30 75 66 22 8 73
2 1 1 b 90 44 99 8 36 72 1 78
3 1 2 a 92 35 93 46 4 68 39 52
4 1 2 b 51 91 50 67 43 72 99 74
5 1 3 a 80 34 31 31 21 52 7 23
6 1 3 b 24 86 25 86 20 43 74 89
7 2 1 a 58 51 48 60 6 56 66 37
8 2 1 b 96 95 76 1 78 2 65 3
9 2 2 a 88 26 92 86 7 37 84 15
10 2 2 b 93 55 25 62 27 39 73 85
# ... with 50 more rows
In this example, I have three columns that uniquely identify all observations: ID
, time
, and rater
.在这个例子中,我有三个唯一标识所有观察值的列:
ID
、 time
和rater
。 I'd like to widen every other column by rater
(ie, excluding the ID
and time
columns).我想按
rater
扩大所有其他列(即,不包括ID
和time
列)。 My expected output is:我预期的 output 是:
# A tibble: 30 x 18
ID time v1_a v1_b v2_a v2_b v3_a v3_b v100_a v100_b vA_a vA_b vB_a vB_b vC_a vC_b vZZ_a vZZ_b
<int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
1 1 1 14 90 56 44 30 99 75 8 66 36 22 72 8 1 73 78
2 1 2 92 51 35 91 93 50 46 67 4 43 68 72 39 99 52 74
3 1 3 80 24 34 86 31 25 31 86 21 20 52 43 7 74 23 89
4 2 1 58 96 51 95 48 76 60 1 6 78 56 2 66 65 37 3
5 2 2 88 93 26 55 92 25 86 62 7 27 37 39 84 73 15 85
6 2 3 75 2 23 55 28 8 66 74 65 92 58 10 91 65 7 44
7 3 1 86 94 7 87 78 85 38 87 36 49 89 83 33 34 32 38
8 3 2 10 75 12 15 21 18 56 77 54 17 61 92 18 50 98 27
9 3 3 38 81 46 90 20 47 88 15 33 95 66 19 12 27 84 52
10 4 1 32 38 88 68 77 71 10 81 21 54 33 16 90 41 29 72
# ... with 20 more rows
I can widen any given columns using the following syntax:我可以使用以下语法加宽任何给定的列:
data_long %>%
pivot_wider(names_from = rater, values_from = c(v1, v2))
Thus, I could widen all columns by entering all of them manually in a vector:因此,我可以通过在向量中手动输入所有列来加宽所有列:
data_long %>%
pivot_wider(names_from = rater, values_from = c(v1, v2, v3, v100, vA, vB, vC, vZZ))
However, this becomes unwieldy if I have many columns.但是,如果我有很多列,这会变得很笨拙。 Another approach is to widen columns by specifying a range of columns:
另一种方法是通过指定列的范围来加宽列:
data_long %>%
pivot_wider(names_from = rater, values_from = v1:vZZ)
However, this approach does not work well if all columns to be widened are not in a single range, for instance if the ID columns are interspersed throughout the data frame (though it would be possible to specify multiple ranges).但是,如果要加宽的所有列不在一个范围内,例如如果 ID 列散布在整个数据框中(尽管可以指定多个范围),则此方法效果不佳。
Is there a way to use pivot_wider()
to widen ALL columns except for any columns that I specify as columns that uniquely identify each observation using id_cols
(ie, ID
and time
).有没有一种方法可以使用
pivot_wider()
来加宽所有列,除了我指定为使用id_cols
(即ID
和time
)唯一标识每个观察值的列的任何列。 I'd like the solution to be extendable to the case where I have many columns (and thus do not want to specify variable names or ranges for variables to be widened).我希望解决方案可以扩展到我有很多列的情况(因此不想指定变量名称或要扩大的变量范围)。
As we know the first 3 columns, should be fixed, use -
on those column names in values_from
正如我们所知,前 3 列应该是固定的,请在
values_from
中的那些列名上使用-
library(dplyr)
library(tidyr)
data_long %>%
pivot_wider(names_from = rater, values_from = -names(.)[1:3])
Or if we already create an object或者如果我们已经创建了一个 object
id_cols <- c("ID", "time")
data_long %>%
pivot_wider(names_from = rater, values_from = -all_of(id_cols))
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