使用collect()将两个(或更多)列组收集为两个(或更多)键值对 [英] Using gather() to gather two (or more) groups of columns into two (or more) key-value pairs

问题描述

我想将两个单独的列组收集到两个键值对中.这是一些示例数据:

I want to gather two seperate groups of columns into two key-value pairs. Here's some example data:

library(dplyr)
library(tidyr)
ID = c(1:5)
measure1 = c(1:5)
measure2 = c(6:10)
letter1 = c("a", "b", "c", "d", "e")
letter2 = c("f", "g", "h", "i", "j")

df = data.frame(ID, measure1, measure2, letter1, letter2)
df = tbl_df(df)
df$letter1 <- as.character(df$letter1)
df$letter2 <- as.character(df$letter2)

我希望两个度量列(measure1和measure2)的值在同一列中(键-值对)旁边，并带有键列.我也想要相同的letter1和letter2.我认为我可以使用select()创建两个不同的数据集，分别在两个数据集上使用collect，然后加入(这可行):

I want the values of the two measure columns (measure1 and measure2) to be in one column with a key-column next to it (the key-value pair). I also want the same for letter1 and letter2. I figured that I could use select() to create two different datasets, use gather seperately on both datasets and then join (this worked):

df_measure = df %>% 
  select(ID, measure1, measure2) %>% 
  gather(measure_time, measure, -ID) %>% 
  mutate(id.extra = c(1:10))
df_letter = df %>% 
  select(ID, letter1, letter2) %>% 
  gather(letter_time, letter, -ID) %>% 
  mutate(id.extra = c(1:10))
df_long = df_measure %>% 
  left_join(df_letter, by = "id.extra")

因此(在这种情况下)这可以很好地工作，但是我想这可以做得更优雅(无需拆分或创建"id.extra"之类的东西).因此，请对此加以说明！

So this works perfectly (in this case), but i guess this could be done more elegantly (without stuff like splitting or creating 'id.extra').So please shed some light on it!

推荐答案

您可以使用类似以下内容的东西.从您当前的方法来看，我不确定这是否正是您想要的输出，因为它似乎包含很多冗余信息.

You can use something like the following. I'm not sure from your current approach if this is exactly your desired output or not since it seems to contain a lot of redundant information.

df %>%
  gather(val, var, -ID) %>%
  extract(val, c("value", "time"), regex = "([a-z]+)([0-9]+)") %>%
  spread(value, var)
# # A tibble: 10 × 4
#       ID  time letter measure
# *  <int> <chr>  <chr>   <chr>
# 1      1     1      a       1
# 2      1     2      f       6
# 3      2     1      b       2
# 4      2     2      g       7
# 5      3     1      c       3
# 6      3     2      h       8
# 7      4     1      d       4
# 8      4     2      i       9
# 9      5     1      e       5
# 10     5     2      j      10

---

使用"data.table"中的melt + patterns更容易做到这一点:

---

This is much more easily done with melt + patterns from "data.table":

library(data.table)
melt(as.data.table(df), measure.vars = patterns("measure", "letter"))

---

或者您可能是老派，只使用基数R中的reshape.但是请注意，基数R的reshape不喜欢"tibbles"，因此您必须使用as.data.frame对其进行转换.) /p>

---

Or you can be old-school and just use reshape from base R. Note, however, that base R's reshape does not like "tibbles", so you have to convert it with as.data.frame).

reshape(as.data.frame(df), direction = "long", idvar = "ID", 
        varying = 2:ncol(df), sep = "")

这篇关于使用collect()将两个(或更多)列组收集为两个(或更多)键值对的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！