dplyr按字符串重新排序行

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问题描述

我有以下数据：

library(tidyverse)


d1 <- data_frame(Nat = c("UK", "UK", "UK", "NONUK", "NONUK", "NONUK"),
 Type = c("a", "b", "c", "a", "b", "c"))

我想重新排列行，使数据帧看起来像这样：

I would like to rearrange the rows so the dataframe looks like this:

d2 <- data_frame(
 Nat = c("UK", "UK", "UK", "NONUK", "NONUK", "NONUK"),
 Type = c("b", "c", "a", "b", "c", "a"))

因此，英国和非英国分组仍然存在，但类型行已经转移了。这个问题很像这样：对以字符串变量为条件的行进行重新排序

So the UK and Non UK grouping remains, but the 'Type' rows have shifted. This questions is quite like this one: Reorder rows conditional on a string variable

但是，以上答案取决于您要重新排序的行的字母顺序（伦敦除外）。有没有一种方法可以更具体地对字符串值进行重新排序，您可以自己选择行的顺序，而不是依赖于字母顺序？

However the answer above is dependent on the rows you are reordering being in alphabetical order (excluding London). Is there a way to reorder a string value more specifically where you select order of the rows yourself, rather than relying on it being alphabetical? Is there a way to do this using dplyr?

谢谢！

推荐答案

您可以使用 match

string_order <- c("b", "c", "a")
d1 %>%
  group_by(Nat) %>%
  mutate(Type = Type[match(string_order, Type)]) %>%
  ungroup()
#  A tibble: 6 x 2
#  Nat   Type
#  <chr> <chr>
#1 UK    b
#2 UK    c
#3 UK    a
#4 NONUK b
#5 NONUK c
#6 NONUK a

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