仅在 R (dplyr) 中满足特定条件的情况下，用另一列数据替换一列中的某些数据

Question

我有一个包含 30 多列和 10000 多行的扩展数据框。今天我想关注两栏：languages 和 languages2:

languages             languages2

Spanish                  NA
Spanish                  NA
Other (specify)        French
Other (specify)        German
Other (specify)        Russian
English                  NA
Other (specify)        Portuguese
English                  NA
(...)

这是我需要的：

languages

Spanish
Spanish
French
German
Russian
English
Portuguese
English
(...)

我正在使用来自 dplyr

的 mutate 函数寻找答案

Answer 1

data %>% 
  mutate(languages=if_else(languages=="Other (specify)", languages2, languages)

Answer 2

对于更大的数据，您可能需要控制其他情况，例如防止用 NA 替换数据并保留 Other 值。此外，如果解决第一列可能包含 Other() 或 Other, lang 的情况可能有好处。您可能要考虑使用正则表达式或 pre-processing 第一列。

library("tidyverse")
dta <- tribble(
    ~lang1, ~lang2,
    "Spanish", NA,
    "Other", "English",
    "Other", NA
)

mutate(dta, lang1 = case_when(
    grepl("^Other,*", lang1) & !is.na(lang2) ~ lang2,
    TRUE ~ lang1
))

Answer 3

另一种可能性（如果您希望检查在第 2 列而不是第 1 列）：

library(dplyr)

df <- data.frame(languages=c("Spanish","Spanish","Other (specify)","Other (specify)","Other (specify)","English","Other (specify)","English"),languages2=c(NA,NA,"French","German","Russian",NA,"Portuguese",NA))

df %>%
 mutate(languages=if_else(!is.na(languages2), languages2, languages))

   languages languages2
1    Spanish       <NA>
2    Spanish       <NA>
3     French     French
4     German     German
5    Russian    Russian
6    English       <NA>
7 Portuguese Portuguese
8    English       <NA>

Answer 4

使用dplyr，我们可以用NA替换Other (specify)，然后使用coalesce:

library(dplyr)

df %>%
  mutate(languages = coalesce(na_if(languages, "Other (specify)"), languages2)) %>%
  select(languages)

输出

  languages
1    Spanish
2    Spanish
3     French
4     German
5    Russian
6    English
7 Portuguese
8    English

一个 tidyverse 选项是使用 str_replace_all 将 Other (specify) 替换为 languages2.

中的值

library(tidyverse)

df %>%
  mutate(languages = str_replace_all(languages,"Other \(specify\)", languages2)) %>% 
  select(languages)

数据

df <- structure(list(languages = c("Spanish", "Spanish", "Other (specify)", 
"Other (specify)", "Other (specify)", "English", "Other (specify)", 
"English"), languages2 = c(NA, NA, "French", "German", "Russian", 
NA, "Portuguese", NA)), class = "data.frame", row.names = c(NA, 
-8L))

基准

但是，如果您有大量数据并且需要更快的速度，那么您可以考虑 base R，它比 dplyr 或 data.table.

更快

bm <- microbenchmark::microbenchmark(Konrad = mutate(df, languages = case_when(
  grepl("^Other,*", languages) & !is.na(languages2) ~ languages2,
  TRUE ~ languages
)),
langtang = df %>%
  mutate(languages=if_else(languages=="Other (specify)", languages2, languages)),
valentina = df %>%
  mutate(languages=if_else(!is.na(languages2), languages2, languages)),
andrew_stringr = df %>%
  mutate(languages = str_replace_all(languages,"Other \(specify\)", languages2)),
andrew_coalesce = df %>%
  mutate(languages = coalesce(na_if(languages, "Other (specify)"), languages2, 'Other (specify)')),
andrew_baseR = {df1 <- df; df1[df1$languages == "Other (specify)", "languages"] <- df1[df1$languages == "Other (specify)", "languages2" ]},
andrew_baseR_with = {df2 <- df; df2$languages <- with( df2, ifelse( languages == "Other (specify)", languages2, languages ) )},
andrew_datatable = {dt <- as.data.table(df); dt[languages == "Other (specify)", languages := languages2 ]},
times = 1000)

仅在 R (dplyr) 中满足特定条件的情况下，用另一列数据替换一列中的某些数据

Replacing some data from a column with another column data only where a certain condition is met in R (dplyr)

r

data-manipulation

data-analysis

dplyr