将数据框中的数据值重新编码为 R 中的组合值答案

【问题标题】：Recode data values in a dataframe into combined values in R将数据框中的数据值重新编码为 R 中的组合值
【发布时间】：2020-02-03 01:00:32
【问题描述】：

我试图比较婚姻状况，我的变量有“已婚”、“未婚”、“订婚”、“单身”和“未婚”的名称。我怎样才能让这些数据只读作“已婚”和“未婚”？（订婚算已婚，单身不单身算未婚）

样本数据集

data.frame(mstatus = sample(x = c("married", 
                                  "not married", 
                                  "engaged", 
                                  "single", 
                                  "not married"), 
                            size = 15, replace = TRUE))

这是我目前所拥有的

df2 <- df%>%mutate(
  mstatus = (tolower(mstatus))
)

【问题讨论】：

标签： r dataframe

【解决方案1】：

你可以使用dplyr（tidyverse packge）中的mutate()函数：

df <- df %>% dplyr::mutate(mstatus = case_when(
    mstatus == "married" | mstatus == "engaged"  ~ "married",
    mstatus == "not married" | mstatus == "single" ~ "not married"
))

【讨论】：

【解决方案2】：

我想最简单的基本 R 方法是使用 ifelse 语句：

df2$mstatus_new <- ifelse(df2$mstatus=="engaged"|df2$mstatus=="married", "married", "not married")

数据：

df2 <- data.frame(
  mstatus = c("married", "not married", "engaged", "single", "nota married"))
df2
       mstatus
1      married
2  not married
3      engaged
4       single
5 nota married

结果：

df2
       mstatus mstatus_new
1      married     married
2  not married not married
3      engaged     married
4       single not married
5 nota married not married

【讨论】：

【解决方案3】：

如果我们需要重新编码'mstatus，一个选项是forcats

library(dplyr)
library(forcats)
df2 %>%
      mutate(mstatus = fct_recode(mstatus, married = "engaged",
         `not married` = "single"))
#      mstatus
#1     married
#2 not married
#3     married
#4 not married
#5 not married

或者如果要更改的值很多，请使用fct_collapse，它可以采用值向量

df2 %>%
   mutate(mstatus = fct_collapse(mstatus, married = c('engaged'), 
         `not married` = c("single")))

数据

df2 <- structure(list(mstatus = structure(c(2L, 3L, 1L, 4L, 3L), .Label = c("engaged", 
"married", "not married", "single"), class = "factor")),
class = "data.frame", row.names = c(NA, 
-5L))

【讨论】：