將數據幀中的數據值重新編碼為 R 中的組合值

Question

我試圖比較婚姻狀況，我的變量名稱為“已婚”、“未婚”、“訂婚”、“單身”和“未婚”。 我如何使這些數據僅讀作“已婚”和“未婚”？ （訂婚算作已婚，未婚，未婚算作未婚）

樣本數據集

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

這是我到目前為止

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

Answer 1

您可以使用dplyr (tidyverse packge) 中的mutate()函數：

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

Answer 2

我想最簡單的基本 R 方法是使用ifelse語句：

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

數據：

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

結果：

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

Answer 3

如果我們需要重新編碼 'mstatus，一種選擇是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，如果有很多值要更改，請使用fct_collapse ，它可以采用值向量

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

數據

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))