将列添加到数据框，测试其他列中的分类变量

我已经提到过：

• 如何根据另一列的条件语句将因子列添加到数据框？ https://stackoverflow.com/questions/16570302/how-to-add-a-factor-column-to-dataframe-based-on-a-conditional-statement-from-an,
• 如何在R编程中根据条件将列添加到数据框中 https://stackoverflow.com/questions/15016723/how-to-add-column-into-a-dataframe-based-on-condition-in-r-programming and
• R：添加对三列进行条件检查的列？ https://stackoverflow.com/questions/6557714/r-add-column-with-condition-check-on-three-columns .

所有示例均基于对其他列中的数值向量或 NA 进行测试并添加新变量。这是一个简短的可重现示例：

x <- c("dec 12", "jan 13", "feb 13", "march 13", "apr 13", "may 13",
       "june 13", "july 13", "aug 13", "sep 13", "oct 13", "nov 13")
y <- c(234, 678, 534, 122, 179, 987, 872, 730, 295, 450, 590, 312)
df<-data.frame(x,y)

我想加上“冬天”df$x= 十二月 |一月 |二月，“春天”，三月|四月|五月，“夏天”和“秋天”。

I tried

df$season <- ifelse(df[1:3, ], "winter", ifelse(df[4:6, ], "spring", 
                    ifelse(df[7:9, ], "summer", "autumn")))

我知道这是一种非常低效的做事方式，但我是一个新手，也是一个混杂者。它返回了错误：

Error in ifelse(df[1:3, ], "winter", ifelse(df[4:6, ], "spring",
ifelse(df[7:9,  : (list) object cannot be coerced to type 'logical'

如果同一个数据框有数千行，并且我想循环遍历它并根据一年中的月份为季节创建一个新变量，我该怎么做？我提到：”循环遍历数据框以添加依赖于其他列中的变量的列 https://stackoverflow.com/questions/18336343/looping-through-a-data-frame-to-add-a-column-depending-variables-in-other-column“但这是循环并设置一个数学运算符来创建新变量。我尝试了外部资源：R 邮件列表中的一个帖子 http://r.789695.n4.nabble.com/R-help-Adding-a-column-in-a-data-frame-with-multiple-conditions-td4645072.html and TalkStats 论坛上的一个帖子 http://www.talkstats.com/showthread.php/30924-Adding-a-new-column-in-R-data-frame-with-values-conditional-on-another-column。然而，两者都是基于数值变量和条件。

如果你有一个非常大的数据框，那么data.table会对你很有帮助。以下作品：

library(data.table)
x <- c("dec 12", "jan 13", "feb 13", "march 13", "apr 13", "may 13",
   "june 13", "july 13", "aug 13", "sep 13", "oct 13", "nov 13")
y <- c(234, 678, 534, 122, 179, 987, 872, 730, 295, 450, 590, 312)
df <-data.frame(x,y)
DT <- data.table(df)
DT[, month := substr(tolower(x), 1, 3)]
DT[, season := ifelse(month %in% c("dec", "jan", "feb"), "winter",
               ifelse(month %in% c("mar", "apr", "may"), "spring",
               ifelse(month %in% c("jun", "jul", "aug"), "summer", 
               ifelse(month %in% c("sep", "oct", "nov"), "autumn", NA))))]
DT
          x   y month season
1:   dec 12 234   dec winter
2:   jan 13 678   jan winter
3:   feb 13 534   feb winter
4: march 13 122   mar spring
5:   apr 13 179   apr spring
6:   may 13 987   may spring
7:  june 13 872   jun summer
8:  july 13 730   jul summer
9:   aug 13 295   aug summer
0:   sep 13 450   sep autumn
1:   oct 13 590   oct autumn
12:  nov 13 312   nov autumn