Question

我提到了：

所有示例都基于测试数字向量或其他列中的NA并添加新变量。这是一个简短的可重现的例子：

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)

我想为df$x = dec |添加“winter” jan | feb，“spring”for march | apr | may，“summer”和“autumn”。

我试过

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，但我是一个新手和一个kludger。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'

如果相同的数据框有数千行，我想循环遍历它并根据一年中的某个月为季节创建一个新变量，我该怎么做？我提到：“Looping through a data frame to add a column depending variables in other columns”但这是循环并设置数学运算符来创建新变量。我尝试了外部资源：a thread on the R mailing list和a thread on the TalkStats forum。但是，两者都基于数值变量和条件。

Answer 1

如果您有一个非常大的数据框，那么data.table将对您非常有帮助。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

将列添加到数据框，在其他列中测试分类变量

1 个答案: