r - 计算数据框中分类变量的出现次数 (R)

Question

这个问题在这里已经有了答案:

Faster ways to calculate frequencies and cast from long to wide (4 个回答)

关闭 4年前。

我有数据框:

station     date        classification
 1    June - 01/16          A
 2    June - 03/16          B
 1    June - 01/16          A
 7    June - 01/16          C
 1    June - 03/16          A
 2    June - 03/16          B
 2    June - 03/16          B

我想得到A、B、C的总出现次数，按站号和日期汇总:

例如，6 月 1 日的第 1 站有 2 个 As，而 6 月 3 日的第 2 站有 3 个 B。

我试过了，

aggregate(x = list(data_frame$classification), by = list(station=data_frame$station, Date=data_frame$date), function(x) length(unique(x))

Answer 1

如果我们需要'A'，'B'和'C'的计数，那么reshape可能会更好。我们将 'data.frame' 转换为 'data.table' (setDT(data_frame)) 并使用 data.table 中的 dcast 来 reshape 从 'long' 到 'wide' 格式，将 fun.aggregate 指定为 length。

library(data.table)
dcast(setDT(data_frame), station+date~classification, length)
#   station         date A B C
#1:       1 June - 01/16 2 0 0
#2:       1 June - 03/16 1 0 0
#3:       2 June - 03/16 0 3 0
#4:       7 June - 01/16 0 0 1

---

dplyr 选项是

library(dplyr)
data_frame %>%
        group_by(station, date, classification) %>%
        tally()
# station         date classification     n
#    (int)        (chr)          (chr) (int)
#1       1 June - 01/16              A     2
#2       1 June - 03/16              A     1
#3       2 June - 03/16              B     3
#4       7 June - 01/16              C     1

数据

data_frame <- structure(list(station = c(1L, 2L, 1L, 7L, 1L, 2L, 2L), 
date = c("June - 01/16", 
"June - 03/16", "June - 01/16", "June - 01/16", "June - 03/16", 
"June - 03/16", "June - 03/16"), classification = c("A", "B", 
"A", "C", "A", "B", "B")), .Names = c("station", "date", "classification"
), class = "data.frame", row.names = c(NA, -7L))