计算 R 中跨列的因子
Calculate factors across columns in R
我需要将一系列 character 列转换为 factors。然后我需要 factors 跨列映射到相应的枚举值，当它们被转换为类型 numeric.
as.numeric(as.factor(characterColumnDataFrame))
这目前 returns 每列独立分解，因此结果数字与列中的相应字符串不匹配。
想尝试避免转换一列然后从第一列查找和映射枚举。
创建因子时使用levels=。 DF 有字符列，而 DF2 有因子列都具有相同的水平，levs。
# test data frame
DF <- as.data.frame(matrix(letters,, 2), stringsAsFactors = FALSE)
DF2 <- DF
levs <- sort(unique(unlist(DF)))
DF2[] <- lapply(DF2, factor, levels = levs)
这可以像这样写成一行：
DF2 <- replace(DF, TRUE, lapply(DF, factor, levels = sort(unique(unlist(DF)))))
library(zoo)
test = xtsCharacterObjectWithManyColumns
xts::coredata(test) = as.numeric(factor(test, levels = unique(test), ordered = T))
base::storage.mode(test) = "numeric"
Hadley Wickham 的 forcats 包中的 fct_unify() 函数统一了因子列表中的水平。
# using G. Grothendieck's test data frame
DF <- as.data.frame(matrix(letters,, 2), stringsAsFactors = FALSE)
str(DF)
'data.frame': 13 obs. of 2 variables:
$ V1: chr "a" "b" "c" "d" ...
$ V2: chr "n" "o" "p" "q" ...
DF[] <- lapply(DF, factor)
str(DF)
'data.frame': 13 obs. of 2 variables:
$ V1: Factor w/ 13 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10 ...
$ V2: Factor w/ 13 levels "n","o","p","q",..: 1 2 3 4 5 6 7 8 9 10 ...
DF[] <- forcats::fct_unify(DF)
str(DF)
'data.frame': 13 obs. of 2 variables:
$ V1: Factor w/ 26 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10 ...
$ V2: Factor w/ 26 levels "a","b","c","d",..: 14 15 16 17 18 19 20 21 22 23 ...
或作为产生统一因子水平数的单线：
DF[] <- lapply(forcats::fct_unify(lapply(DF, factor)), as.numeric)
DF
V1 V2
1 1 14
2 2 15
3 3 16
4 4 17
5 5 18
6 6 19
7 7 20
8 8 21
9 9 22
10 10 23
11 11 24
12 12 25
13 13 26
我需要将一系列 character 列转换为 factors。然后我需要 factors 跨列映射到相应的枚举值，当它们被转换为类型 numeric.
as.numeric(as.factor(characterColumnDataFrame))
这目前 returns 每列独立分解，因此结果数字与列中的相应字符串不匹配。
想尝试避免转换一列然后从第一列查找和映射枚举。
创建因子时使用levels=。 DF 有字符列，而 DF2 有因子列都具有相同的水平，levs。
# test data frame
DF <- as.data.frame(matrix(letters,, 2), stringsAsFactors = FALSE)
DF2 <- DF
levs <- sort(unique(unlist(DF)))
DF2[] <- lapply(DF2, factor, levels = levs)
这可以像这样写成一行：
DF2 <- replace(DF, TRUE, lapply(DF, factor, levels = sort(unique(unlist(DF)))))
library(zoo)
test = xtsCharacterObjectWithManyColumns
xts::coredata(test) = as.numeric(factor(test, levels = unique(test), ordered = T))
base::storage.mode(test) = "numeric"
Hadley Wickham 的 forcats 包中的 fct_unify() 函数统一了因子列表中的水平。
# using G. Grothendieck's test data frame
DF <- as.data.frame(matrix(letters,, 2), stringsAsFactors = FALSE)
str(DF)
'data.frame': 13 obs. of 2 variables: $ V1: chr "a" "b" "c" "d" ... $ V2: chr "n" "o" "p" "q" ...
DF[] <- lapply(DF, factor)
str(DF)
'data.frame': 13 obs. of 2 variables: $ V1: Factor w/ 13 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10 ... $ V2: Factor w/ 13 levels "n","o","p","q",..: 1 2 3 4 5 6 7 8 9 10 ...
DF[] <- forcats::fct_unify(DF)
str(DF)
'data.frame': 13 obs. of 2 variables: $ V1: Factor w/ 26 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10 ... $ V2: Factor w/ 26 levels "a","b","c","d",..: 14 15 16 17 18 19 20 21 22 23 ...
或作为产生统一因子水平数的单线：
DF[] <- lapply(forcats::fct_unify(lapply(DF, factor)), as.numeric)
DF
V1 V2 1 1 14 2 2 15 3 3 16 4 4 17 5 5 18 6 6 19 7 7 20 8 8 21 9 9 22 10 10 23 11 11 24 12 12 25 13 13 26