我想将data.frame包含 130 多列的整个转换为数字。
我知道我需要使用as.numeric,但问题是我必须将这个函数分别应用到 130 列中的每一列。我尝试将其应用于整个data.frame,但收到以下错误消息:
Error: (list) object cannot be coerced to type 'double'
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我怎样才能通过相对较短的代码做到这一点?
akr*_*run 10
一个选项dplyr
library(dplyr)
df1 %>%
mutate_all(as.numeric)
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如果列是factor类,则转换为character,然后转换为numeric
df1 %>%
mutate_all(funs(as.numeric(as.character(.)))
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character另请注意,如果任何单元格中都没有元素,则在列type.convert上使用character
df1 %>%
mutate_all(funs(type.convert(as.character(.)))
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如果效率很重要,一种选择是data.table
library(data.table)
DF1 <- copy(DF) # from other post
system.time({setDT(DF1)
for(j in seq_along(DF1)) set(DF1, i = NULL, j=j, value = as.numeric(DF1[[j]]))
})
# user system elapsed
# 0.032 0.005 0.037
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在基础 R 中,我们可以执行以下操作:
df[] <- lapply(df, as.numeric)
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或者
df[cols_to_convert] <- lapply(df[cols_to_convert], as.numeric)
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这是解决方案的基准(忽略对因素的考虑):
DF <- data.frame(a = 1:10000, b = letters[1:10000],
c = seq(as.Date("2004-01-01"), by = "week", len = 10000),
stringsAsFactors = TRUE)
DF <- setNames(do.call(cbind,replicate(50,DF,simplify = F)),paste0("V",1:150))
dim(DF)
# [1] 10000 150
library(dplyr)
n1tk <- function(x) data.frame(data.matrix(x))
mm <- function(x) {x[] <- lapply(x,as.numeric); x}
akrun <- function(x) mutate_all(x, as.numeric)
mo <- function(x) {for(i in 1:150){ x[, i] <- as.numeric(x[, i])}}
microbenchmark::microbenchmark(
akrun = akrun(DF),
n1tk = n1tk(DF),
mo = mo(DF),
mm = mm(DF)
)
# Unit: milliseconds
# expr min lq mean median uq max neval
# akrun 152.9837 177.48150 198.292412 190.38610 206.56800 432.2679 100
# n1tk 10.8700 14.48015 22.632782 17.43660 21.68520 89.4694 100
# mo 9.3512 11.41880 15.313889 14.71970 17.66530 37.6390 100
# mm 4.8294 5.91975 8.906348 7.80095 10.11335 71.2647 100
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