如何在 R 中更改多列的数据类型?
How to change multiple columns' data type in R?
我想将所有以 _FL 结尾的字段从字符转换为数字。我认为这段代码可以工作,但事实并非如此:所有这些字段都填满了 NA。怎么了?
library(data.table)
#s = fread('filename.csv',header = TRUE,sep = ";",dec = ".")
s=data.table(ID=(1:10), B=rnorm(10), C_FL=c("I","N"), D_FL=(0:1), E_FL=c("N","I"))
cn=colnames(s)
# Change all fields ending with _FL from "N"/"I" to numeric 0/1
for (i in cn){
if(substr(i,nchar(i)-2,nchar(i))=='_FL'){
s[,i] = as.numeric(gsub("I",1,gsub("N",0,s[,i])))
}
}
一种方法,
library(data.table)
#create function to change the values
f1 <- function(x){ifelse(x == 'N', 1, ifelse(x == 'I', 0, x))}
#get the columns to apply the function
ind <- names(s)[grepl('_fl', names(s))]
s[, (ind) := lapply(.SD, f1), .SDcols = ind]
#to convert to numeric then,
s[, (ind) := lapply(.SD, as.numeric), .SDcols = ind]
s
# id b c_fl d_fl e_fl
# 1: 1 0.20818371 0 0 1
# 2: 2 -0.06470128 1 1 0
# 3: 3 -1.03487884 0 0 1
# 4: 4 1.38119541 1 1 0
# 5: 5 -0.67924124 0 0 1
# 6: 6 0.84424732 1 1 0
# 7: 7 -0.65531266 0 0 1
# 8: 8 0.44867938 1 1 0
# 9: 9 0.15805731 0 0 1
#10: 10 -0.42541642 1 1 0
str(s)
Classes ‘data.table’ and 'data.frame': 10 obs. of 5 variables:
$ id : int 1 2 3 4 5 6 7 8 9 10
$ b : num 0.7464 -0.7491 -0.7144 0.561 0.0243 ...
$ c_fl: num 0 1 0 1 0 1 0 1 0 1
$ d_fl: num 0 1 0 1 0 1 0 1 0 1
$ e_fl: num 1 0 1 0 1 0 1 0 1 0
- attr(*, ".internal.selfref")=<externalptr>
另一种选择是使用intersect()
找到包含“_FL”的character
列,并根据条件== "N"
:[=14=将它们转换为二进制列]
library(data.table)
# Find relevant columns
chr.cols <- names(s)[intersect(which(sapply(s,is.character)),
grep("_FL", names(s)))]
# Convert to numeric
for(col in chr.cols) set(s, j = col, value = as.numeric(s[[col]] == "N"))
# See result
> s
ID B C_FL D_FL E_FL
1: 1 0.6175364 0 0 1
2: 2 -0.9500318 1 1 0
3: 3 -0.6341547 0 0 1
4: 4 -0.8055696 1 1 0
5: 5 -0.3139938 0 0 1
6: 6 0.4676558 1 1 0
7: 7 1.6455591 0 0 1
8: 8 -0.4544377 1 1 0
9: 9 0.3512442 0 0 1
10: 10 0.3828367 1 1 0
我想将所有以 _FL 结尾的字段从字符转换为数字。我认为这段代码可以工作,但事实并非如此:所有这些字段都填满了 NA。怎么了?
library(data.table)
#s = fread('filename.csv',header = TRUE,sep = ";",dec = ".")
s=data.table(ID=(1:10), B=rnorm(10), C_FL=c("I","N"), D_FL=(0:1), E_FL=c("N","I"))
cn=colnames(s)
# Change all fields ending with _FL from "N"/"I" to numeric 0/1
for (i in cn){
if(substr(i,nchar(i)-2,nchar(i))=='_FL'){
s[,i] = as.numeric(gsub("I",1,gsub("N",0,s[,i])))
}
}
一种方法,
library(data.table)
#create function to change the values
f1 <- function(x){ifelse(x == 'N', 1, ifelse(x == 'I', 0, x))}
#get the columns to apply the function
ind <- names(s)[grepl('_fl', names(s))]
s[, (ind) := lapply(.SD, f1), .SDcols = ind]
#to convert to numeric then,
s[, (ind) := lapply(.SD, as.numeric), .SDcols = ind]
s
# id b c_fl d_fl e_fl
# 1: 1 0.20818371 0 0 1
# 2: 2 -0.06470128 1 1 0
# 3: 3 -1.03487884 0 0 1
# 4: 4 1.38119541 1 1 0
# 5: 5 -0.67924124 0 0 1
# 6: 6 0.84424732 1 1 0
# 7: 7 -0.65531266 0 0 1
# 8: 8 0.44867938 1 1 0
# 9: 9 0.15805731 0 0 1
#10: 10 -0.42541642 1 1 0
str(s)
Classes ‘data.table’ and 'data.frame': 10 obs. of 5 variables:
$ id : int 1 2 3 4 5 6 7 8 9 10
$ b : num 0.7464 -0.7491 -0.7144 0.561 0.0243 ...
$ c_fl: num 0 1 0 1 0 1 0 1 0 1
$ d_fl: num 0 1 0 1 0 1 0 1 0 1
$ e_fl: num 1 0 1 0 1 0 1 0 1 0
- attr(*, ".internal.selfref")=<externalptr>
另一种选择是使用intersect()
找到包含“_FL”的character
列,并根据条件== "N"
:[=14=将它们转换为二进制列]
library(data.table)
# Find relevant columns
chr.cols <- names(s)[intersect(which(sapply(s,is.character)),
grep("_FL", names(s)))]
# Convert to numeric
for(col in chr.cols) set(s, j = col, value = as.numeric(s[[col]] == "N"))
# See result
> s
ID B C_FL D_FL E_FL
1: 1 0.6175364 0 0 1
2: 2 -0.9500318 1 1 0
3: 3 -0.6341547 0 0 1
4: 4 -0.8055696 1 1 0
5: 5 -0.3139938 0 0 1
6: 6 0.4676558 1 1 0
7: 7 1.6455591 0 0 1
8: 8 -0.4544377 1 1 0
9: 9 0.3512442 0 0 1
10: 10 0.3828367 1 1 0