问题
I have a whole column of numbers that include dot separators at the thousands and comma instead of dot as an dismal separator. When I try to create a numeric column out of them, I lose all data.
var1 <- c("50,0", "72,0", "960,0", "1.920,0", "50,0", "50,0", "960,0")
df <- cbind(var1, var2 = as.numeric(gsub(".", "", as.character(var1))))
and wound up with:
var1 var2
[1,] "50,0" NA
[2,] "72,0" NA
[3,] "960,0" NA
[4,] "1.920,0" NA
[5,] "50,0" NA
[6,] "50,0" NA
[7,] "960,0" NA
What am I doing wrong?
回答1:
You need to escape the "."
in your regular expression, and you need to replace the commas with a "."
before you can convert to numeric.
> as.numeric(gsub(",", ".", gsub("\\.", "", var1)))
[1] 50 72 960 1920 50 50 960
回答2:
For things like these I like scan()
the most, because it is easy to understand. Just use
scan(text=var1, dec=",", sep=".")
Alas, it's not faster than gsub()
, which on the other hand seemes overpowered. Hence another, and fast, option is sub()
:
as.numeric(sub(",", ".", sub(".", "", var1, fixed=TRUE), fixed=TRUE))
And just in case: When you're reading var1
from a file directly, just read it in with a specified separator: read.table("file.txt", dec=",", sep=".")
回答3:
You can use function "type_convert", from "readr" package. I am reading an ODS file (Locale Portuguese), and converting the numbers:
library('readODS')
library('tidyverse')
data <- read_ods('mod-preditivo.ods', sheet=1,col_names = TRUE,range='a1:b30',col_types=NA)
df <- type_convert(data,trim_ws=TRUE,col_types = cols(Pesos=col_integer(),Alturas=col_double()),locale = locale(decimal_mark = ","))
str(df)
来源:https://stackoverflow.com/questions/21027806/replacing-commas-and-dots-in-r