How to convert character of percentage into numeric in R

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一向 2020-11-27 15:29

I run into a problem when converting character of percentage to numeric. E.g. I want to convert \"10%\" into 10%, but

as.numeric(\"10%\")

r

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  • 2020-11-27 15:41

    I wanted to convert an entire column and combined the above answers.

    pct_to_number<- function(x){
      x_replace_pct<-sub("%", "", x)
      x_as_numeric<-as.numeric(x_replace_pct)
      }
    df[['ColumnName']] = pct_to_number(df[['ColumnName']])
    
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  • 2020-11-27 15:42

    Try with:

    > x = "10%"
    > as.numeric(substr(x,0,nchar(x)-1))
    [1] 10
    

    This works also with decimals:

    > x = "10.1232%"
    > as.numeric(substr(x,0,nchar(x)-1))
    [1] 10.1232
    

    The idea is that the symbol % is always at the end of the string.

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  • 2020-11-27 15:46

    10% is per definition not a numeric vector. Therefore, the answer NA is correct. You can convert a character vector containing these numbers to numeric in this fashion:

    percent_vec = paste(1:100, "%", sep = "")
    as.numeric(sub("%", "", percent_vec))
    

    This works by using sub to replace the % character by nothing.

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  • 2020-11-27 15:48

    Remove the "%", convert to numeric, then divide by 100.

    x <- c("10%","5%")
    as.numeric(sub("%","",x))/100
    # [1] 0.10 0.05
    
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  • 2020-11-27 15:53

    Get rid of the extraneous characters first:

    topct <- function(x) { as.numeric( sub("\\D*([0-9.]+)\\D*","\\1",x) )/100 }
    my.data <- paste(seq(20)/2, "%", sep = "")
    > topct( my.data )
     [1] 0.005 0.010 0.015 0.020 0.025 0.030 0.035 0.040 0.045 0.050 0.055 0.060 0.065 0.070 0.075 0.080
    [17] 0.085 0.090 0.095 0.100
    

    (Thanks to Paul for the example data).

    This function now handles: leading non-numeric characters, trailing non-numeric characters, and leaves in the decimal point if present.

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  • 2020-11-27 16:04

    If you're a tidyverse user (and actually also if not) there's now a parse_number function in the readr package:

    readr::parse_number("10%")
    

    The advantage is generalization to other common string formats such as:

    parse_number("10.5%")
    parse_number("$1,234.5")
    
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