Multi tool use

Clean special character, numeric and character

I have a variable like below in my dataframe

df$emp_length(10+ years, <1 year, 8 years)


I need to clean this variable for better analysis. Example, I want to compare this variable with other categorical or numerical variable. What is the best way to seperate this variable in to multiple columns.

I am thinking to separate this variable based on space something like below,

df$emp_length = c(10+, <1, 8)
df$years = c(years, years, years)


Also I would like to know if the number with special characters like + and < will be considered as numeric in R or I have to separate special character and numbers?

I want to have emp_length variable as numeric and years variable as character.

Please help!

10+

<1

1 Answer
1

One can use tidyr::extract to first separate emp_length in 2 columns. Then replace any symbol (anything other than 0-9) to "" in column with number and then convert it to numeric.

tidyr::extract

emp_length

0-9

""

Option#1: Keep the symbol with number

library(tidyverse)
df <- df %>% extract(emp_length, c("emp_length", "years"),
regex="([[:digit:]+<]+)\s+(\w+)")

df
# emp_length years
# 1 10+ years
# 2 <1 year
# 3 8 years


Option#2: Just number but column is numeric

library(tidyverse)

df <- df %>%
extract(emp_length, c("emp_length", "years"), regex="([[:digit:]+<]+)\s+(\w+)") %>%
mutate(emp_length = as.numeric(gsub("[^0-9]","\1",emp_length)))

df
# emp_length years
# 1 10 years
# 2 1 year
# 3 8 years


Data:

df <- data.frame(emp_length = c("10+ years", "<1 year", "8 years"),
stringsAsFactors = FALSE)


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