remove_all_non_numbers_from_selected_columns #r

remove_all_non_numbers_from_selected_columns_in_R

####  Remove all non-number ####
library(tidyverse)
library(readr)

numbers<-c(1,2,3,4,5,6,7,8,9,10,11)
numbers_with_some_characters<-c("1","2zwei","3","4vier","5","6 sechs","7","8 ", " 9", "1 0", " 1 1 ")


data_to_show_remove_nonnumbers<-data.frame(numbers, numbers_with_some_characters)

cleaned<-data_to_show_remove_nonnumbers %>% 
  mutate_at(vars(numbers, numbers_with_some_characters), funs(gsub("[^0-9.-]", "", .)))

table(cleaned$numbers_with_some_characters)
is.numeric(cleaned$numbers_with_some_characters)
# if we want to turn it directly into numeric 
cleaned<-data_to_show_remove_nonnumbers %>% 
  mutate_at(vars(numbers, numbers_with_some_characters), funs(as.numeric((gsub("[^0-9.-]", "", .)))))
table(cleaned$numbers_with_some_characters)
is.numeric(cleaned$numbers_with_some_characters)



# there is also the nice command parse_number from the readr package, 
# but it throws an error of one column is already a number 

cleaned2d<-data_to_show_remove_nonnumbers %>% 
mutate_at(vars(numbers, numbers_with_some_characters), parse_number)