How to replace multiple string columns to binary values (0 and 1) in a dataframe?

Question

I am trying to get a binary matrix but first I need to replace multiple string columns to binary values (0 and 1). I tried to get it in R and python but the code didn't work. I was wondering if someone could help me.

I have a matrix of 29,584 rows x 982 columns, similar like:

  G       X4646466.555  X564737373.455  X737347474.56   
0 add     bp_ggfgfgg    
1 fgr     bb_jhfjfjf    bpp_fhfhfhf     bb_jfjfjf
2 dfr
3 tth                   bb_jdjfjdd
4 dee     bp_djdjdd
5 ee                    bp_dhsdhdh
6 ff                    bb_hfhfhf       bpp_dfhdhdhd
...

For each column that start with X, there are various string values. These values start in bb_, bpp_ and bp_. In addition, there are missing data (in blank). I would like to replace with 1 all the string values from each column that start witn X (or all columns except G) and to replace with 0 the missing data from the columns that start with X.

I am attaching a imagen of the dataframe.

Are you looking for an answer in python or in R?

Martin Gal
– Martin Gal

2021-08-03 18:18:25 +00:00
Commented Aug 3, 2021 at 18:18 — Martin Gal
– Martin Gal, Commented Aug 3, 2021 at 18:18

akrun · Accepted Answer · 2021-08-03 18:28:06Z

2

We can use

library(dplyr)
df2 <- df1 %>%
    mutate(across(starts_with('X'), ~ +(!is.na(.)))

edited Aug 3, 2021 at 18:28

answered Aug 3, 2021 at 18:25

akrun

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Comments

TarJae · Accepted Answer · 2021-08-03 18:38:17Z

We could use mutate across with case_when:

library(dplyr)
df %>% 
    dplyr::mutate(across(starts_with("X"), ~case_when(is.na(.) ~ 0,
                                                TRUE ~ 1)))

# A tibble: 7 x 5
  G     X4646466.555 X564737373.455 X737347474.56    X5
  <chr>        <dbl>          <dbl>         <dbl> <dbl>
1 add              1              0             0     0
2 fgr              1              1             1     0
3 dfr              0              0             0     0
4 tth              1              0             0     0
5 dee              1              0             0     0
6 ee               1              0             0     0
7 ff               1              1             0     0

OR

library(tidyverse)
df1 <- df[,-1] %>% 
    modify(~ ifelse(is.na(.), 0,1))
    
cbind(df[,1],df1)

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