Use of Replace() in Python Dataframe for Multiple Columns but same value

Question

Query: I need to replace the 1 old value with the 1 new value for a bunch of columns (not all columns) in a dataframe. The question is about the syntax to be used. Is there a shorter syntax?

Sample Dataframe:

df = pd.DataFrame({'A': [0,1,2,3,4],
                   'B': [5,6,7,0,9],
                   'C': [2,0,9,3,0],
                   'D': [1,3,0,5,2]})

I need all 0 to be replaced with 10 in the above df but only for column A and C (Not for B or D).

Code that I use to do this:

Method 1: Two separate commands.

df['A'].replace({0:10},inplace=True)
df['C'].replace({0:10},inplace=True)

Method 2: One command using dictionary in dictionary

df.replace({'A': {0:10}, 'C': {0:10}},inplace=True)

Method 3: Keeping new value out of dictionary

df.replace({'A':0,'C':0},10,inplace=True)

Expected Outcome:

    A  B   C  D
0  10  5   2  1
1   1  6  10  3
2   2  7   9  0
3   3  0   3  5
4   4  9  10  2

I am able to get expected outcome using all three methods. But I have a doubt that can we give a list of columns and enter old and new values for replacement only once?

Something like:

df.replace({['col_ref'...]:{'old':'new'})
#OR
df['col_ref'...].replace()

In my scenario, there are 26 columns out of 52 that need replacing, and the value is to be replaced through a regex command. Now I can store the regex command as a variable and use the method 2 to do this. But this also requires entering the variable name for 26 times. Is there any shorter way where I can enter these 26 columns and the regex replacement {'r':'r2'} only once?

Answer 1

I tried this.

for col in [list of columns]:
    df.replace({col:{'r':'r2'}},regex=True,inplace=True)

This is the shortest way I could think of to write minimum code characters.

However, if there is a faster way, other answers are welcome.

Answer 2

I was looking on how to do this quicker myself this week and found this method and setup to handle instead of a for loop:

col_list = ['A', 'B']
df[col_list] = df[col_list.replace(0,10,inplace=True)

If you are using regex for a string:

col_list = ['A', 'B']
df[col_list] = df[col_list.replace('[\$,]','',regex=True, inplace=True)