CODEWITHSUNDEEP
pythonpandaslambda
Ling
Ling

Reputation: 359

How to apply lambda function to multiple columns

I have a dataframe, need to apply the same lambda function to multiple columns.

sample data: 

col1                    col2                  col3 
xxx;#2;yyy              zzz;#46;zyzcz        1
aaa;#3;bbbccc           bbbb;cccc;dd#5        2

I need to clean up and result should be as below: 

col1                    col2                  col3 
xxx;yyy                 zzz;zyzcz             1
aaa;bbbccc              bbbb;cccc;dd          2

function I used: 

def cleanDigit(row):
    replacements = [('\d', ''), ('#', ''), (';;', ';')]

    for (old, new) in replacements: 
        row = re.sub(old, new, row)

    return row

code to apply function to multiple columns: 

df[['col1', 'col2']] = df[['col1', 'col2']] .apply(lambda r: cleanDigit(r))

Error message:

TypeError: ('expected string or buffer', u'occurred at index col1')

Upvotes: 1

Views: 580

Answers (1)

jezrael
jezrael

Reputation: 862641

Use DataFrame.applymap, also lambda function should be omit and pass only function:

df[['col1', 'col2']] = df[['col1', 'col2']].applymap(cleanDigit)
print (df)
         col1          col2  col3
0     xxx;yyy     zzz;zyzcz     1
1  aaa;bbbccc  bbbb;cccc;dd     2

Upvotes: 2

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