Python compare two columns in a pandas df while replacing text using a function

Question

I have a df like this,

Cola    Colb
Mr      Mr..!
Mrs     Mrs.!.
Mr      Tests

I want to compare these two columns ignoring the (. and ! present in Colb) - I can generate a new column while replacing the unwanted characters. But, is there a better way to do it using pandas function ?

The expected results are true for all of the 3 rows.

This is my single line of code for a direct compare,

temp_result_df[res_col_name] = \
((temp_result_df[primaryreportreqcolname] == temp_result_df[RequiredSecondaryReport_Col_Name])\
& (temp_result_df[RequiredSecondaryReport_Col_Name]!= 'Tests'))

New to Python. So, I am exploring the different functions and methods to do a compare with some noise in the data.

What is the expected output? And compare? You mean check if they are equal? — yatu
– yatu, Commented Feb 14, 2019 at 17:06

Vaishali · Accepted Answer · 2019-02-14 17:09:58Z

4

IIUC,

df['res_col_name'] = df['Cola'].eq(df['Colb'].replace('\W+', '', regex = True))  | df['Colb'].eq('Tests')


    Cola    Colb    res_col_name
0   Mr      Mr..!   True
1   Mrs     Mrs.!.  True
2   Mr      Tests   True

answered Feb 14, 2019 at 17:09

Vaishali

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4 Comments

Student of the Digital World Over a year ago

what does \W+ actually do here ?

Vaishali Over a year ago

\W is the regex for non-alphanumeric, so it replaces all characters

Student of the Digital World Over a year ago

Thank you, one last question - so, if I want to replace two letters "A" and "E" by "", then I will be doing something like .replace (''A", "E", '",regex = True) - ??? how can I pass two variables here. I was putting a full stop and an exclamatory mark in question to know this more :)

yatu Over a year ago

No, for that do df.Colb.str.replace('A|E', '')

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