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I have a question about some code.

So I have two dataframes, df1 and df2. df1 looks like the following:

name     irrelevant_data_1
Kate     'some irrelevant data 1'
Mary     'some irrelevant data 1'
Max      'some irrelevant data 1'
Ethan    'some irrelevant data 1'
Peter    'some irrelevant data 1'
John     'some irrelevant data 1'

And df2 looks like this:

name    irrelevant_data_2
Mary    'some irrelevant data 2'
Max     'some irrelevant data 2'
Ethan   'some irrelevant data 2'

I need to filter df1 so that it only includes the rows in which the name column is in df2. The final look of df1 should be:

name    irrelevant_data_1
Mary    'some irrelevant data 1'
Max     'some irrelevant data 1'
Ethan   'some irrelevant data 1'

Any ideas on how to do this?

HRDSL
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  • No, because I need the output dataframe to look like I said. That solution only provides True and False values. – HRDSL Aug 13 '19 at 12:47

1 Answers1

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You can use pandas isin.

df1[df1.irrelevant_data_1.isin(df2.irrelevant_data_2)]
Poojan
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