Filter if one element of a column fits the conditioning pandas DataFrame

Asked Oct 08 '19 at 13:15

Active Oct 08 '19 at 13:15

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I have a data table that contains several keywords in one column and I would like to filter if one of the keywords registers with my query.

Assume this example DataFrame:

    import pandas as pd 
    testdata = pd.DataFrame({"key":["This is", "just a", "meaningless and boring test example"], "value" : [2,3,4]})

This should result in a DataFrame like this:

key                                 | value
--------------------------------------------
This is                             | 2
just a                              | 3
meaningless and boring text example | 4

I'd now like to filter for occurrence if some keywords are part of my keywords. i. e. show all rows that contain "This" and "meaningless". In code I would expect something to work like:

    testdata.query('key in ["This", "meaningless"]')

asked Oct 08 '19 at 13:15

MichaelA

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Use `df[df['key'].str.contains("This|meaningless")]` – jezrael Oct 08 '19 at 13:16
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Or `L = ["This", "meaningless"]` and then `df[df['key'].str.contains('|'.join(L))]` – jezrael Oct 08 '19 at 13:17
thx, if someone wants to use the (in my opinion) more readable query function: testdata.query('key.str.contains("This|meaningless")') – MichaelA Oct 08 '19 at 13:54
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check in [this](https://stackoverflow.com/a/55335207) answer. – jezrael Oct 08 '19 at 13:55

Filter if one element of a column fits the conditioning pandas DataFrame

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