How do I drop certain rows of my table in python? [duplicate]

Question

I have a table with data for multiple continents. Now I want to delete every row where the continent isn't Europe or Africa. With:

df1 = df1.loc[(df1["region"] == "Europe")]

I get every row with "Europe" but I miss the "Africa" ones. Is there a way to include an "or"-operator? It doesn't work for me.

Roxy · Accepted Answer · 2021-11-09 09:02:57Z

3

The question says drop, which needs to be adapted as follows if you want to drop the rows containing the mentioned value.

df1[(df1.region == "Europe") & (df1.region == "Africa")]

or you can also use the query command to achieve the same at the faster rate

df1.query("region == ['Europe', 'Africa']")

answered Nov 9, 2021 at 8:54

Roxy

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1 Comment

Are you sure that query is faster? It is indeed shorter to type, but I am not sure for execution speed...

Gedas Miksenas · Accepted Answer · 2021-11-09 09:12:25Z

3

Also option df1[df1["region"].isin(["Europe", "Africa"])]

answered Nov 9, 2021 at 9:12

Gedas Miksenas

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Patrick · Accepted Answer · 2021-11-09 08:48:21Z

2

you can use

df1 = df1.loc[(df1["region"].isin(["Europe", "Africa"]))]

answered Nov 9, 2021 at 8:48

Patrick

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Apparently this is an invalid syntax. Python doesn't like the ".in".

ive made an edit it should be .isin()