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

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 · Answer 1 · 2021-11-09T09:02:57.007

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']")

edited Nov 09 '21 at 09:02

answered Nov 09 '21 at 08:54

Roxy

Are you sure that `query` is faster? It is indeed shorter to type, but I am not sure for execution speed... – Serge Ballesta Nov 09 '21 at 09:14

score 3 · Answer 2 · answered Nov 09 '21 at 09:12

3

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

answered Nov 09 '21 at 09:12

Gedas Miksenas

score 2 · Accepted Answer · answered Nov 09 '21 at 08:48

2

you can use

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

answered Nov 09 '21 at 08:48

Patrick

Apparently this is an invalid syntax. Python doesn't like the ".in". – Jeankrikri Nov 09 '21 at 08:50
ive made an edit it should be .isin() – Patrick Nov 09 '21 at 08:51

3 Answers3