count dataframe rows where two particular columns have the same, particular value, output number of rows

Asked Jun 05 '21 at 14:49

Active Jun 05 '21 at 14:51

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how can i count the number of rows in which two columns of a given df have the same, particular value? I want to obtain only the number of such rows, so maybe there is a better solution than just double groupby?

I was thinking about something like that: rows = (data['col1'] == 0 and data['col2']==0).sum()

but while it works with only one condition, then when adding the second one I get an error saying The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()..

edited Jun 05 '21 at 14:51

asked Jun 05 '21 at 14:49

Zuzu

3

`(data['col1'].eq(0) & data['col2'].eq(0)).sum()` or `((data['col1'] == 0) & (data['col2'] == 0)).sum()` – Henry Ecker Jun 05 '21 at 14:50
1

Take a look at [difference between “&” and “and” in pandas?](https://stackoverflow.com/q/54315627/15497888) – Henry Ecker Jun 05 '21 at 14:53
Thanks! It works perfectly, exactly what I wanted. – Zuzu Jun 05 '21 at 14:54

count dataframe rows where two particular columns have the same, particular value, output number of rows

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