Pandas count true boolean values per row

Question

I have a dataframe df which looks like the following:

num1	num2	bool1	bool2	bool3
20	30	True	False	True
10	5	False	True	True

For each row I want to count the number of True values for a specific subset of the boolean columns, say bool2 and bool3. So the desired output would look like this:

num1	num2	bool1	bool2	bool3	count
20	30	True	False	True	1
10	5	False	True	True	2

In SQL I used to do this with something like CARDINALITY(bool2, bool3). Trying to figure out if there is a simple way to do something like that in Pandas.

See also: stackoverflow.com/questions/33823091/… stackoverflow.com/questions/49557895/… — i vk
– i vk, Commented Dec 9, 2021 at 19:17

Corralien · Accepted Answer · 2021-12-09 19:09:39Z

4

Apply sum over columns axis:

df['count'] = df[['bool2', 'bool3']].sum(axis=1)

Output:

>>> df
   num1  num2  bool1  bool2  bool3  count
0    20    30   True  False   True      1
1    10     5  False   True   True      2

edited Dec 9, 2021 at 19:09

Corralien

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answered Dec 9, 2021 at 18:58

user17242583

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