Pandas count true boolean values per row-CodePudding

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.

CodePudding user response：

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