[Python] how to count the number of non-NA elements in each column of a Pandas Dataframe

Question

I want to find the number of non-NA cells for each column of a dataframe. What function should I use?

Answer 1

You can use the count() function of the dataframe. It returns the count of non-NA cells for each column or row depending on the parameter axis.

If the parameter 'axis' is set to 0, counts are generated for each column. If 1, counts are generated for each row.

Here is an example:

>>> import numpy as np

>>> import pandas as pd

>>> df = pd.DataFrame({'A':[12,13,np.nan], 'B':[43,np.nan,34],'C':[np.nan,np.nan,90]})

>>> df

      A     B     C

0  12.0  43.0   NaN

1  13.0   NaN   NaN

2   NaN  34.0  90.0

>>> df.count()

A    2

B    2

C    1

dtype: int64

>>> df.count(axis=0)

A    2

B    2

C    1

dtype: int64

>>> df.count(axis=1)

0    2

1    1

2    2

dtype: int64