pyspark.pandas.groupby.GroupBy.count# GroupBy.count()[source]# Compute count of group, excluding missing values. See also pyspark.pandas.Series.groupby pyspark.pandas.DataFrame.groupby Examples >>> df = ps.DataFrame({'A': [1, 1, 2, 1, 2], ... 'B': [np.nan, 2, 3, 4, 5], ... 'C': [1, 2, 1, 1, 2]}, columns=['A', 'B', 'C']) >>> df.groupby('A').count().sort_index() B C A 1 2 3 2 2 2