modin.pandas.DataFrameGroupBy.count¶

DataFrameGroupBy.count()[source]¶

Compute count of group, excluding missing values.

Returns:

Count of values within each group.

Return type:

Series or DataFrame

Examples

For SeriesGroupBy:

>>> lst = ['a', 'a', 'b']
>>> ser = pd.Series([1, 2, np.nan], index=lst)
>>> ser
a    1.0
a    2.0
b    NaN
dtype: float64
>>> ser.groupby(level=0).count()
a    2
b    0
dtype: int64
Copy

For DataFrameGroupBy:

>>> data = [[1, np.nan, 3], [1, np.nan, 6], [7, 8, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"],
...                   index=["cow", "horse", "bull"])
>>> df
       a    b  c
cow    1  NaN  3
horse  1  NaN  6
bull   7  8.0  9
>>> df.groupby("a").count()     
   b  c
a
1  0  2
7  1  1
Copy