pandas.core.groupby.DataFrameGroupBy.ngroup#

DataFrameGroupBy.ngroup(ascending=True)[source]#

Number each group from 0 to the number of groups - 1.

This is the enumerative complement of cumcount. Note that the numbers given to the groups match the order in which the groups would be seen when iterating over the groupby object, not the order they are first observed.

Groups with missing keys (where pd.isna() is True) will be labeled with NaN and will be skipped from the count.

Parameters
ascendingbool, default True

If False, number in reverse, from number of group - 1 to 0.

Returns
Series

Unique numbers for each group.

See also

cumcount

Number the rows in each group.

Examples

>>> df = pd.DataFrame({"color": ["red", None, "red", "blue", "blue", "red"]})
>>> df
   color
0    red
1   None
2    red
3   blue
4   blue
5    red
>>> df.groupby("color").ngroup()
0    1.0
1    NaN
2    1.0
3    0.0
4    0.0
5    1.0
dtype: float64
>>> df.groupby("color", dropna=False).ngroup()
0    1
1    2
2    1
3    0
4    0
5    1
dtype: int64
>>> df.groupby("color", dropna=False).ngroup(ascending=False)
0    1
1    0
2    1
3    2
4    2
5    1
dtype: int64