pandas.core.groupby.SeriesGroupBy.indices # 属性 SeriesGroupBy。索引[来源] # 字典 {组名称 -> 组索引}。 例子 对于系列分组依据: >>> lst = ['a', 'a', 'b'] >>> ser = pd.Series([1, 2, 3], index=lst) >>> ser a 1 a 2 b 3 dtype: int64 >>> ser.groupby(level=0).indices {'a': array([0, 1]), 'b': array([2])} 对于 DataFrameGroupBy: >>> data = [[1, 2, 3], [1, 5, 6], [7, 8, 9]] >>> df = pd.DataFrame(data, columns=["a", "b", "c"], ... index=["owl", "toucan", "eagle"]) >>> df a b c owl 1 2 3 toucan 1 5 6 eagle 7 8 9 >>> df.groupby(by=["a"]).indices {1: array([0, 1]), 7: array([2])} 对于重采样器: >>> ser = pd.Series([1, 2, 3, 4], index=pd.DatetimeIndex( ... ['2023-01-01', '2023-01-15', '2023-02-01', '2023-02-15'])) >>> ser 2023-01-01 1 2023-01-15 2 2023-02-01 3 2023-02-15 4 dtype: int64 >>> ser.resample('MS').indices defaultdict(<class 'list'>, {Timestamp('2023-01-01 00:00:00'): [0, 1], Timestamp('2023-02-01 00:00:00'): [2, 3]})