pandas.core.groupby.SeriesGroupBy.__iter__ # 系列分组依据。__iter__ ( ) [来源] # Groupby 迭代器。 返回: 生成器生成(名称,子集对象)的序列 对于每组 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 >>> for x, y in ser.groupby(level=0): ... print(f'{x}\n{y}\n') a a 1 a 2 dtype: int64 b b 3 dtype: int64 对于 DataFrameGroupBy: >>> data = [[1, 2, 3], [1, 5, 6], [7, 8, 9]] >>> df = pd.DataFrame(data, columns=["a", "b", "c"]) >>> df a b c 0 1 2 3 1 1 5 6 2 7 8 9 >>> for x, y in df.groupby(by=["a"]): ... print(f'{x}\n{y}\n') (1,) a b c 0 1 2 3 1 1 5 6 (7,) a b c 2 7 8 9 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 >>> for x, y in ser.resample('MS'): ... print(f'{x}\n{y}\n') 2023-01-01 00:00:00 2023-01-01 1 2023-01-15 2 dtype: int64 2023-02-01 00:00:00 2023-02-01 3 2023-02-15 4 dtype: int64