snowflake.snowpark.modin.plugin.extensions.resample_overrides.Resampler.indices¶
- property Resampler.indices: defaultdict[Hashable, list][source] (https://github.com/snowflakedb/snowpark-python/blob/v1.42.0/src/snowflake/snowpark/modin/plugin/extensions/resample_overrides.py#L183-L192)¶
- Dict {group name -> group indices}. - Return type:
- collections.defaultdict[Hashable, list] 
 - Notes - Beware that the return value is a python dictionary, so evaluating this property will trigger evaluation of the pandas dataframe and will materialize data that could be as large as the size of the grouping columns. - Examples - For Series: - >>> lst1 = pd.date_range('2020-01-01', periods=4, freq='1D') >>> ser1 = pd.Series([1, 2, 3, 4], index=lst1) >>> ser1 2020-01-01 1 2020-01-02 2 2020-01-03 3 2020-01-04 4 Freq: None, dtype: int64 - >>> ser1.resample('2D').indices defaultdict(<class 'list'>, {Timestamp('2020-01-01 00:00:00'): [0, 1], Timestamp('2020-01-03 00:00:00'): [2, 3]}) - For DataFrame: - >>> data = [[1, 8, 2], [1, 2, 5], [2, 5, 8], [2, 6, 9]] >>> df = pd.DataFrame(data, ... columns=["a", "b", "c"], ... index=pd.date_range('2020-01-01', periods=4, freq='1D')) >>> df a b c 2020-01-01 1 8 2 2020-01-02 1 2 5 2020-01-03 2 5 8 2020-01-04 2 6 9 - >>> df.resample('2D').indices defaultdict(<class 'list'>, {Timestamp('2020-01-01 00:00:00'): [0, 1], Timestamp('2020-01-03 00:00:00'): [2, 3]})