snowflake.snowpark.modin.plugin.extensions.resample_overrides.Resampler.indices¶

property Resampler.indices: defaultdict[Hashable, list][source] (https://github.com/snowflakedb/snowpark-python/blob/v1.26.0/snowpark-python/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

Copy

>>> 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]})

Copy

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

Copy

>>> 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]})

Copy