pandas.api.indexers.BaseIndexer

class pandas.api.indexers.BaseIndexer(index_array=None, window_size=0, **kwargs)

Base class for window bounds calculations.

Parameters:

index_arraynp.ndarray, default None

Array-like structure representing the indices for the data points. If None, the default indices are assumed. This can be useful for handling non-uniform indices in data, such as in time series with irregular timestamps.

window_sizeint, default 0

Size of the moving window. This is the number of observations used for calculating the statistic. The default is to consider all observations within the window.

**kwargs

Additional keyword arguments passed to the subclass’s methods.

See also

DataFrame.rolling

Provides rolling window calculations on dataframe.

Series.rolling

Provides rolling window calculations on series.

Examples

>>> from pandas.api.indexers import BaseIndexer
>>> class CustomIndexer(BaseIndexer):
...     def get_window_bounds(self, num_values, min_periods, center, closed, step):
...         start = np.arange(num_values, dtype=np.int64)
...         end = np.arange(num_values, dtype=np.int64) + self.window_size
...         return start, end
>>> df = pd.DataFrame({"values": range(5)})
>>> indexer = CustomIndexer(window_size=2)
>>> df.rolling(indexer).sum()
    values
0   1.0
1   3.0
2   5.0
3   7.0
4   4.0

Methods

get_window_bounds([num_values, min_periods, ...])

Computes the bounds of a window.