pandas.api.indexers.BaseIndexer — pandas 3.0.0rc0+33.g1fd184de2a documentation (original) (raw)

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

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