pandas.api.indexers.FixedForwardWindowIndexer#

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

Creates window boundaries for fixed-length windows that include the current row.

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.
api.indexers.VariableWindowIndexer: Calculate window bounds based on variable-sized windows.

Examples

>>> df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
>>> df
     B
0  0.0
1  1.0
2  2.0
3  NaN
4  4.0

>>> indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=2)
>>> df.rolling(window=indexer, min_periods=1).sum()
     B
0  1.0
1  3.0
2  2.0
3  4.0
4  4.0

Methods

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

Computes the bounds of a window.