pandas.api.indexers.FixedForwardWindowIndexer#

classpandas.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.

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