Rolling

Compute rolling mean, std, min, max, and quantile

rolling_mean

rolling_mean(x, window_size, min_samples=None, skipna=False)

Compute the rolling_mean of the input array.

Parameters:

Name	Type	Description	Default
x	np.ndarray	Input array.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	required
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	required

Returns:

Type	Description
np.ndarray: Array with the rolling statistic

rolling_std

rolling_std(x, window_size, min_samples=None, skipna=False)

Compute the rolling_std of the input array.

Parameters:

Name	Type	Description	Default
x	np.ndarray	Input array.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	required
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	required

Returns:

Type	Description
np.ndarray: Array with the rolling statistic

rolling_min

rolling_min(x, window_size, min_samples=None, skipna=False)

Compute the rolling_min of the input array.

Parameters:

Name	Type	Description	Default
x	np.ndarray	Input array.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	required
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	required

Returns:

Type	Description
np.ndarray: Array with the rolling statistic

rolling_max

rolling_max(x, window_size, min_samples=None, skipna=False)

Compute the rolling_max of the input array.

Parameters:

Name	Type	Description	Default
x	np.ndarray	Input array.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	required
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	required

Returns:

Type	Description
np.ndarray: Array with the rolling statistic

rolling_quantile

rolling_quantile(x, p, window_size, min_samples=None, skipna=False)

Compute the rolling_quantile of the input array.

Parameters:

Name	Type	Description	Default
x	ndarray	Input array.	required
p	float	Quantile to compute.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	None
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	False

Returns:

Type	Description
ndarray	np.ndarray: Array with rolling statistic

seasonal_rolling_mean

seasonal_rolling_mean(x, season_length, window_size, min_samples=None, skipna=False)

Compute the seasonal_rolling_mean of the input array

Parameters:

Name	Type	Description	Default
x	np.ndarray	Input array.	required
season_length	int	The length of the seasonal period.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	required
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	required

Returns:

Type	Description
np.ndarray: Array with the seasonal rolling statistic

seasonal_rolling_std

seasonal_rolling_std(x, season_length, window_size, min_samples=None, skipna=False)

Compute the seasonal_rolling_std of the input array

Parameters:

Name	Type	Description	Default
x	np.ndarray	Input array.	required
season_length	int	The length of the seasonal period.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	required
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	required

Returns:

Type	Description
np.ndarray: Array with the seasonal rolling statistic

seasonal_rolling_min

seasonal_rolling_min(x, season_length, window_size, min_samples=None, skipna=False)

Compute the seasonal_rolling_min of the input array

Parameters:

Name	Type	Description	Default
x	np.ndarray	Input array.	required
season_length	int	The length of the seasonal period.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	required
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	required

Returns:

Type	Description
np.ndarray: Array with the seasonal rolling statistic

seasonal_rolling_max

seasonal_rolling_max(x, season_length, window_size, min_samples=None, skipna=False)

Compute the seasonal_rolling_max of the input array

Parameters:

Name	Type	Description	Default
x	np.ndarray	Input array.	required
season_length	int	The length of the seasonal period.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	required
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	required

Returns:

Type	Description
np.ndarray: Array with the seasonal rolling statistic

seasonal_rolling_quantile

seasonal_rolling_quantile(x, p, season_length, window_size, min_samples=None, skipna=False)

Compute the seasonal_rolling_quantile of the input array.

Parameters:

Name	Type	Description	Default
x	ndarray	Input array.	required
p	float	Quantile to compute.	required
season_length	int	The length of the seasonal period.	required
window_size	int	The size of the rolling window.	required
min_samples	int	The minimum number of samples required to compute the statistic. If None, it is set to window_size.	None
skipna	bool	Exclude NaN values from calculations. When False (default), any NaN value in the window causes the result to be NaN. When True, NaN values are ignored and statistics are computed on remaining valid values in the window. Defaults to False for backwards compatibility.	False

Returns:

Type	Description
ndarray	np.ndarray: Array with rolling statistic