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pastas.plotting.plots.acf#

acf(series, alpha=0.05, lags=365, acf_options=None, smooth_conf=True, color='k', ax=None, figsize=(5, 2))[source]#

Plot of the autocorrelation function of a time series.

Parameters
  • series (pandas.Series) – Residual series to plot the autocorrelation function for.

  • alpha (float, optional) – Significance level to calculate the (1-alpha)-confidence intervals. For 95% confidence intervals, alpha should be 0.05.

  • lags (int, optional) – Maximum number of lags (in days) to compute the autocorrelation for.

  • acf_options (dict, optional) – Dictionary with keyword arguments passed on to pastas.stats.acf.

  • smooth_conf (bool, optional) – For irregular time series the confidence interval may be.

  • color (str, optional) – Color of the vertical autocorrelation lines.

  • ax (matplotlib.axes.Axes, optional) – Matplotlib Axes instance to plot the ACF on. A new Figure and Axes is created when no value for ax is provided.

  • figsize (Tuple, optional) – 2-D Tuple to determine the size of the figure created. Ignored if ax is also provided.

Returns

ax

Return type

matplotlib.axes.Axes

Examples

>>> res = pd.Series(index=pd.date_range(start=0, periods=1000, freq="D"),
>>>                 data=np.random.rand(1000))
>>> ps.plots.acf(res)