pmdarima.utils.plot_acf

pmdarima.utils.plot_acf(series, ax=None, lags=None, alpha=None, use_vlines=True, unbiased=False, fft=True, title='Autocorrelation', zero=True, vlines_kwargs=None, show=True, **kwargs)

Plot a series’ auto-correlation as a line plot.

A wrapper method for the statsmodels plot_acf method.

Parameters:

series : array-like, shape=(n_samples,)

The series or numpy array for which to plot an auto-correlation.

ax : Matplotlib AxesSubplot instance, optional

If given, this subplot is used to plot in instead of a new figure being created.

lags : int, array-like or None, optional (default=None)

int or Array of lag values, used on horizontal axis. Uses np.arange(lags) when lags is an int. If not provided, lags=np.arange(len(corr)) is used.

alpha : scalar, optional (default=None)

If a number is given, the confidence intervals for the given level are returned. For instance if alpha=.05, 95 % confidence intervals are returned where the standard deviation is computed according to Bartlett’s formula. If None, no confidence intervals are plotted.

use_vlines : bool, optional (default=True)

If True, vertical lines and markers are plotted. If False, only markers are plotted. The default marker is ‘o’; it can be overridden with a marker kwarg.

unbiased : bool, optional (default=False)

If True, then denominators for autocovariance are n-k, otherwise n

fft : bool, optional (default=True)

If True, computes the ACF via FFT.

title : str, optional (default=’Autocorrelation’)

Title to place on plot. Default is ‘Autocorrelation’

zero : bool, optional (default=True)

Flag indicating whether to include the 0-lag autocorrelation. Default is True.

vlines_kwargs : dict, optional (default=None)

Optional dictionary of keyword arguments that are passed to vlines.

show : bool, optional (default=True)

Whether to show the plot after it’s been created. If not, will return the plot as an Axis object instead.

**kwargs : kwargs, optional

Optional keyword arguments that are directly passed on to the Matplotlib plot and axhline functions.

Returns:

plt : Axis or None

If show is True, does not return anything. If False, returns the Axis object.

Notes

This method will only show the plot if show=True (which is the default behavior). To simply get the axis back (say, to add to another canvas), use show=False.

Examples

>>> plot_acf([1, 2, 3], show=False)  
<matplotlib.figure.Figure object at 0x122fab4e0>