plot_correlations(series, lags=24, alpha=0.05, zero_lag=True, acf_fft=False, acf_adjusted=True, pacf_method='ywadjusted', suptitle=None, series_title=None, acf_title='Autocorrelation', pacf_title='Partial Autocorrelation')[source]#

Plot series and its ACF and PACF values.


A time series.

lagsint, default = 24

Number of lags to include in ACF and PACF plots

alphaint, default = 0.05

Alpha value used to set confidence intervals. Alpha = 0.05 results in 95% confidence interval with standard deviation calculated via Bartlett’s formula.

zero_lagbool, default = True

If True, start ACF and PACF plots at 0th lag

acf_fftbool, = False

Whether to compute ACF via FFT.

acf_adjustedbool, default = True

If True, denonimator of ACF calculations uses n-k instead of n, where n is number of observations and k is the lag.

pacf_methodstr, default = ‘ywadjusted’

Method to use in calculation of PACF.

suptitlestr, default = None

The text to use as the Figure’s suptitle.

series_titlestr, default = None

Used to set the title of the series plot if provided. Otherwise, series plot has no title.

acf_titlestr, default = ‘Autocorrelation’

Used to set title of ACF plot.

pacf_titlestr, default = ‘Partial Autocorrelation’

Used to set title of PACF plot.


Array of the figure’s Axe objects


>>> from sktime.utils.plotting import plot_correlations
>>> from sktime.datasets import load_airline
>>> y = load_airline()
>>> fig, ax = plot_correlations(y)