statsmodels.graphics.tsaplots.plot_accf_grid¶

statsmodels.graphics.tsaplots.plot_accf_grid(x, *, varnames=None, fig=None, lags=None, negative_lags=True, alpha=0.05, use_vlines=True, adjusted=False, fft=False, missing='none', zero=True, auto_ylims=False, bartlett_confint=False, vlines_kwargs=None, **kwargs)[source]¶

Plot auto/cross-correlation grid

Plots lags on the horizontal axis and the correlations on the vertical axis of each graph.

Parameters:¶

xarray_like: 2D array of time-series values: rows are observations, columns are variables.
varnames: sequence of str, optional: Variable names to use in plot titles. If x is a pandas dataframe and varnames is provided, it overrides the column names of the dataframe. If varnames is not provided and x is not a dataframe, variable names x[0], x[1], etc. are generated.
figMatplotlib figure instance, optional: If given, this figure is used to plot in, otherwise a new figure is created.
lags{int, array_like}, optional: An int or array of lag values, used on horizontal axes. Uses np.arange(lags) when lags is an int. If not provided, lags=np.arange(len(corr)) is used.
negative_lags: bool, optional: If True, negative lags are shown on the horizontal axes of plots below the main diagonal.
alphascalar, optional: If a number is given, the confidence intervals for the given level are plotted, e.g. if alpha=.05, 95 % confidence intervals are shown. If None, confidence intervals are not shown on the plot.
use_vlinesbool, optional: If True, shows vertical lines and markers for the correlation values. If False, only shows markers. The default marker is ‘o’; it can be overridden with a marker kwarg.
adjustedbool: If True, then denominators for correlations are n-k, otherwise n.
fftbool, optional: If True, computes the ACF via FFT.
missingstr, optional: A string in [‘none’, ‘raise’, ‘conservative’, ‘drop’] specifying how NaNs are to be treated.
zerobool, optional: Flag indicating whether to include the 0-lag autocorrelations (which are always equal to 1). Default is True.
auto_ylimsbool, optional: If True, adjusts automatically the vertical axis limits to correlation values.
bartlett_confintbool, default False: If True, use Bartlett’s formula to calculate confidence intervals in auto-correlation plots. See the description of plot_acf for details. This argument does not affect cross-correlation plots.
vlines_kwargsdict, optional: Optional dictionary of keyword arguments that are passed to vlines.
**kwargskwargs, optional: Optional keyword arguments that are directly passed on to the Matplotlib plot and axhline functions.

Returns:¶

Figure: If fig is None, the created figure. Otherwise, fig is returned. Plots on the grid show the cross-correlation of the row variable with the lags of the column variable.