pandas.plotting.lag_plot#

pandas.plotting.lag_plot(series,lag=1,ax=None,**kwds)[source]#

Lag plot for time series.

Parameters:

seriesSeries

The time series to visualize.

lagint, default 1

Lag length of the scatter plot.

axMatplotlib axis object, optional

The matplotlib axis object to use.

**kwds

Matplotlib scatter method keyword arguments.

Returns:

matplotlib.axes.Axes

Examples

Lag plots are most commonly used to look for patterns in time series data.

Given the following time series

>>>np.random.seed(5)>>>x=np.cumsum(np.random.normal(loc=1,scale=5,size=50))>>>s=pd.Series(x)>>>s.plot()

A lag plot withlag=1 returns

>>>pd.plotting.lag_plot(s,lag=1)<Axes: xlabel='y(t)', ylabel='y(t + 1)'>