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