pandas.plotting.lag_plot¶
- pandas.plotting.lag_plot(series, lag=1, ax=None, **kwds)[source]¶
 Lag plot for time series.
- Parameters
 - seriesTime series
 - laglag of the scatter plot, default 1
 - axMatplotlib axis object, optional
 - **kwds
 Matplotlib scatter method keyword arguments.
- Returns
 - class:matplotlib.axis.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() <AxesSubplot:xlabel='Midrange'>
A lag plot with
lag=1returns>>> pd.plotting.lag_plot(s, lag=1) <AxesSubplot:xlabel='y(t)', ylabel='y(t + 1)'>