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)'> 