pandas.plotting.lag_plot — pandas 2.3.0 documentation (original) (raw)

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=1 returns

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