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.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'>
../../_images/pandas-plotting-lag_plot-1.png

A lag plot with lag=1 returns

>>> pd.plotting.lag_plot(s, lag=1)
<AxesSubplot: xlabel='y(t)', ylabel='y(t + 1)'>
../../_images/pandas-plotting-lag_plot-2.png