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