pandas.Series.plot.area#

Series.plot.area(x=None, y=None, stacked=True, **kwargs)[source]#

Draw a stacked area plot.

An area plot displays quantitative data visually. This function wraps the matplotlib area function.

Parameters
xlabel or position, optional

Coordinates for the X axis. By default uses the index.

ylabel or position, optional

Column to plot. By default uses all columns.

stackedbool, default True

Area plots are stacked by default. Set to False to create a unstacked plot.

**kwargs

Additional keyword arguments are documented in DataFrame.plot().

Returns
matplotlib.axes.Axes or numpy.ndarray

Area plot, or array of area plots if subplots is True.

See also

DataFrame.plot

Make plots of DataFrame using matplotlib / pylab.

Examples

Draw an area plot based on basic business metrics:

>>> df = pd.DataFrame({
...     'sales': [3, 2, 3, 9, 10, 6],
...     'signups': [5, 5, 6, 12, 14, 13],
...     'visits': [20, 42, 28, 62, 81, 50],
... }, index=pd.date_range(start='2018/01/01', end='2018/07/01',
...                        freq='M'))
>>> ax = df.plot.area()
../../_images/pandas-Series-plot-area-1.png

Area plots are stacked by default. To produce an unstacked plot, pass stacked=False:

>>> ax = df.plot.area(stacked=False)
../../_images/pandas-Series-plot-area-2.png

Draw an area plot for a single column:

>>> ax = df.plot.area(y='sales')
../../_images/pandas-Series-plot-area-3.png

Draw with a different x:

>>> df = pd.DataFrame({
...     'sales': [3, 2, 3],
...     'visits': [20, 42, 28],
...     'day': [1, 2, 3],
... })
>>> ax = df.plot.area(x='day')
../../_images/pandas-Series-plot-area-4.png