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