pandas.DataFrame.plot.area#

DataFrame.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年01月01日', end='2018年07月01日',
...  freq='ME'))
>>> ax = df.plot.area()

../../_images/pandas-DataFrame-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-DataFrame-plot-area-2.png

Draw an area plot for a single column:

>>> ax = df.plot.area(y='sales')

../../_images/pandas-DataFrame-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-DataFrame-plot-area-4.png