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.

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

pandas.DataFrame.plot.area#

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