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pandas.DataFrame.plot — pandas 3.0.0.dev0+2231.g4f2aa4d2be documentation

DataFrame.plot(*args, **kwargs)[source]#

Make plots of Series or DataFrame.

Uses the backend specified by the option plotting.backend. By default, matplotlib is used.

Parameters:

dataSeries or DataFrame

The object for which the method is called.

Attributes

Returns:

matplotlib.axes.Axes or numpy.ndarray of them

If the backend is not the default matplotlib one, the return value will be the object returned by the backend.

Notes

• See matplotlib documentation online for more on this subject

• If kind = ‘bar’ or ‘barh’, you can specify relative alignments for bar plot layout by position keyword. From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)

Examples

For Series:

>>> ser = pd.Series([1, 2, 3, 3])
>>> plot = ser.plot(kind="hist", title="My plot")

For DataFrame:

>>> df = pd.DataFrame(
...     {
...         "length": [1.5, 0.5, 1.2, 0.9, 3],
...         "width": [0.7, 0.2, 0.15, 0.2, 1.1],
...     },
...     index=["pig", "rabbit", "duck", "chicken", "horse"],
... )
>>> plot = df.plot(title="DataFrame Plot")

For SeriesGroupBy:

>>> lst = [-1, -2, -3, 1, 2, 3]
>>> ser = pd.Series([1, 2, 2, 4, 6, 6], index=lst)
>>> plot = ser.groupby(lambda x: x > 0).plot(title="SeriesGroupBy Plot")

For DataFrameGroupBy:

>>> df = pd.DataFrame({"col1": [1, 2, 3, 4], "col2": ["A", "B", "A", "B"]})
>>> plot = df.groupby("col2").plot(kind="bar", title="DataFrameGroupBy Plot")

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