bigframes.pandas.Series.bar#

Series.bar(x: Hashable | None = None, y: Hashable | None = None, **kwargs)[source]#

Draw a vertical bar plot.

This function calls pandas.plot to generate a plot with a random sample of items. For consistent results, the random sampling is reproducible. Use the sampling_random_state parameter to modify the sampling seed.

Examples:

Basic plot.

>>> import bigframes.pandas as bpd
>>> df = bpd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
>>> ax = df.plot.bar(x='lab', y='val', rot=0)

Plot a whole dataframe to a bar plot. Each column is assigned a distinct color, and each row is nested in a group along the horizontal axis.

>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
...          'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = bpd.DataFrame({'speed': speed, 'lifespan': lifespan}, index=index)
>>> ax = df.plot.bar(rot=0)

Plot stacked bar charts for the DataFrame.

>>> ax = df.plot.bar(stacked=True)

If you don’t like the default colours, you can specify how you’d like each column to be colored.

>>> axes = df.plot.bar(
...     rot=0, subplots=True, color={"speed": "red", "lifespan": "green"}
... )
Parameters:

  • x (label or position, optional) – Allows plotting of one column versus another. If not specified, the index of the DataFrame is used.

  • y (label or position, optional) – Allows plotting of one column versus another. If not specified, all numerical columns are used.

  • **kwargs – Additional keyword arguments are documented in DataFrame.plot().

Returns:

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

Return type:

matplotlib.axes.Axes or numpy.ndarray

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