databricks.koalas.DataFrame.plot.bar

plot.bar(x=None, y=None, **kwds)

Vertical bar plot.

Parameters

xlabel or position, optional

Allows plotting of one column versus another. If not specified, the index of the DataFrame is used.

ylabel or position, optional

Allows plotting of one column versus another. If not specified, all numerical columns are used.

**kwdsoptional

Additional keyword arguments are documented in Koalas.DataFrame.plot().

Returns

axesmatplotlib.axes.Axes or numpy.ndarray of them

Examples

Basic plot.

>>> df = ks.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 = ks.DataFrame({'speed': speed,
...                    'lifespan': lifespan}, index=index)
>>> ax = df.plot.bar(rot=0)

Instead of nesting, the figure can be split by column with subplots=True. In this case, a numpy.ndarray of matplotlib.axes.Axes are returned.

>>> axes = df.plot.bar(rot=0, subplots=True)
>>> axes[1].legend(loc=2)  

Plot a single column.

>>> ax = df.plot.bar(y='speed', rot=0)

Plot only selected categories for the DataFrame.

>>> ax = df.plot.bar(x='lifespan', rot=0)

databricks.koalas.DataFrame.plot.barh databricks.koalas.DataFrame.plot.hist