plot.
bar
Vertical bar plot.
Allows plotting of one column versus another. If not specified, the index of the DataFrame is used.
Allows plotting of one column versus another. If not specified, all numerical columns are used.
Additional keyword arguments are documented in pyspark.pandas.Series.plot() or pyspark.pandas.DataFrame.plot().
pyspark.pandas.Series.plot()
pyspark.pandas.DataFrame.plot()
plotly.graph_objs.Figure
Return an custom object when backend!=plotly. Return an ndarray when subplots=True (matplotlib-only).
backend!=plotly
subplots=True
Examples
Basic plot.
For Series:
>>> s = ps.Series([1, 3, 2]) >>> s.plot.bar()
For DataFrame:
>>> df = ps.DataFrame({'lab': ['A', 'B', 'C'], 'val': [10, 30, 20]}) >>> df.plot.bar(x='lab', y='val')
Plot a whole dataframe to a bar plot. Each column is stacked with a distinct color 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 = ps.DataFrame({'speed': speed, ... 'lifespan': lifespan}, index=index) >>> df.plot.bar()
Instead of stacking, the figure can be split by column with plotly APIs.
>>> from plotly.subplots import make_subplots >>> 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 = ps.DataFrame({'speed': speed, ... 'lifespan': lifespan}, index=index) >>> fig = (make_subplots(rows=2, cols=1) ... .add_trace(df.plot.bar(y='speed').data[0], row=1, col=1) ... .add_trace(df.plot.bar(y='speed').data[0], row=1, col=1) ... .add_trace(df.plot.bar(y='lifespan').data[0], row=2, col=1)) >>> fig
Plot a single column.
>>> 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 = ps.DataFrame({'speed': speed, ... 'lifespan': lifespan}, index=index) >>> df.plot.bar(y='speed')
Plot only selected categories for the DataFrame.
>>> 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 = ps.DataFrame({'speed': speed, ... 'lifespan': lifespan}, index=index) >>> df.plot.bar(x='lifespan')