bigframes.pandas.api.typing.PlotAccessor#

class bigframes.pandas.api.typing.PlotAccessor(data)[source]#

Make plots of Series or DataFrame with the matplotlib backend.

Examples: For Series:

>>> import bigframes.pandas as bpd
>>> ser = bpd.Series([1, 2, 3, 3])
>>> plot = ser.plot(kind='hist', title="My plot")

For DataFrame:

>>> df = bpd.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")
Parameters:

  • data (Series or DataFrame) – The object for which the method is called.

  • kind (str) –

    The kind of plot to produce:

    • ’line’ : line plot (default)

    • ’hist’ : histogram

    • ’area’ : area plot

    • ’scatter’ : scatter plot (DataFrame only)

  • **kwargs – Options to pass to pandas.DataFrame.plot method. See pandas documentation online for more on these arguments.

Returns:

An ndarray is returned with one matplotlib.axes.Axes per column when subplots=True.

Return type:

matplotlib.axes.Axes or np.ndarray of them

Methods

__init__(data)

area([x, y, stacked])

Draw a stacked area plot.

bar([x, y])

Draw a vertical bar plot.

barh([x, y])

Draw a horizontal bar plot.

hist([by, bins])

Draw one histogram of the DataFrame’s columns.

line([x, y])

Plot Series or DataFrame as lines.

pie([y])

Generate a pie plot.

scatter([x, y, s, c])

Create a scatter plot with varying marker point size and color.