Plotting

PyODPS DataFrame provides plotting. To enable plotting, install the pandas and matplotlib libraries.

The following examples run in Jupyter:

>>> from odps.df import DataFrame
>>> iris = DataFrame(o.get_table('pyodps_iris'))
>>> %matplotlib inline
>>> iris.sepalwidth.plot()
<matplotlib.axes._subplots.AxesSubplot at 0x10c2b3510>
_images/df-plot-iris-sequence.png
>>> iris.plot()
<matplotlib.axes._subplots.AxesSubplot at 0x10db7e690>
_images/df-plot-iris-collection.png
>>> iris.groupby('name').sum().plot(kind='bar', x='name', stacked=True, rot=30)
<matplotlib.axes._subplots.AxesSubplot at 0x10c5f2090>
_images/df-plot-iris-sum.png
>>> iris.hist(sharex=True)
array([[<matplotlib.axes._subplots.AxesSubplot object at 0x10e013f90>,
        <matplotlib.axes._subplots.AxesSubplot object at 0x10e2d1c10>],
       [<matplotlib.axes._subplots.AxesSubplot object at 0x10e353f10>,
        <matplotlib.axes._subplots.AxesSubplot object at 0x10e3c4410>]], dtype=object)
_images/df-plot-iris-hist.png

The kindparameter specifies the plotting type, and supports the following types:

kind

Description

line

Line chart

bar

Vertical bar chart

barh

Horizontal bar chart

hist

Histogram

box

Boxplot

kde

Kernel density estimation

density

Same as kernel density estimation

area

pie

Pie chart

scatter

Scatter chart

hexbin

For more information, see pandas.DataFrame.plot: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.plot.html

The plot function also provides the following parameters for plotting:

Parameter

Description

xlabel

X axis name

ylabel

Y axis name

xlabelsize

Size of x axis name

ylabelsize

Size of y axis name

labelsize

Axis name size

title

Title

titlesize

Title size

annotate

Annotation