PlottingΒΆ
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>

>>> iris.plot()
<matplotlib.axes._subplots.AxesSubplot at 0x10db7e690>

>>> iris.groupby('name').sum().plot(kind='bar', x='name', stacked=True, rot=30)
<matplotlib.axes._subplots.AxesSubplot at 0x10c5f2090>

>>> 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)

The kind
parameter 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 |