Pandas Bokeh

Pandas Bokeh provides a Bokeh plotting backend for Pandas and GeoPandas, similar to the already existing Visualization feature of Pandas. Importing the library adds a complementary plotting method plot_bokeh() on DataFrames and Series (and also on GeoDataFrames).

For more information and examples have a look at the Github Repository.

Installation

You can install Pandas Bokeh from PyPI via pip:

pip install pandas-bokeh

Pandas Bokeh is supported on Python 2.7, as well as Python 3.6 and above.

Description

With Pandas Bokeh, creating stunning, interactive, HTML-based visualization is as easy as calling:

df.plot_bokeh()

In this early version, the following plot types are supported:

• line
• point
• scatter
• bar
• histogram

In the near future many more will be implemented as horizontal barplot, boxplots,pie-charts, etc.

Pandas Bokeh is a high-level API for Bokeh. Nevertheless there are many options for customizing the plots, for example:

• figsize: Choose width & height of the plot
• title: Sets title of the plot
• xlim/ylim: Set visibler range of plot for x- and y-axis (also works for datetime x-axis)
• xlabel/ylabel: Set x- and y-labels
• logx/logy: Set log-scale on x-/y-axis
• xticks/yticks: Explicitly set the ticks on the axes
• colormap: Defines the colors to plot. Can be either a list of colors or the name of a Bokeh color palette
• hovertool: If True a Hovertool is active, else if False no Hovertool is drawn.

Plots like scatterplot or histogram also have many more additional customization options.