Bokeh plotting backend for Pandas.DataFrames
Project description
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.
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