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In this tutorial we'll learn how to use Bokeh to build interactive visualizations viewable in a browser. Generally this tutorial will have the following format
charting
- High level interface to go from data to plotplotting
- Intermediate interface allowing control to all parts of a plotThis tutorial uses many different libraries that are all available with the Anaconda Distribution. Once you have Anaconda install, please run these commands from a terminal:
$ conda install -y blaze
$ conda install -y bokeh
$ conda install -y odo
Provide a first-class visualization library for web-aware applications, without requiring web-level programming.
Write a visualization python. Bokeh creates data descripors and a scenegraph consumed by BokehJS. This works in ipython notebook, creating static files and interacting with dynamic data sources.
Bokeh includes pre-built schemas in bokeh.charts, a low-level composition interface (similar to matplotlib), a server for large and/or dynamic datasources and widgets for providing client-side realtime interaction.
The non-JS framework also has prototypes in other languages (Scala, Julia...maybe R).
Note: There are examples notebooks in bokeh/examples/plotting/notebooks. Start an ipython notebook server there to get more examples.
Gallery -- tutorial -- Documentation -- Repo
In [1]:
import pandas as pd
import numpy as np
In [2]:
from bokeh.plotting import output_notebook
output_notebook() # Tell Bokeh to output in an ipython notebook (other options later)