Bokeh is an useful CLI tool for data visualization exactly like d3.js is useful tool. With Bokeh You Can Create Interactive Tables and Charts. Here is How to Install Bokeh Python Visualization Library in Jupyter Notebooks. In case, you do not have Jupyter Notebook installed, follow how to install Jupyter Notebook on Mac, GNU/Linux. If you are Windows 10 user, the same guide can be used if you use Python, pip from Bash.
Steps to Install Bokeh Python Visualization Library in Jupyter Notebooks
Installing via Anacona/Miniconda
If you have Anaconda or miniconda installed, then it is just easy :
|
1 2 3 4 5 6 7 8 9 10 11 |
# cd to directory where your environment.yml file conda env create source activate bokeh-notebooks conda install phantomjs pillow selenium # sample data download to build demo visualizations bokeh sampledata ## optional install Datashader, Holoviews conda install -c datashader holoviews flask # run the Jupyter notebook ## run jupyter notebook, open 00 - Introduction, Setup.ipynb notebook jupyter notebook |
Installing in Python Way
Basically, these are commonly needed dependencies or rather practical to have installed, not all can be installed via pip :
Jinja2
python-dateutil
PyYAML
numpy
packaging
six
tornado
NodeJS
Pandas
psutil
Sphinx
---
You can install like with pip like any other python stuff :
|
1 |
pip install bokeh |
You can check sample data by running the below common on bash :
|
1 |
bokeh sampledata |
By default, sample data is downloaded, stored inside ~/.bokeh/data/. Bokeh uses a YAML configuration file located at ~/.bokeh/config/. You can run cat on that file to check the contents.
If we use this python script from bash :
|
1 2 3 4 5 |
from bokeh.plotting import figure, output_file, show output_file("example.html") p = figure() p.line([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], line_width=2) show(p) |
That example.html will locally open. Bokeh also has Javascript, CSS like D3.js for web usage.
This is an example of using Bokeh (with code) to create an interactive Periodic Table :
|
1 |
http://bokeh.pydata.org/en/latest/docs/gallery/periodic.html |
Bokeh has good number of guides, examples on their official website.
About Abhishek Ghosh
Follow the Author of this article :
Here’s what we’ve got for you which might like :
Additionally, performing a search on this website can help you. Also, we have YouTube Videos.
Take The Conversation Further ...
We'd love to know your thoughts on this article.
Meet the Author over on Google+ or Twitter to join the conversation right now!
If you want to Advertise on our Article or want Business Partnership, you are invited to Contact us.
Contact Us