12 Python Data Visualization Libraries to Explore for Business Analysis

This piece has been updated by our Technical Content Writer, Chioma Dunkley.

Oct. '22 update: Python 3.9 and new libraries have been added to the standard notebook environment.

Scroll through the Python Package Index and you'll find libraries for practically every data visualization need—from GazeParser for eye movement research to pastalog for realtime visualizations of neural network training. And while many of these libraries are intensely focused on accomplishing a specific task, some can be used no matter what your field.

This list is an overview of 12 interdisciplinary Python data visualization libraries, from the well-known to the obscure. Mode Python Notebooks support five libraries on this list - matplotlib, Seaborn, Plotly, pygal, and Folium - and more than 60 others that you can explore on our Notebook support page.

We hope these lists inspire you, and if you want to add a library that's not listed, use our instructions to install additional libraries or send a note to success [at] modeanalytics [dot com].

• Matplotlib

• Seaborn

• Plotnine(ggplot)

• Bokeh

• pygal

• Plotly

• geoplotlib

• Gleam

• missingno

• Leather

• Altair

• Folium