While matplotlib is good for getting a sense of the data, it's not very They allow you to access a number of matplotlib’s methods with less code. Some libraries like pandas and Seaborn are “wrappers” over matplotlib. It was designed to closely resemble MATLAB, a proprietary programming language developed in the 1980s.īecause matplotlib was the first Python data visualization library, many other libraries are built on top of it or designed to work in tandem with it during analysis. Despite being over a decade old, it's still the most widely used library for plotting in the Python community. 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 modeanalytics. 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. This list is an overview of 12 interdisciplinary Python data visualization libraries, from the well-known to the obscure. And while many of these libraries are intensely focused on accomplishing a specific task, some can be used no matter what your field. 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. '22 update: Python 3.9 and new libraries have been added to the standard notebook environment. This piece has been updated by our Technical Content Writer, Chioma Dunkley.
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