This repository contains sample code for creating awesome data visualizations from scratch using different python libraries (such as matplotlib, plotly, seaborn) with the help of example notebooks. Please see the individual folder for python jupyter notebooks and datasets.

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Python libraries for data visualization

• altair - Declarative statistical visualizations, based on Vega-Lite.
• PyGWalker - Turn your pandas dataframe into a Tableau-style User Interface for visual analysis.
• bokeh - Interactive Web Plotting for Python.
• bqplot - plotting library for IPython/Jupyter notebooks - front-end in d3
• Chartify - Bokeh wrapper that makes it easy for data scientists to create charts.
• dash - Dash is a Python framework for building analytical web applications
• diagram - Text mode diagrams using UTF-8 characters
• ggplot - plotting system based on R's ggplot2.
• glumpy - OpenGL scientific visualizations library.
• holoviews - Complex and declarative visualizations from annotated data.
• mayai - interactive scientific data visualization and 3D plotting in Python.
• matplotlib - 2D plotting library.
• missingno - provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib.
• plotly - Interactive web based visualization built on top of plotly.js
• PyQtGraph - Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.
• PyVista – 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)
• seaborn - A library for making attractive and informative statistical graphics.
• toyplot - The kid-sized plotting toolkit for Python with grownup-sized goals.
• three.py - Easy to use 3D library based on PyOpenGL. Inspired by Three.js.
• veusz - Python multiplatform GUI plotting tool and graphing library
• VisPy - High-performance scientific visualization based on OpenGL.
• vtk - 3D computer graphics, image processing, and visualization that includes a Python interface.
• PyGMT - PyGMT is a library for processing geospatial and geophysical data and making publication quality maps and figures. It provides a Pythonic interface for the Generic Mapping Tools (GMT), a command-line program widely used in the Earth Sciences.