work in progress
Plotly's Python graphing library makes interactive, publication-quality graphs. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.
Built on top of the Plotly JavaScript library (plotly.js), plotly.py enables Python users to create beautiful interactive web-based visualizations that can be displayed in Jupyter notebooks, saved to standalone HTML files, or served as part of pure Python-built web applications using Dash.
Thanks to deep integration with the orca image export utility, plotly.py also provides great support for non-web contexts including desktop editors (e.g. QtConsole, Spyder, PyCharm) and static document publishing (e.g. exporting notebooks to PDF with high-quality vector images).
plotly.py may be installed using pip...
$ pip install plotly==4.1.0
or conda.
$ conda install -c plotly plotly=4.1.0
This package contains everything you need to write figures to standalone HTML files.
Note: No internet connection, account, or payment is required to use plotly.py. Prior to version 4, this library could operate in
either an "online" or "offline" mode. The documentation tended to emphasize the online mode, where graphs get published to the Chart
Studio web service. In version 4, all "online" functionality was removed from the plotly package and is now available as the separate,
optional, chart-studio package (See below). plotly.py version 4 is "offline" only, and does not include any functionality for
uploading figures or data to cloud services.
This repository serves as a guide for beginners to learn plotly library and use various techniues and graphs for their own problems.