The library is built on top of plotly.js JavaScript library ( GitHub). Plotly Python is a free and open-source interactive graphing library for Python. There are some minor differences for the Plotly Python with JupyterLab, please see the JupyterLab example in GitHub repository. Note: This article is focusing on the Plotly Python with classic Jupyter Notebook only. The demo application uses Corona Virus Disease (COVID-19), Environmental, Social and Governance, and Financial data from Eikon Data API as an example of a dataset.
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This example project demonstrates how to use the Plotly Python library to plot various types of graphs. There are a lot of other alternative Plotting libraries such as Seaborn (which is a high-level interface of Matplotlib), Spotify's Chartify, Bokeh, Plotly Python, etc. However, the Matplotlib is a huge library that contains several interfaces, capabilities, and 1000+ pages of documents. The Matplotlib Pyplot is a de-facto library for making interactive plots and data visualization in the Python and Data Scientists world.
The good data analysis itself cannot be used with a good graph representation. With the rise of Data Scientists, Financial coders, or Traders (aka Citizen Developers), data visualization is a big part of how to present data, information, and its context to the readers (Financial team, Marketing team, etc.).
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