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Data Visualization

Data VisualizationCreated By:Joshua Rafael 1 Basic Visuals | Matplotlib, SeabornBasic Visualization Concepts, Introduction and Comparison b/t Matplotlib and Seaborn Python Libraries in Jupyter 2 Interactive Visuals | Plotly, Bokeh, Tableau, insights into more interactive and fun data Visualization functions. Introduction to Plotly, Bokeh and made by Freepik from Notebooks Slideshow Homework ReferencesTable of Contents(Note: Click on hyperlinks to go to different parts of the slides.) About Matplotlib Installing Matplotlib Object Hierarchy Functional/MATLAB Approach (w/ ex) Object-Oriented Approach (w/ ex)0. About/Intro1. Matplotlib About Seaborn Installing Seaborn Theme Adjustments (w/ ex)2. Seaborn About Plotly Installing Plotly Using Plotly Offline or Online Plotly Examples Plotly Alternatives: Bokeh (w/ ex) Plotly Links to Notebooks References Cited5. References4. Tableau About Tableau Tableau Desktop No-Code Visualization Tools Visualization ComparisonData VisualizationWhat is data Visualization ?

create visualizations. Usage: Use D3.js build-in data-driven transitions for extra customization and elevated visualization for your data. Pro: Helps build type of framework you want (Plotly uses D3.js library, here you can use the D3.js library itself; open-source) Con: High learning curve; you need to learn HTML, CSS, Javascript

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