Data Visualization: Plotly

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Data Visualization: PlotlyCreated By:Joshua Rafael Sanchezjoshuarafael@berkeley.edu

Plotlyplotly.com/python

Plotly - AboutAbout Plotly: From website: Plotly is an interactive, open-source plotting library that supports over 40unique chart types.Usage: Plotly is advantageous for those who want an interactive environment which manyuse cases, ranging from statistics to finance to geography and more.Pros and Cons of Plotly: Pro: Make beautiful, interactive, exportable figures in just a few lines of code.Pro: Much more interactive & visually flexible than Matplotlib or Seaborn.Con: Confusing initial setup to use Plotly without an online account, and lots ofcode to write.Con: Out-of-date documentation and the large range of Plotly tools (ChartStudio, Express, etc.) make it hard to keep up.PlotlyResources

Plotly - InstallingInstalling Plotly Offline: (if you want to host locally on your own computer) Steps: You need to import packages and use commands: Resource: Keep checking current version: Initialization for Online Plotting Command to create standalone HTML: plotly.offline.plot() Command to create plot in Jupyter Notebook: plotly.offline.iplot()Installing Plotly Online: (use if you want to host graphs in plotly account) How to: You must create an account to run:1.Set up an account at plot.ly2.Get a User ID and API keys3.Sign keys into the account.PlotlyResources

Plotly - Alternatives (Bokeh, D3.js)Bokeh: Bokeh is an interactive visualization Python library.Provides elegant and concise construction of versatile graphics.Usage: Can be used in Jupyter Notebooks and can provide high-performance interactivecharts and plots.D3.js: D3.js (used with Flask) is a framework used with HTML, CSS, and Javascript together tocreate visualizations.Usage: Use D3.js build-in data-driven transitions for extra customization and elevatedvisualization for your data.Pro: Helps build type of framework you want (Plotly uses D3.js library, here you can use theD3.js library itself; open-source)Con: High learning curve; you need to learn HTML, CSS, JavascriptPlotlyResources

Bokeh - ExampleExample of using Bokeh from article. Screenshots of interactive features that Bokeh offers:PlotlyResources

ReferencesData Visualization - References

Bokeh is an interactive visualization Python library. Provides elegant and concise construction of versatile graphics. Usage: Can be used in Jupyter Notebooks and can provide high-performance interactive charts and plots. Plotly - Alternatives (Bokeh, D3.js) D3.js:

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