Data Visualization: Plotly

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Data Visualization: PlotlyCreated By:Joshua Rafael

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or Seaborn.Con: Confusing initial setup to use Plotly without an online account, and lots ofcode to write.Con: Out-of-date documentation and the large range of Plotly tools (ChartStudio, Express, etc.)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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p a plotly object. fun a function. Should take a plotly object as input and return a modified plotly object. arguments passed to fun. add_trace Add trace(s) to a plotly visualization Description Add trace(s) to a plotly visualization Usage add_trace(p, ., data NULL, inherit TRUE)File Size: 210KB

Plotly ii About the Tutorial This tutorial is about Canada based technical computing company Plotly which is also known for its URL. Here, you will learn about how to develop data analytics and visualization tools. Moreover, this tu

Feb 18, 2020 · DASH PLOTLY Presentation Dash “Dash is the fastest way to build interactive analytic apps” (says their website) Open source under MIT licensing Dash is available for both Python and R (similar to RStudio) good&illustrated documentation: Plotly HTML/JS

Instructions and FAQs for creating and submitting interactive Plotly figures to F1000Research Creating Plotly figures 1a. Online method using your Plotly cloud account Go to to sign up. The default Community account is free, and has all the features needed to cr

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