TLDR: There are many great interactive dashboarding options in Python, which should you use? Jump to the comparison for our thoughts.  It's often

Dash, Voila, Panel, & Streamlit—Our Thoughts on the Big Four Dashboarding Tools

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2022-05-14 07:30:08

TLDR: There are many great interactive dashboarding options in Python, which should you use? Jump to the comparison for our thoughts.

It's often said that a picture is worth a thousand words, and similarly so is a well-crafted data visualization. It conveys a complex message quickly and effectively. There are examples throughout history of people telling a visual story of what is happening in their datasets.

One of the most famous examples is from French civil engineer, Charles Minard. In 1869, Minard created this precursor to the modern Sankey diagram that shows the dwindling size of Napoleon’s army as it advanced through Russia during the Russian campaign of 1812-1813. Minard captured five different variables in his map—direction, distance, size, location, and temperature.

While data visualizations like these are great at conveying meaning for an established dataset, where they fall short is in providing a path to understanding during exploratory analysis of new and complex data. This is where interactive visualization dashboards come into play. By providing an interface to interact with the data and seeing how changes in key parameters affect various outcomes, these tools provide users a way to gain deeper insights into what the data is telling them.

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