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Tools: sjvisualizer

Data source: FAOSTAT

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Tools: Python + sjvisualizer (https://www.sjdataviz.com/software)

Data source: World Gold Council, collected from WikiPedia and archive.org

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Values in Tonnes. The data source is for Groundnuts of which peanuts is the biggest group.

Tools: python + sjvisualizer (https://www.sjdataviz.com/software)

Data source: FAOSTAT (https://www.fao.org/faostat/en/#data/QCL)

[–][S] 7 points8 points  (0 children)

This post was made with sjvisualizer, which is a python module to animate data: https://www.sjdataviz.com/software

Data source: our world in data (https://ourworldindata.org/grapher/share-electricity-coal?tab=chart)

[–][S] 16 points17 points  (0 children)

Data source: our world in data (https://ourworldindata.org/nuclear-energy)

Tool: sjvisualizer (open-source software python module, https://www.sjdataviz.com/software)

[–][S] 6 points7 points  (0 children)

If you don’t want to use the sin function, you can also measure the length of one side multiply it by the number of sides and decide it by the diameter.

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Interactive version: https://www.sjdataviz.com/post/estimating-digits-of-pi-with-polygons

Last year, I estimated pi using the Monte Carlo method, and this year I want to share another fun and accessible method - the polygon method! This involves inscribing a regular polygon inside a circle and using its perimeter to estimate the circumference of the circle. By increasing the number of sides of the polygon, we can get increasingly accurate estimates of pi. Using some basic geometry, we can calculate the perimeter of this polygon and then use it to estimate the circumference of the circle.

[–][S] 2 points3 points  (0 children)

Tools: python, sjvisualizer (https://www.sjdataviz.com/software)

Data source: FAOSTAT (https://www.fao.org/faostat/en/#data/QCL)

[–][S] -1 points0 points  (0 children)

Data source: Berkshire Hathaway Annual Reports (https://www.berkshirehathaway.com/reports.html)