This gist was created to demonstrate map generation with Leaflet.js, and all files are associated with my blog post under the same name.
We access map tiles through Open Street Maps (OSM) and then plot location data formatted as GeoJSON.
This gist was created to demonstrate map generation with Leaflet.js, and all files are associated with my blog post under the same name.
We access map tiles through Open Street Maps (OSM) and then plot location data formatted as GeoJSON.
D3.js visualization of Anscombe's Quartet. Each dataset in the quartet is graphed separately along with its linear best fit. While all datasets have the same summary statistics (mean, variance, correlation, linear fit), their structures differ markedly.
Anscombe used the quartet in his seminal paper "Graphs in Statistical Analysis" to emphasize the importance of data visualization for exploratory data analysis. Such visualization exploration enables the analyst to make more informed analytical decisions and conclusions.
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This gist was originally created to illustrate the data scrubbing process, and all files are associated with my blog post under the same name.
The file progression proceeds from data.txt
, a simple text document which contains a list of places, to formatting this original data set as GeoJSON, data.geojson
.
Once formatted as GeoJSON, we use D3.js to visualize the data, drawing inspiration from similar visualizations utilizing the same framework.
license: gpl-3.0 |
D3.js visualizations of data from Florence Nightingale's "A contribution to the sanitary history of the British army during the late war with Russia".
Several works served as inspiration:
A D3.js recreation of Charles Minard's Napolean's 1812 March.
Data from Wilkinson's The Grammar of Graphics.
Several works provided inspiration; see Michael Friendly's Re-visions of Minard.
Note that this implementation uses several different data files. Included are both original JSON files and associated GeoJSON files. For the army size labels, the data has been massaged some to agree with the (edited) army movements (data from Mike Bostock's Protovis implementation). River data is from Natural Earth; admittedly, the river da
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D3.js visualization of the famous polar area diagram from Florence Nightingale's "A contribution to the sanitary history of the British army during the late war with Russia".
Two works served as the inspiration for this implementation:
A few comments. Bostock's implmentation, while visually similar to Nightingale's visualization, is wrong. First, the data is not correct. You can verify this in Nightingale's original work. Second, Bostock directly maps the wedge radius to deaths. This mistake is common. Instead, Nightingale represents deaths in terms of area, thus requiring the radius for each