[null, {"document_url": "https://helgasoft.com/tools/fr.visa.html", "unformatted_src": "https://2268e15ae1206fc04954-76b466cd72f6b3a6e7219a8a02851d8e.ssl.cf1.rackcdn.com/files/5a2696d7ff39355f1aaa0897/size_3_picture.png", "src": "https://2268e15ae1206fc04954-76b466cd72f6b3a6e7219a8a02851d8e.ssl.cf1.rackcdn.com/files/5a2696d7ff39355f1aaa0897/size_3_picture.png", "formatted_filename": "size picture", "rendered_width": 300, "rendered_height": 169}]
Put me on a map!

Have you seen web pages screeming "Put me on a map!" ? One found lately was the French Tech Visa page. Having a soft spot for things french, we decided to 'repair' the injustice and geocode the companies listed (as of Dec 2017). Luckily, all the data was inside the page source in JSON format. To clean and use it in R, one could simply copy and assign it to a variable, then source it in RStudio to fix any errors. Then it can be converted to a data.frame.

Next step was to extract the addresses (companies[1:100,]$Adresse), clean them of special characters and try a batch geocode online. From the KML output file, one could extract the lon/lat coordinates and match them to the companies by address. As a result, the companies data frame gets two more columns - latitude and longitude. We saved this geocoded data in a second JSON file.
Used Javascript next to recode the data from JSON to geojson format. You can see the file raw, or here on a map. Finally we read this same geojson file and present it on a Leaflet map with clustering - here below. Clicking on a company marker will show the details just below the map. Et voilà!

Click on a map marker to see details here.