Live-updates with Datawrapper: An overview
Datawrapper has an option to update charts and tables automatically, without republishing. This can be useful when visualizing daily updated election charts, daily reports of COVID-19 case numbers, etc. Every time a user updates a website with your chart, the chart will freshly get the data from the CSV.
Here is a round-up of everything you need to know about live-updated visualizations with Datawrapper. If you're not sure where to start, start here.
By visualization type
- live-update charts (or if you're new to live-updated charts) → How to create a live-updating chart
- live-update choropleth/ symbol maps → How to create a live-updating symbol map or choropleth map
- live-update locator maps → this blogpost might help: Tomorrow’s weather in Datawrapper: A live-updating locator map
- live-update tables → some hacks for live-updating sparklines, mini-columns, and heatmaps inside tables here
External CSV & JSON data
- If you have external CSV data from an API that you want to edit first before you upload it into Datawrapper → How to set up automatic updates on a Google Sheet
- If you have external JSON data you want to upload → How to create live-updating charts with JSON data
- You can also update chart metadata → How to create a chart with live-updating metadata
Using API for automation
- Datawrapper Developer Docs → Automatic updates for live data
- R package → Why I created an R package to use Datawrapper’s API and how to use it
- Python library → How to use the new Python library “datawrapper” to create 34 charts in a few seconds
FAQ & Troubleshooting
- My live-updating chart is not updating/not appearing.
- I get the message "Undefined" when I upload a CSV.
- How do I add "Last updated" timestamps to visualizations?
Still have questions? Reach out at firstname.lastname@example.org.