Since late last year Felt has welcomed uploads of large files in all popular vector formats up to 5GB with styling and editing for advanced, data-driven maps. You’ve uploaded tens of thousands of files in the four months since.
Now we’re going beyond simple vector file formats and styles to support even more kinds of uploads. We’ve seen our users hopefully provide data with non-lat/lon data like place names or addresses, data with numeric columns to visualize, and data with multiple nested layers. We’re making Felt an even better data uploading experience for stying and sharing complex data.
Starting today, users can:
- Upload any tabular data with geographic entities like zip codes, place names, or street addresses and see them on a map automatically geocoded into vector polygons or points;
- Style data uploads with visualizations driven by numeric column statistics;
- Combine uploaded datasets into merged and nested layers to tell a richer story.
Geocoding & Geomatching
Upload your data with only addresses or administrative boundaries and Felt will map it with no additional steps necessary!
Many valuable mapping datasets are hidden away in spreadsheets with address, place name, or zip code columns. Turning them into maps can be a time-consuming, complex, or costly application of data joins and geocoding APIs. Felt’s Geomatching recognizes compatible data automatically and converts it into maps. When you upload files without lat/lon geometries we’ll look for street addresses, country names, provinces, states, and popular location codes like ZIP, FIPS, ISO-3166, and others to automatically turn them into visual maps just like any other upload.
Matching free-form input data to geographic entities is a common chore in map-making. Many maps are created from text descriptions with place names in them, and these must be painstakingly matched to the correct thing: administrative regions chosen, postal codes looked up, and addresses converted to individual points. Felt’s geomatching feature makes it easy by magically supporting a growing list of likely inputs:
- Felt finds addresses in single fields or multiple columns and sends them to Geocode Earth to be turned into points;
- Felt recognizes names and ISO-3166 codes for countries, states, provinces, and other major areas around the world and incorporate their boundary shapes from the global Natural Earth dataset;
- Felt understands common U.S. Census geographic summary level FIPS codes for counties, tracts, core-based statistical areas, and zip code tabulation areas.
See our docs for a complete guide to data we recognize!