title: “Preparing and Formatting Data” subtitle: “Intro Guides” description: “Describes some tips that you can use to prepare and format your data before importing to CARTO.” layout: “guide” type: ‘intro’ time: “10 min” tags:
CARTO automatically includes guessing functionality during the import process, which is useful when files (or fields of data) are missing required upload information. As a best practice, you can also prepare and format data before connecting it to CARTO. This helps avoid errors and performance issues, even if you are using one of the supported geospatial formats.
CARTO supports a large number of data types and file formats, including shapefiles, KML, GeoJSON, CARTO files, and more. For details about the type of data that you can import, see Supported Geospatial Data Formats.
It is highly recommended that you compress your files before importing them. CARTO supports .ZIP and .GZ (which includes .TAR.GZ and .TGZ) for compressing and archiving files.
If you are importing a non-supported file type, the import will fail. See Import Errors for a list of known error codes and solutions.
When you import a file into your account, CARTO checks if the file contains latitude and longitude column names. If detected, those values are used to automatically geocode your data during the import process. Behind the scenes, CARTO uses PostgreSQL extensions to programmatically convert your data into geometries, based on services from our data providers.
the_geomcolumn of your dataset.
Before importing data, it is recommended to change any column headers to latitude and longitude to populate
the_geom column with geometry coordinates. There should be one column for latitude, and one column for longitude. Otherwise, once data is imported, you can geocode your data to convert it to geometry coordinates. The Geocode analysis is subject to quota limitations and extra fees may apply.
Geocoding street address data is allocated to your account, and is subject to quota limitations. A permitted amount of credits are allowed per month, based on your account plan. Any geocode matches to the indicated street address consumes credits from your account.
If you have a .CSV file, it should be saved with UTF-8 encoding so that the data is imported into CARTO properly. This helps if there are any special characters in your data.
Confirm that your data includes proper projections. By default, CARTO uses the EPSG 4326 projection to store geospatial data in your dataset. When data is imported,
the_geom column is created and displays the latitude and longitude in a single projection, using the WGS84 cartographic method (EPSG 4326 projection).
You can always change the map projection to a compatible projection, using
the_geom_webmercator column in your dataset.
Shapefiles, a widespread format for transferring spatial data (created by ESRI), can be imported into CARTO. Shapefiles are collections of three or more associated files. To import them into CARTO, make sure all files (SHP, DBF, SHX, and possibly PRJ) have the same name, and are compressed as a ZIP file.
View more tips about preparing Shapefile data for CARTO.
Some of these other data formatting tips may help with accuracy and performance in CARTO.
If you are importing numeric data for thematic maps, are your data values normalized? As a general rule, be sure to normalize numeric data before importing it to CARTO; since using raw numbers may misrepresent data.
For performance issues, it is recommended to sample your data in order to work with a smaller, more manageable size of data. For example, when importing OSM data.
OpenStreetMap data contains features that make up our cities, including neighborhoods, streets, roads, and even lampposts. OpenStreetMap data is contributed by a diverse community, is rich with local knowledge, and frequently updated.
Sampling your data is also recommended when you are applying long-running analyses in Builder. Ideally, your data is sampled before it is imported to CARTO. Otherwise, you can apply the Subsample percent of rows analysis to a map layer as the first analysis in a workflow. This keeps the size of your data managable and improves performance.
Now that you have reviewed and prepared your data, import it to CARTO!