Carto Super Camp

CartoDB SQL tricks: Various things that as a SQL-newbie I had to search for >10 minutes to find answers for.

This example demonstrates a collection of SQL recipes for solving common spatial data problems in CartoDB, ranging from merging neighboring county polygons with ST_Union to creating great circle lines via ST_MakeLine and ST_Segmentize. It shows practical techniques like updating geometries with conditional CASE statements, extracting coordinates with ST_X and ST_Y, stripping HTML tags using regexp_replace, and formatting zip codes with to_char. The code also covers performance strategies for large updates and querying spatial relationships with st_contains. Each snippet targets PostGIS functions within the CartoDB platform, emphasizing data preparation and geometric transformations.

Aandrewbt

64% match

Gist 89811213f98645c51fa8

Using CartoDB’s SQL API and PostGIS functions, this notebook explores Gilt purchase data aggregated by zip code. It shows a series of interactive maps, including a bubble map of average session time and choropleths of purchase rates, built from geocoded postal points and polygon tables. The workflow demonstrates nested SQL subqueries to join transaction aggregates with geometries, spatial filtering with `ST_Intersects` and `ST_Buffer` around New York City, and on-the-fly centroid generation via `st_centroid` for a target audience map. Geocoding and tile rendering rely on CartoDB’s default web-mercator projection.

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rundown

This example demonstrates how SQL queries can filter, analyze, and modify geographic data in CartoDB, using Massachusetts census blocks and Boston corner store locations. It shows spatial queries like distance calculations and bounding-box filters, plus joins to compute nearest fire station distances. The code uses the CartoDB SQL API and CartoDB.js library, with Leaflet for map rendering, to apply dynamic SQL filters and create visualizations without altering the underlying dataset.

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Fun SQL statements for CartoDB

This example shows how to explore and analyze tornado and county data in CartoDB using SQL statements. It demonstrates basic queries for filtering, sorting, and aggregating records, followed by spatial functions that inspect geometry types, compute areas, distances, and intersections. The code uses PostGIS functions such as `ST_Area`, `ST_Distance`, `ST_Intersects`, and `ST_DWithin`, alongside CartoDB-specific helpers like `CDB_LatLng`. It also includes updates to add tornado counts and density per county, highlighting how SQL can drive interactive map visualizations.

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Gist 7c1efd9bdead734010b0

This tutorial demonstrates how to build interactive maps and animated visualizations of a cat’s GPS tracking data using CartoDB’s web interface, SQL, and CartoCSS. It shows point, categorical, and temporal bubble maps, including a Torque animation of Spencer the Cat’s movements over time. The code uses CartoDB’s SQL API with functions like `ST_MakeLine` and `date_part`, along with CartoCSS styling for markers. It also covers importing polygon building datasets from MassGIS and querying them with spatial operations like `ST_Distance` and `CDB_LatLng`.

NACIS Workshop | CartoDB

A step-by-step workshop guide demonstrates CartoDB's mapping and data-analysis capabilities through a sequence of exercises. The HTML page embeds a Speaker Deck presentation and lists tasks covering data import, visualization styling with CartoCSS, SQL filtering, and spatial queries. It references downloadable shapefiles, including tornado paths, NYC bike blocks, and tracked location data, with example SQL statements for distance calculations. The code loads CartoDB.js v3 and its CSS to support interactive map rendering throughout the tutorial.

Map Connections | CartoDB.js

Clicking a ZIP code polygon on a U.S. map triggers a dynamic query that draws purple curved lines from that selected area to nearby ski resorts within a 1,000-unit distance. The example uses CartoDB.js with Leaflet to render the base map and vector layers, while a CartoDB SQL API call executes `ST_MakeLine`, `ST_Segmentize`, and `ST_Transform` to generate geodesic connection paths in GeoJSON format. Interactivity includes cursor changes on feature hover and line removal/replacement on each new click, with styling controlled through CartoCSS.

Batch API uploads to CARTO

This example shows how to upload large datasets to CARTO by splitting them into smaller chunks and using the SQL Batch API to merge them. It demonstrates three chained batch queries: creating a combined table with `CREATE TABLE ... UNION ALL`, dropping the `cartodb_id` column with `ALTER TABLE`, and finalizing with `cdb_cartodbfytable`. The code references CARTO’s SQL API and batch query chaining, alongside a Python script from `carto-etl` and GDAL/ogr2ogr alternatives for record-by-record inserts.

Aandrewbt