Carto

command-line python interface for manipulating data on CartoDB

This example demonstrates a command-line Python tool for managing and manipulating data stored on CartoDB, allowing users to upload files, overwrite or append rows, add columns, drop tables, and export datasets. It first shows the workflow of interacting with CartoDB’s SQL and Import APIs, then explains the underlying implementation. The script uses the `requests` library for HTTP calls, `urllib2` for polling import status, and `argparse` for command-line options, translating between CartoDB’s data types and PostgreSQL types during column alterations and insertions.

66% match

Easy example | CartoDB.js

This example shows a full-screen interactive map that renders a dataset called "untitled_table_5" with custom CartoCSS styling. The map displays points, lines, and polygons in a red color scheme with white outlines, and includes tooltips triggered by interactivity on the `cartodb_id` field. The code uses the CartoDB.js library version 3, specifically `cartodb.createVis`, which loads the visualization from a JSON configuration object. The base map is provided by OpenStreetMap tiles via Leaflet, while the geographic data is queried from a CartoDB table using SQL and styled with CartoCSS rules for each geometry type.

65% 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.

64% match

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`.

Gist a61b3f54da810f6e9490

This example demonstrates how to map and animate earthquake data from the USGS CSV feed using CartoDB’s mapping tools. It shows temporal earthquake occurrences through an interactive map, with points updating over time. The code relies on CartoDB’s SQL API and JavaScript library for layer management, alongside D3.js for data-driven visualizations. It also integrates Chart.js for supplementary graphs and uses dynamic styling via CartoDB’s tile rendering. The visualization highlights both spatial distribution and time-based animation of seismic events.

Notes

A set of tutorial notes for CartoDB demonstrates a progression through mapping workflows, from importing CSV data with latitude/longitude coordinates to styling visualizations with CartoCSS and querying tables via SQL. The notes cover data editing, georeferencing, privacy settings, and integrating CartoDB.js for web maps, referencing external resources like colorbrewer2.org and PostGIS documentation.

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.

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.