Tag: geocoding

Urban Informatics and Visualization at UC Berkeley

Post author By gboeing
Post date 2015-08-20
10 Comments on Urban Informatics and Visualization at UC Berkeley

The fall semester begins next week at UC Berkeley. For the third year in a row, Paul Waddell and I will be teaching CP255: Urban Informatics and Visualization, and this is my first year as co-lead instructor.

This masters-level course trains students to analyze urban data, develop indicators, conduct spatial analyses, create data visualizations, and build Paris open data interactive web maps. To do this, we use the Python programming language, open source analysis and visualization tools, and public data.

This course is designed to provide future city planners with a toolkit of technical skills for quantitative problem solving. We don’t require any prior programming experience – we teach this from the ground up – but we do expect prior knowledge of basic statistics and GIS.

Update, September 2017: I am no longer a Berkeley GSI, but Paul’s class is ongoing. Check out his fantastic teaching materials in his GitHub repo. From my experiences here, I have developed a course series on urban data science with Python and Jupyter, available in this GitHub repo.

Tags academia, anaconda, arcgis, berkeley, cartodb, city, code for america, data, data science, geocoding, geopandas, geopy, geospatial, gis, github, javascript, land use, leaflet, localdata, mapbox, maps, matplotlib, modeling, numpy, pandas, planning, projection, qgis, science, scikit-learn, scipy, scrapy, shapely, smart cities, socrata, statistics, tilemill, tutorial, urban, urban design, urban planning, visualization, wordpress

Data

Visualizing Summer Travels

This is a series of posts about visualizing spatial data. I spent a couple of months traveling in Europe this summer and collected GPS location data throughout the trip with the OpenPaths app. I explored different web mapping technologies such as CartoDB, Leaflet, Mapbox, and Tilemill to plot my travels. I also used Python and matplotlib to run some descriptive statistics and visualize other aspects of my trip.

Here is the series of posts:

My Python code is available in this GitHub repo. I also did some more involved work under the hood to prep the data and support these visualizations. For example, in the following posts I reverse-geocoded the spatial data set and reduced its size with clustering algorithms and the Douglas-Peucker algorithm:

Tags cartodb, clustering, data, douglas-peucker, geocoding, geospatial, gis, leaflet, mapbox, matplotlib, projection, python, tilemill, travel, visualization

Data

Reverse Geocode a Set of Lat-Long Coordinates to City + Country

Post author By gboeing
Post date 2014-08-14
9 Comments on Reverse Geocode a Set of Lat-Long Coordinates to City + Country

This tutorial demonstrates how to reverse geocode a set of latitude-longitude coordinates to city and country using Python and the Google Maps API.

I have previously written about my GPS location data from this summer’s travels. The data set, gathered with the OpenPaths app, contains lat-long coordinates and timestamps. Without city or country data, any visualizations would be very simplistic because all I have is coordinates and timestamps. It would be nice to reverse geocode these coordinates to add city and country data to each point. Then, I could create richer, more informative marker popups that include this new geographical information.

Tags data, geocoding, google, maps, python, travel, tutorial