Community Data Science Workshops (Fall 2015)/Day 3 Projects/Civic data

Building and visualizing datasets using data.seattle.gov and Google apps
In this project, we will explore a few ways to analyze and visualize data from data.seattle.gov. We will examine trends in the construction of houses, townhomes, and condos in Seattle over the last five years, in order to determine the true extent of the current "construction boom".


 * We'll download data from two APIs (Socrata open data platform and Google Maps)
 * We'll analyze trends over time in our dataset
 * We'll visualize our data in graphs and heatmaps

Topics we will cover

 * Writing and testing complex API queries
 * Reading and writing CSV and JSON files
 * Filtering and aggregating data
 * Combining data from multiple APIs
 * Graphing and mapping data

Preparation

 * Step 1: Download today's scripts: Python scripts
 * Step 2: Download today's datasets: datasets

If you are confused by anything today, go back and refresh your memory with the Day 0 setup and tutorial and Day 0 tutorial

Part 1: getting the building permit data

 * Get the dataset: https://data.seattle.gov/Permitting/Building-Permits-Current/mags-97de


 * Run the script: download_building_permit_data.py

Now open up the CSV output file to verify that you got all the data you asked for.

Part 2: charting new construction by month

 * Question: Has the rate of residential construction increased since 2010?

Now we want to learn whether there is, in fact, a housing boom in Seattle. We'll do this by counting how many new permits are issued each month, and then plot these on a graph.

Run the script building_permits_by_month.py

Now open up the CSV output file and check your data. Does this look right to you?


 * Challenge question: how could we separate out single family homes from apartments, and count/plot them separately?

Part 3: charting new construction by neighborhood

 * Question: which Seattle neighborhoods have had the most multifamily residential construction (apartments and townhomes) since 2010?

Now we want to learn where all this new construction is happening. We'll do this by sending the address for each MULTIFAMILY permit to the Google Geolocation API, which will return the neighborhood where that address is located.

Run the script building_permits_by_neighborhood.py

Now open up the CSV output file and check your data. Does this look right to you?


 * Challenge question: In which Seattle neighborhood is the cost of new apartment construction projects highest, on average?

Part 4: Mapping new home construction in Seattle

 * Question: what locations have experienced the highest density of new construction since 2010?

Now we will try to get an even more detailed picture of where this construction is occuring, using Google Fusion tables, a powerful visualization application that makes it easy to plot data on a map.

Go here and follow the steps to upload your new_all_2010-2015.csv file.


 * Create a point map and heatmap.
 * Experiment with filtering and weighting the points on your map.


 * Example map: https://www.google.com/fusiontables/data?docid=1gm0wVqnK7zQ7hgp5bsKoBIetMZ75jo-VMs5noDoJ#map:id=3

Going further
''Try to answer these additional questions that draw on the data and methods we're learning today. Ask a mentor if you get stuck!''
 * 1) Which developer has spent the most on new construction in Seattle since 2010?
 * 2) How many townhouses have been constructed in Seattle since 2010?
 * 3) Where in Seattle are the most commercial buildings being constructed in 2015?
 * 4) How does the rate of residential construction in Seattle from 2010-2015 compare to the previous 5 years?

Resources

 * Datasets
 * Permits, last 5 years: https://data.seattle.gov/Permitting/Building-Permits-Current/mags-97de
 * Permits older than 5 years: https://data.seattle.gov/Permitting/Building-Permits-Older-than-5-years/47eb-r92t


 * Sample API queries
 * Building permit data: https://data.seattle.gov/resource/mags-97de.json?$where=issue_date%20IS%20NOT%20NULL%20&action_type=NEW&category=MULTIFAMILY&$limit=100
 * Google maps location (using street address): http://maps.googleapis.com/maps/api/geocode/json?address=5601+22ND+AVE+NW+Seattle+WA
 * Google maps location (using lat/long): http://maps.googleapis.com/maps/api/geocode/json?latlng=47.66979666%2C-122.38570052


 * Hurl.it API testing tool: https://www.hurl.it


 * Google tools
 * About Fusion table heatmaps: https://support.google.com/fusiontables/answer/1152262
 * About Google maps geocoding API: https://developers.google.com/maps/documentation/geocoding/

Socrata open data portal

 * More about the Socrata open data portal and API: http://www.socrata.com/products/open-data-portal/
 * Example of a Socrata API-powered app: http://web6.seattle.gov/mnm/
 * Socrata API help resources: http://dev.socrata.com/consumers/getting-started.html
 * filtering results: http://dev.socrata.com/docs/filtering.html
 * dealing with timestamps: http://dev.socrata.com/docs/datatypes/timestamp.html
 * writing API queries: http://dev.socrata.com/docs/queries.html


 * Socrata API instructional videos
 * https://data.seattle.gov/videos
 * https://www.youtube.com/watch?v=YlKzXTrTLOQ
 * https://www.youtube.com/watch?v=Whfp8ojMf0U
 * https://www.youtube.com/watch?v=Vd6bwz3ivVA


 * Some other government website that use the Socrata API
 * https://data.austintexas.gov/
 * https://data.cityofchicago.org/
 * https://data.cityofnewyork.us/