Click on the title links to download the data for each session. Unzip the folders and place them on your desktop.
Two subfolders, with the following files:
gdp_pc_2013.csv CSV file with World Bank data on GDP per capita for the world’s nations in 2013, in current international dollars, corrected for purchasing power in different terrorities.sf_test_addresses.tsv Text file containing a list of 100 addresses in San Francisco, derived by “reverse geocoding” from a sample of San Francisco reported crime incidents. Note that these are not the exact locations of crimes, as the original locations were not precisely mapped to address, see here for details. (The file has been given the extension .tsv, for “tab-separated values,” so that the commas in the addresses will not be interpreted as separators between fields in the data by the software we will use to geocode it.)sf_addresses_short.tsv The first 10 addresses from the previous file.refine-geocoder.json A script in JSON format that we will use to automate geocoding.The geocoding files can also be downloaded from my GitHub account — click the Download ZIP button at right.
Several subfolders, with the following files/folders:
quakes_1964_2013_5+.csv Earthquakes with a magnitude of 5 and greater that occurred within a circles of radius 6,000 kilometres, extending from geographical center of the continental United States. From U.S. Geological Survey data.
seismic_risk Shapefile detailing the risk of experiencing a damaging earthquake by location for a geographical region focused on the continental the United States, from the U.S. Geological Survey.
seismic_risk_clip The same data, clipped to the boundaries of the continental United States.
ne_50m_admin_0_countries ne_50m_lakes Global shapefiles from Natural Earth giving boundaries for nations and lakes respectively.gdp_pc_2013.csv gdp_pc_2013,csvt CSV file with World Bank data on Gross Domestic Product per capita for the world’s nations in 2013, in current international dollars, corrected for purchasing power in different territories. The second file is necessary to perform a data “join” in QGIS.sf_test_addresses Shapefile with geolocations for the same addresses we geocoded in this morning’s session.storms.csv Shapefile with data on tropical storms and hurricanes in the North Atlantic compiled by the U.S. National Oceanic and Atmospheric Administration (NOAA). I have processed the raw data to give the following fields for storms from 1990 onwards:
name Official name for each storm; unnamed storms are listed as Unnamed and also numbered.year month day hour minute Date and time fields for each observation.timestamp Date and time fields combined into a full timestamp for each observation in YYYY-MM-DD HH:MM format.record_ident The entry L indicates the time at which a storm made landfall, defined as the center of the system crossing a coastline, recorded from 1991 onwards.status Options include HU for hurricane, TS for tropical storm and TD for tropical depression.latitude longitude Geographic coordinates for the center of the system at each observation.max_wind_kts max_wind_kph max_wind_mph Maximum sustained wind for each observation in various units.min_press Minimum air pressure at the center of the system for each observation in millibars.newhurdat-format.pdf More explanation of the raw storms data from NOAA, including the full list of storm status codes.
2013_Q1 Shapefile with data on violent events in the Syrian civil war from the first quarter of 2013, derived from GDELT project data. See here for more on how these events were classified.Four subfolders, with the following files:
quakes.csv All quakes with a magnitude of 5 and greater from 1964 to 2013 inclusive, in a circle with a radius of 6,000 kilometers from the center of the continental United States.seismic_risk.geojson The seismic risk data from yesterday in GeoJSON format, clipped to the borders and coastline of the continental United States.storms_points.csv Observations on North Atlantic hurricanes and other tropical storms. This is the data in the shapefile you worked with yesterday in CSV format.storms_tracks.zip Zipped shapefile showing the tracks of each storm since 1990, as you made yesterday with QGIS from the points shapefile.sf_test_addresses.csv The same sample of geocoded addresses in San Francisco from yesterday.sfpd_stations.zip Zipped shapefile with locations and other data for police stations in San Francisco, from DataSF, the city’s data portal.syria_all.csv CSV file documenting violent events in the Syrian civil war from the start of 2011 to the end of the first quarter of 2013, derived from GDELT project data. See here for more on how these events were classified.There is also a template web page, test.html in which to embed maps made with CartoDB.
One folder, containing the following:
This in turn contains two subfolders:
data contains a single file, seismic_risk.js. This is the seismic risk GeoJSON data we earlier imported into CartoDB, declared as a JavaScript variable by pasting it into the following code:var seismic_risk =
//GeoJSON pasted here
;
src contains two JavaScript files, date-format.js and leaflet.ajax.min.js. The first is a script by web developer Steven Levithan, which we will use to format dates. The second is a Leaflet plugin, which we will use to turn GeoJSON returned by an API into a Leaflet map layer.