EPA Fuel Economy Data (Python Usage)

Contents

• Source
• Fuel prices
• All Vehicle Data
• Makes (year-specific)
• Model options
• Metadata (site-provided)
• Specific Vehicle Data

Source

http://www.fueleconomy.gov/feg/ws/index.shtml

Data services

• Fuel prices (national average?): http://www.fueleconomy.gov/ws/rest/fuelprices
• All vehicle data: http://www.fueleconomy.gov/feg/epadata/vehicles.csv.zip

• Data for a specific vehicle: http://www.fueleconomy.gov/ws/rest/vehicle/31873

  Can use https://www.fueleconomy.gov/feg/findacar.shtml to interactively search for a particular vehicle; then note the “id” query parameter in the URL that you are directed to and use that to query the data service.

• Makes for a particular year: http://www.fueleconomy.gov/ws/rest/vehicle/menu/make?year=2012
• Models for a particular year and make: http://www.fueleconomy.gov/ws/rest/vehicle/menu/model?year=2012&make=Honda
• Model options and the associated vehicle ID for a particular year, make and model: http://www.fueleconomy.gov/ws/rest/vehicle/menu/options?year=2012&make=Honda&model=Fit

Fuel prices

Code

from sinbad import *

ds = DataSource.connect_load("http://www.fueleconomy.gov/ws/rest/fuelprices", format="xml")
ds.print_description()
print( ds.fetch("premium") )

Output

dictionary with {
  cng : *
  diesel : *
  e85 : *
  electric : *
  lpg : *
  midgrade : *
  premium : *
  regular : *
}
2.86

All Vehicle Data

Code

from sinbad import *

ds = DataSource.connect_load("http://www.fueleconomy.gov/feg/epadata/vehicles.csv.zip")
ds.print_description()
print( ds.fetch_random("make", "model", "year", "city08", "highway08") )

Output

{'make': 'Ford', 'model': 'F150 Pickup 2WD', 'highway08': '19', 'year': '2003', 'city08': '14'}

Makes (year-specific)

Code

from sinbad import *

ds = DataSource.connect("http://www.fueleconomy.gov/ws/rest/vehicle/menu/make", format="xml")
ds.set_param("year", "2012")
ds.load()
makes = ds.fetch("value")
print(makes)

Model options

Code

from sinbad import *

ds = DataSource.connect("http://www.fueleconomy.gov/ws/rest/vehicle/menu/options", format="xml")
ds.set_param("year", "2012")
ds.set_param("make", "Honda").set_param("model", "Fit")
ds.load()

for e in ds.fetch():
    print( e['text'], " ID:", e['value'] )

Output

Auto (S5), 4 cyl, 1.5 L  ID: 31819
Auto 5-spd, 4 cyl, 1.5 L  ID: 31818
Man 5-spd, 4 cyl, 1.5 L  ID: 31817

Specific Vehicle Data

See previous one for searching for vehicle IDs, or use https://www.fueleconomy.gov/feg/findacar.shtml to interactively search for a particular vehicle; then note the “id” query parameter in the URL that you are directed to.

Code

from sinbad import *

ds = DataSource.connect_load("http://www.fueleconomy.gov/ws/rest/vehicle/31819", format="xml")
print( ds.fetch("make", "model", "trany", "year", "city08", "highway08") )

Output

{'city08': '27', 'model': 'Fit', 'make': 'Honda', 'year': '2012', 'trany': 'Automatic (S5)', 'highway08': '33'}

Metadata (site-provided)

• http://www.fueleconomy.gov/feg/ws/index.shtml#vehicle
• http://www.fueleconomy.gov/feg/ws/index.shtml#fuelprices