The Philadelphia electrical, natural gas, and water utilities websites each allow for a residential account holder to access (and export!) their own usage data.
This Django web application imports utility usage data. The data is then displayed with HighCharts and DataTables.
The website is publicly available online at:
New data can be added (by staff) one of two ways:
- Upload a file of usage data generated by one of the utility companies.
- Manually using the appropriate Django management commands documented below.
- The
/add/view allows an authenticated staff user to upload a file of usage data. - Uploads are processed and any new data is inserted/updated to the appropriate model.
There are also Django management commands to import each utility file:
electric_fillnatural_gas_fillwater_fill
Examples of each of these management commands, including output, is below per utility.
A ZIP (.zip) archive containing a comma-separated values (.csv) file, of
electricity used in kilowatt-hours (kWh), can be downloaded from the
"My Green Button Data"
page of the "My Usage" section of the PECO website:
The export CSV file from PECO is named based upon the dates exported, like so:
peco_electric_usage_interval_data_Service 1_1_2023-07-04_to_2023-07-04.csv
The PECO file begins with a header that includes account information:
Name,WILLIAM PENN
Address,"1 S BROAD ST, PHILADELPHIA PA 19112"
Account Number,1776xxxxxx
Service,Service 1
Each row of the PECO CSV export file has kilowatt-hours (kWh) of electricity used, as well as the start and end of the hour measured:
TYPE,DATE,START TIME,END TIME,USAGE (kWh),NOTES
...
Electric usage,2024-12-17,18:00,18:59,0.46
Electric usage,2024-12-17,19:00,19:59,0.44
Electric usage,2024-12-17,20:00,20:59,0.41
Electric usage,2024-12-17,21:00,21:59,0.51
Electric usage,2024-12-17,22:00,22:59,1.08
Electric usage,2024-12-17,23:00,23:59,2.92
The electric_fill Django management command imports this file into the database:
$ python3 manage.py electric_fill
1 CSV file(s) found.
...
Created: Tuesday, December 17, 2024 @ 06 PM (2024-12-17 18:00:00-05:00) [0.46 kWh]
Created: Tuesday, December 17, 2024 @ 07 PM (2024-12-17 19:00:00-05:00) [0.44 kWh]
Created: Tuesday, December 17, 2024 @ 08 PM (2024-12-17 20:00:00-05:00) [0.41 kWh]
Created: Tuesday, December 17, 2024 @ 09 PM (2024-12-17 21:00:00-05:00) [0.51 kWh]
Created: Tuesday, December 17, 2024 @ 10 PM (2024-12-17 22:00:00-05:00) [1.08 kWh]
Created: Tuesday, December 17, 2024 @ 11 PM (2024-12-17 23:00:00-05:00) [2.92 kWh]
Total: 24
Done.The electric_weekend Django management command compares electric usage on
weekdays vs. weekends:
$ python3 manage.py electric_weekend
From: Sat Jan 21 23:00:00 2023 (2023-01-21 23:00:00-05:00) [2 years, 2 months ago]
To: Mon Apr 14 23:00:00 2025 (2025-04-14 23:00:00-04:00) [4 days, 20 hours ago]
Weekdays: 8,910.2900 total kWh / 13,944 total hours = average 0.6390 kWh over 1 year, 7 months.
Weekends: 3,966.6500 total kWh / 5,590 total hours = average 0.7096 kWh over 7 months, 2 weeks.
Total: 12,876.9400 kWh / 19,534 hours = average 0.6592 kWh over 2 years, 2 months.
An Excel (.xlsx) spreadsheet file of natural gas, used in hundreds of cubic
feet (CCF), each (billing) month can be downloaded from the
"usage" section
of the Philadelphia Gas Works (PGW) website:
The Excel spreadsheet from PGW is named by the date it was exported
(such as UsageDataMMDDYYYY.xlsx):
UsageData12142024.xlsx
The PGW file also begins with a header that includes account information:
Service Point Number: 1776xxxxxx
Period: Jan 2021 To Jun 2021
Property: 1 S BROAD ST (xxxxx1776)
Each row of the PGW file includes hundreds of cubic feet (CCF) of natural gas used each billing month:
Bill Month Units Consumed (CCF) Period Start Period End
Jan, 2021 50.00 12/18/20 01/21/21
Feb, 2021 73.00 01/21/21 02/22/21
Mar, 2021 45.00 02/22/21 03/22/21
Apr, 2021 17.00 03/22/21 04/21/21
May, 2021 10.00 04/21/21 05/20/21
Jun, 2021 5.0 05/20/21 06/18/21
The natural_gas_fill Django management command imports this file into the database:
$ python3 manage.py natural_gas_fill
1 spreadsheet(s) found.
...
Created: March 2025 (2025-03-01) [33.0 CCF]
Total: 1
Done.
Comma-separated values ("CSV" / .csv) file of water used, in gallons, daily.
A CSV file can be downloaded by "Gallons" of water used "Daily" from the
"Detailed Usage"
section of the Philadelphia Water Department (PWD) website:
The water usage export .csv file is always named ChartData.csv.
Each row of the PWD file includes the number of gallons of water used each day:
Access Code, Time Interval, Consumption, Units
00145xxxx, 11/27/2024, 18.7013, Gallons
00145xxxx, 11/28/2024, 35.9065, Gallons
00145xxxx, 11/29/2024, 35.1584, Gallons
00145xxxx, 11/30/2024, 44.8831, Gallons
00145xxxx, 12/01/2024, 71.8130, Gallons
00145xxxx, 12/02/2024, 25.4338, Gallons
00145xxxx, 12/03/2024, 23.9377, Gallons
The water_fill Django management command imports this file into the database:
$ python3 manage.py water_fill
Created: Wednesday, March 26, 2025 (2025-03-26) [18.7013 gallons]
Created: Thursday, March 27, 2025 (2025-03-27) [23.1896 gallons]
Created: Friday, March 28, 2025 (2025-03-28) [43.387 gallons]
Created: Saturday, March 29, 2025 (2025-03-29) [35.9065 gallons]
Created: Sunday, March 30, 2025 (2025-03-30) [35.1584 gallons]
Created: Monday, March 31, 2025 (2025-03-31) [56.1039 gallons]
Total: 6
Done.The water_weekend Django management command compares water usage on
weekdays vs. weekends:
$ python3 manage.py water_weekend
From: Thursday, September 15, 2022 (2022-09-15)
To: Thursday, April 17, 2025 (2025-04-17)
Weekdays: 22,605.3836 gallons / 674 week days = average 33.5391 gallons over 1 year, 10 months.
Weekends: 14,608.7073 gallons / 267 weekend days = average 54.7143 gallons over 8 months, 3 weeks.
Total: 37,214.0909 gallons / 941 days = average 39.5474 gallons over 2 years, 6 months.Highcharts and DataTables are rendered using the JSON data from the Django REST Framework read-only API endpoint for each utility: