https://github.com/ericoc/utilities
Philadelphia (electrical, natural gas, and water) utilities usage graphs and tables!
https://github.com/ericoc/utilities
analytics datatables django django-rest-framework drf highcharts javascript openpyxl philadelphia philly python python3 utilities
Last synced: about 1 year ago
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Philadelphia (electrical, natural gas, and water) utilities usage graphs and tables!
- Host: GitHub
- URL: https://github.com/ericoc/utilities
- Owner: ericoc
- Created: 2024-12-12T01:55:26.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-30T03:39:02.000Z (about 1 year ago)
- Last Synced: 2025-03-30T04:24:35.305Z (about 1 year ago)
- Topics: analytics, datatables, django, django-rest-framework, drf, highcharts, javascript, openpyxl, philadelphia, philly, python, python3, utilities
- Language: JavaScript
- Homepage: https://utilities.ericoc.com/
- Size: 5.52 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
Awesome Lists containing this project
README
# Utilities
The Philadelphia electrical, natural gas, and water utilities websites each
allow for a residential account holder to access (and export!) their own usage
data.
## Electric
### Pennsylvania Electric Company ("PECO")
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](https://secure.peco.com/MyAccount/MyBillUsage/Pages/Secure/GreenButtonConnectDownloadMyData.aspx)"
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 does some calculations based
upon the data to compare 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 ago]
> To: Sun Jan 19 23:00:00 2025 (2025-01-19 23:00:00-05:00) [4 days, 22 hours ago]
> Weekdays: 8,075.9400 total kWh / 12,480 total hours = average 0.6471 kWh over 1 year, 5 months.
> Weekends: 3,655.5800 total kWh / 5,015 total hours = average 0.7289 kWh over 6 months, 3 weeks.
> Total: 11,731.5200 kWh / 17,495 hours = average 0.6706 kWh over 1 year, 11 months.
> ```
## Natural Gas
### Philadelphia Gas Works ("PGW")
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](https://myaccount.pgworks.com/portal/usages.aspx?type=GU)"
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 `gas_fill` Django management command imports this file into the database:
> ```
> $ python3 manage.py natural_gas_fill
> (venv) ➜ eric@pro:~/code/utilities git:(main) ✗ $ python3 manage.py natural_gas_fill
> 1 spreadsheet(s) found.
> ...
> Created: Saturday 2025 (2025-03-01) [33.0 CCF]
> Total: 1
> Done.
> ```
## Water
#### Philadelphia Water Department ("PWD")
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](https://secure8.i-doxs.net/CityOfPhiladelphiaWRB/Secure/Usage.aspx)"
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 does some calculations based
upon the data to compare water usage on weekdays vs. weekends:
> ```
> $ python3 manage.py water_weekend
> From: Thursday, September 15, 2022 (2022-09-15)
> To: Tuesday, February 04, 2025 (2025-02-04)
> Weekdays: 20,831.0039 gallons / 622 week days = average 33.4904 gallons over 1 year, 8 months.
> Weekends: 13,859.1591 gallons / 247 weekend days = average 56.1100 gallons over 8 months.
> Total: 34,690.1630 gallons / 869 days = average 39.9196 gallons over 2 years, 4 months.
> ```
## API
Highcharts and DataTables are displayed using the JSON data from Django REST
Framework endpoints for each data set:
- Electric: [`https://utilities.ericoc.com/api/electric/`](https://utilities.ericoc.com/api/electric/)
- Natural Gas: [`https://utilities.ericoc.com/api/natural_gas/`](https://utilities.ericoc.com/api/natural_gas/)
- Water: [`https://utilities.ericoc.com/api/water/`](https://utilities.ericoc.com/api/water/)