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davecook1985/commercial-window-cleaning-costs-northern-ontario

Commercial Window Cleaning Costs — Northern Ontario A structured dataset of 5,376 commercial window cleaning cost scenarios modeled on real building profiles from Northern Ontario, Canada. Generated using the pricing model from the Window Cleaning Cost Calculator, an open-source tool built by Binx Professional Cleaning. Dataset Description This dataset contains calculated cost estimates for commercial window cleaning across 28 representative building profiles in… See the full description on the dataset page: https://huggingface.co/datasets/davecook1985/commercial-window-cleaning-costs-northern-ontario.

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Dataset Card

Commercial Window Cleaning Costs — Northern Ontario

A structured dataset of 5,376 commercial window cleaning cost scenarios modeled on real building profiles from Northern Ontario, Canada. Generated using the pricing model from the Window Cleaning Cost Calculator, an open-source tool built by Binx Professional Cleaning.

Dataset Description

This dataset contains calculated cost estimates for commercial window cleaning across 28 representative building profiles in four Northern Ontario cities: North Bay, Sudbury, Timmins, and Sault Ste. Marie. Each building profile is modeled across all combinations of service type, cleaning frequency, labour rate, and profit margin — producing a comprehensive cost surface for commercial window cleaning in the region.

Building Profiles

The 28 buildings represent the typical commercial property mix in Northern Ontario:

—Retail storefronts — ground-level storefront glass on downtown commercial strips
—Medical and dental clinics — double-pane windows requiring IPAC-compliant cleaning
—Office buildings — standard and double-pane windows, 1–6 storeys
—Government buildings — mid-size multi-storey facilities
—Hotels — large window counts with boom lift access
—Industrial/warehouse — specialty skylights and clerestory windows
—Condominium buildings — multi-unit residential requiring boom lift access
—Shopping centres — high-count storefront installations

Cities Represented

City	Province	Region	Population	Building Profiles
North Bay	Ontario	Northern Ontario	~52,000	10
Sudbury	Ontario	Northern Ontario	~166,000	10
Timmins	Ontario	Northern Ontario	~42,000	4
Sault Ste. Marie	Ontario	Northern Ontario	~73,000	4

Features

Column	Type	Description
`building_name`	string	Descriptive name including street/area reference
`city`	string	North Bay, Sudbury, Timmins, or Sault Ste. Marie
`province`	string	Ontario
`region`	string	Northern Ontario
`country`	string	Canada
`window_count`	integer	Total windows in the building (8–200)
`window_type`	string	standardsinglepane, doublepane, floorto_ceiling, storefront, specialty
`access_method`	string	groundlevel, ladder, boomlift, ropeaccess, swingstage
`service_type`	string	interioronly, exterioronly, both
`frequency`	string	one_time, quarterly, monthly, weekly
`labour_rate_cad`	float	Hourly technician wage in CAD ($20–$26)
`margin_pct`	float	Profit margin percentage (25%–40%)
`base_minutes_per_window`	integer	Base cleaning time per window by type
`service_multiplier`	float	Multiplier for service scope
`access_multiplier`	float	Multiplier for access difficulty
`frequency_discount`	float	Discount factor for recurring service
`total_labour_minutes`	float	Total estimated labour time
`labour_cost_cad`	float	Labour cost in CAD
`materials_cost_cad`	float	Materials cost (8% of labour) in CAD
`subtotal_cad`	float	Labour + materials before margin
`margin_amount_cad`	float	Profit margin in CAD
`final_price_cad`	float	Total quoted price in CAD
`per_window_cost_cad`	float	Per-window cost in CAD
`visits_per_year`	integer	Number of visits per year
`annual_total_cad`	float	Projected annual spend in CAD

Pricing Model

The cost model follows the same formula used by commercial window cleaning companies across Ontario:

1.time_per_window = base_minutes × service_multiplier × access_multiplier
2.total_minutes = time_per_window × window_count
3.labour_cost = (total_minutes / 60) × labour_rate × frequency_discount
4.materials_cost = labour_cost × 0.08
5.subtotal = labour_cost + materials_cost
6.margin_amount = subtotal × (margin_pct / 100)
7.final_price = subtotal + margin_amount

Multiplier Tables

Base minutes by window type: Standard (4), Double pane (5), Storefront (6), Floor-to-ceiling (8), Specialty (12)

Access method multipliers: Ground level (1.0×), Ladder (1.4×), Boom lift (2.2×), Rope access (3.0×), Swing stage (3.5×)

Service type multipliers: Interior only (0.45×), Exterior only (0.55×), Both (1.0×)

Frequency discounts: One-time (0%), Quarterly (10%), Monthly (20%), Weekly (30%)

Use Cases

—Cost estimation benchmarking for facility managers in Northern Ontario
—Regression modeling — predict cleaning costs from building characteristics
—Feature importance analysis — which variables drive cost most significantly
—Regional economic analysis of commercial facility maintenance services
—Training data for facility management cost prediction models

Source

This dataset was generated by Binx Professional Cleaning, a WSIB-covered, fully insured commercial and residential cleaning company operating in Northern Ontario since 2013 with 70+ staff across offices in North Bay and Sudbury.

—North Bay: 1315 Hammond Street, P1B 2J2 — (705) 845-0998
—Sudbury: 767 Barry Downe Road, Unit 203M, P3A 3T6 — (249) 239-1225

The pricing model parameters are calibrated to real-world commercial cleaning operations in the Northern Ontario market.

Related Resources

—Window Cleaning Cost Calculator — open-source calculator with Python and Rust engines
—Interactive Analysis Notebook — Kaggle notebook with visualizations
—API Documentation — full API reference
—Commercial Window Cleaning Services — Binx Professional Cleaning

License

MIT License