saraNour/compliments-reference-phase1

Phase 1 — Data Quality Foundation

Compliments Reference DB Pipeline

Version: 2.0.0 Date: 2026-07-30 Status: PASS

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Purpose

Phase 1 is the data quality foundation of the pipeline. It loads the authoritative Compliments product dataset, performs comprehensive data quality checks, cleans string fields, validates key fields, and produces a clean output with full traceability (raw + cleaned columns).

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Authoritative Input

Property	Value
Source	saraNour/compliments-brand/source_of_truth/products.parquet
URL	https://huggingface.co/datasets/saraNour/compliments-brand/blob/main/source_of_truth/products.parquet
Type	HuggingFace dataset (private)
Original Source	Voila.ca (Loblaw) Compliments private-label products
Row Count	4,440
Column Count	16

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What Phase 1 Does

1. Schema Validation

• Validates column names, types, and row count
• Checks for unexpected changes from baseline

2. Raw Data Audit

• Null audit for every column
• Duplicate audit: full rows, external_id, upc, title+size+brand
• Price anomaly detection (negative, zero, >$100)
• UPC format validation (12-14 digits)
• 100% null column detection

3. Data Cleaning (NEW in v2.0.0)

• String normalization: Trim whitespace, collapse multiple spaces, empty strings → null
• Brand cleaning: Normalizes casing and whitespace (e.g., COMPLIMENTS → Compliments)
• Title cleaning: Normalizes casing and whitespace
• UPC validation: Format check, null audit, reused-UPC analysis
• External ID validation: Uniqueness check, null audit

4. Output Generation

• Produces cleaned output with raw + cleaned columns for traceability
• Documents all dropped columns with reasons
• Generates validation report, statistics, and provenance

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Phase 1 Does NOT

• Normalize brands semantically (Phase 2)
• Extract identity attributes (Phase 2)
• Classify food/non-food (Phase 3)
• Perform any grouping (Phase 3)
• Use any external data sources beyond the authoritative input

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Output Schema

The Phase 1 output (phase1_output.parquet) contains 20 columns:

#	Column	Type	Description
1	upc	str	Universal Product Code (1 null, 3,271 unique)
2	external_id	str	Voila retailer product ID (4,440 unique)
3	brand	str	Original brand string (11 variants)
4	title	str	Original product title
5	price	float64	Price in CAD
6	price_currency	str	Always "CAD"
7	size	str	Raw size string (631 unique)
8	size_amount	float64	Parsed numeric amount (307 nulls)
9	size_unit	str	Parsed unit: g, kg, ml, l, count (307 nulls)
10	size_qty	int64	Quantity multiplier (usually 1)
11	size_unit_norm	str	Normalized unit (307 nulls)
12	image_url	str	Product image URL
13	source	str	Always "voila"
14	source_url	str	Product page URL
15	brand_clean	str	Cleaned brand (whitespace/case normalized)
16	brand_raw	str	Original brand (for traceability)
17	title_clean	str	Cleaned title (whitespace normalized)
18	title_raw	str	Original title (for traceability)
19	upc_raw	str	Original UPC (for traceability)
20	external_id_raw	str	Original external_id (for traceability)

Dropped Columns

Column	Reason
size_per_unit	100% null (4,440/4,440 values are NaN)
size_total	100% null (4,440/4,440 values are NaN)

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Validation Results

Check	Result
Row count = 4,440	PASS
Column count = 16 (input) → 20 (output)	PASS
Column names match expected	PASS
Full row duplicates = 0	PASS
external_id duplicates = 0	PASS
Schema validation	PASS
Overall	PASS

Key Metrics

Metric	Value
Total products	4,440
Unique external_ids	4,440
Unique UPCs	3,271
Reused UPCs (same UPC, different products)	1,168
Null UPCs	1
Title+size+brand duplicates	60
100% null columns dropped	2 (size_per_unit, size_total)

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Brand Cleaning Summary

Raw Brand	Cleaned Brand	Count
COMPLIMENTS	Compliments	1
Compliments	Compliments	4,258
Compliments Organic	Compliments Organic	90
Compliments Balance	Compliments Balance	42
Compliments Naturally Simple	Compliments Naturally Simple	25
Sensations	Sensations	8
Compliments Little Ones	Compliments Little Ones	7
Compliments Green Care	Compliments Green Care	5
Compliments Green	Compliments Green	4

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Files

phase1/
    README.md                          # This file
    src/phase1.py                      # Production Python script (v2.0.0)
    notebooks/phase1.ipynb             # Interactive notebook (unexecuted)
    outputs/
        phase1_output.parquet          # Clean output (4,440 rows, 20 cols)
        phase1_provenance.json         # Column provenance documentation
        phase1_executed.ipynb          # Executed notebook with all outputs
    validation/
        phase1_validation.json         # Validation report (PASS)
    statistics/
        phase1_statistics.json         # Data statistics

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How to Run

# Using the Python script
cd /home/sara/gsoc/compliments-reference-db
python -m phase1.src.phase1

# Using the notebook
jupyter notebook phase1/notebooks/phase1.ipynb

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Handoff to Phase 2

Phase 2 must read:

• phase1/outputs/phase1_output.parquet

Phase 2 must use:

• brand_clean for semantic normalization (not brand)
• title (original) for identity extraction (BEFORE normalization)

Phase 2 must NOT:

• Re-download from HuggingFace
• Read from any other source
• Skip Phase 1 validation
• Duplicate cleaning already done in Phase 1