Point-of-Sale transactions for an independent coffee shop in Sonora

Dataset: Independent Coffee Shop Transactions (Hermosillo, 2026)1. Overview This dataset contains anonymized, item-level transaction records from an independent coffee shop located in Hermosillo, Sonora. The data covers sales from January 1st, 2025, through May 11th 2026. The goal of this dataset is to provide high-fidelity retail data for analysis of consumer behavior, product popularity, and peak business hours.2. MethodologyThe dataset was created using an automated ETL (Extract, Transform, Load) pipeline written in Python.A. Data Acquisition (Extraction) Source: Data was extracted via the official Loyverse POS REST API (v1.0). Timeframe: The extraction was scoped to the year 2025 and the ongoing 2026. Timezone Handling: The business operates in MST (UTC-7). The extraction script explicitly converted the local start date (2025-01-01 00:00 MST) to its UTC equivalent (2025-01-01 07:00 UTC) to satisfy API requirements while ensuring a complete local year snapshot. B. Data Cleaning & Transformation Flattening: The raw JSON response was "exploded" from a receipt-centric view to a line-item-centric view. Each row represents a single item sold. Categorization: Customizations (modifiers) such as flavors, milk types, and add-ons were collapsed into a single pipe-separated string to maintain a "Tidy Data" format. Localization: Timestamps were converted from UTC back to Arizona Time (America/Phoenix) to reflect actual local business hours. Encoding: The file was saved using UTF-8-SIG to preserve Spanish language accents (e.g., "Té de burbujas") and ensure compatibility with Microsoft Excel. C. Anonymization (Ethics & Privacy) To protect customer and business privacy: All Personally Identifiable Information (PII) including Customer Names, Emails, and Employee IDs were programmatically excluded during the transformation stage. Internal database UUIDs for variants and stores were removed. Only the human-readable item names and transaction timestamps remain. 3. Data Dictionary (Column Descriptions) receipt_no: A unique transaction ID. timestamp: The date and time of the sale (UTC-7). item_name: The primary product sold. variant: The size or specific version of the product. modifiers: Customizations including flavors and milk types, separated by a pipe (|). quantity: Number of units sold in that transaction. total_item_price: The total price paid for that item. source: The origin of the sale (e.g., "point of sale").