Enhanced Places API and Data Handling Techniques

2 min read

📅 2025-08-25 — Session: Enhanced Places API and Data Handling Techniques

🕒 22:35–22:50
🏷️ Labels: Places Api, Data Cleaning, Google Cloud, Csv Handling, Python
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to refine the handling of Google Cloud’s Places API and improve data manipulation techniques for restaurant datasets.

Key Activities

  • API Management: Adjusted the field mask and flatten logic for the Places API v1 by replacing places.placeId with places.name and deriving Place IDs accordingly.
  • API Usage Optimization: Explored SKU tiers in Google Cloud’s Places API to understand billing impacts and optimize API usage.
  • Data Loading and Cleaning: Loaded a CSV file of Buenos Aires restaurant data into a Pandas DataFrame, displaying initial data insights and performing data cleaning to address missing values.
  • CSV Data Retrieval: Provided guidance on field masking for CSV data retrieval to ensure completeness of desired fields.

Achievements

  • Successfully adjusted API field masks and flatten logic for improved data retrieval.
  • Enhanced understanding of Google Cloud API billing and usage strategies.
  • Completed initial data loading and cleaning of restaurant datasets, improving data quality.

Pending Tasks

  • Further refine API usage strategies to minimize costs while maximizing data retrieval efficiency.
  • Continue data analysis on the cleaned restaurant dataset to extract actionable insights.

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