Weather Reports

Weather forecasting using automated API calls, SQLite, Python.

Overview

At Avenue Road, I was responsible for aggregating and analyzing historical and forecast weather data using Python and SQLite. My work involved automating API calls and utilizing Selenium for web scraping to collect weather data, structuring it in a database, and generating weekly reports with detailed weather and snow forecasts. These reports played a key role in data-driven decision-making for clients.

Key Responsibilities

  • Automated Data Collection
    • Integrated multiple weather APIs to fetch historical and forecast data.
    • Utilized Selenium to scrape weather-related data from websites when APIs lacked specific information.
    • Scheduled automated API calls and web scraping tasks using Python scripts, ensuring up-to-date data.
    • Processed, cleaned, and stored data in an SQLite database for structured analysis.
  • Database Management & Analysis
    • Maintained a database of thousands of weather records, ensuring consistency and reliability.
    • Designed optimized SQL queries for efficient data retrieval and analysis.
    • Used Pandas and NumPy to process weather data, identify trends, and generate insights.
  • Forecast Reporting & Insights
    • Produced 8 detailed weather forecasts per month, including snow accumulation, temperature trends, and precipitation probabilities.
    • Delivered data-driven reports that supported client planning and operational decisions.
    • Used Matplotlib and Seaborn to visualize weather trends, making forecasts more actionable.

Technologies Used

  • Python – Data collection, processing, and automation.
  • Selenium – Web scraping for weather data extraction.
  • APIs – Automated retrieval of forecast and historical weather data.
  • SQLite – Structured storage of weather records.
  • Pandas / NumPy – Data manipulation and statistical analysis.
  • Matplotlib / Seaborn – Data visualization for trend analysis.
  • Scheduling (e.g., Cron Jobs, Task Scheduler) – Automating data retrieval and report generation.

Impact & Achievements

✅ Enabled data-driven decision-making for clients through accurate and timely weather forecasts.
✅ Maintained a reliable weather database with thousands of records for continuous analysis.
✅ Automated API calls and web scraping, reducing manual effort and improving data collection efficiency.

This project strengthened my expertise in data engineering, web scraping, API integration, and predictive analysis, providing valuable insights for weather-dependent decision-making.