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Flight Data Analysis and Visualization Using Aviationstack API
Date
April 2023
Google Colab
School Coding Project
In this project, I developed a Python program to track flights between specific airports, leveraging the Aviationstack API for real-time data. The project involved collecting and processing flight information, then visualizing key insights through data analysis and visualization.
Objective: To create a tool that tracks flights from one airport to another in real-time using Aviationstack API data. The goal was to provide a comprehensive summary of flight frequency by airline, time of day, and current status, providing valuable insights into flight patterns.
Data Collection and Methodology
Data Source: The program used the Aviationstack API to retrieve real-time flight data, requiring a user-provided API key and departure/arrival airport codes.
Process:
The program requests data based on the chosen departure and arrival airports.
Data is saved in a text file, which is then processed to extract necessary information for visualization.
Visualizations and Key Insights
Flight Frequency by Airline:
Visualization: A bar chart showing the number of flights per airline.
Insight: This chart highlights which airlines have the most flights on the chosen route, valuable for understanding airline traffic on specific routes.
Flights by Time of Day:
Visualization: A bar chart displaying flight frequency at different times.
Insight: This graph shows peak flight times, indicating when flights are most frequent during the day.
Flight Status Distribution:
Visualization: A bar chart indicating the number of flights by current status (e.g., scheduled, in-flight, delayed).
Insight: Helps to understand operational reliability by showing the status of flights on the chosen route at a glance.
Technical Challenges and Solutions
Data Extraction: Parsing JSON responses from the API and filtering relevant information.
API Integration: Handling potential API limits and ensuring stable data retrieval.
Data Visualization: Cleaning and structuring data from the text file output to produce accurate and meaningful visualizations.
Tools and Technologies Used
Languages & Libraries: Python, Matplotlib (for visualizations), and the Aviationstack API.
Platform: Google Colab for code execution and visualization.
Learning Outcomes
Strengthened API integration skills, learned to handle and visualize real-time data, and improved my ability to extract insights from large datasets.
