Flight Dashboard || SQL+Python+Streamlit Project

Flight Analytics Dashboard Project Walkthrough
Welcome to my detailed walkthrough of the Flight Analytics Dashboard! This project leverages Python, MySQL, and Streamlit to provide comprehensive insights into flight data.
📋 Project Overview:
Check Flights: Easily find detailed information about flights between selected cities.
Price Distribution: Explore average flight prices across different airlines with visual representations.
Flight Frequency per Airline: See how many flights each airline operates.
Average Flight Duration per Airline: Analyze the average duration of flights for various airlines.
Peak Departure Times: Identify the busiest times for flight departures.
Price Trends by Time of the Day: Understand how flight prices change throughout the day.
🔧 Technologies Used:
Python
MySQL
Streamlit
Plotly
📂 Resources:
GitHub Repository: [github.com/adi...]
Datasets: [www.kaggle.com...]
In this video, I’ll guide you through the key features of the dashboard, explain the technologies used, and show you how to navigate and interpret the data visualizations.

[@rameshbabuk6357]

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[@Techify_Tutorials]

You could find a lot of videos on TH-cam related to streamlit.