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Project Overview:

Flight Delays and Cancellations Analysis using Power BI & Python

Here we provide a comprehensive Power BI dashboard project centered around analyzing flight delays and cancellations using the 2015 Flight Delays and Cancellations dataset sourced from Kaggle. The dataset retrieval process was automated through a Python script leveraging the Kaggle API to ensure real-time data updates.

Data Preparation:

Collected the 2015 Flight Delays and Cancellations dataset from Kaggle, Used a Python script to fetch and maintain the dataset in a designated folder Cleaned the dataset using Power Query within Power BI. [Python Script]Python Script

Data Modeling and Analysis:

Created a robust data model within Power BI to facilitate in-depth analysis. Developed DAX measures to enhance data analysis capabilities. Visualized data insights using advanced features of Power BI. [Data Model]Data model

Dashboard:

Overview Dashboard: Provides a holistic view of airlines, airports, total flights, flight distribution by airline and airport, and monthly flight and cancellation trends. Includes interactive filters for enhanced user experience.

[Overview Dashboard]Overview Dashboard

Cancellation Analysis Dashboard:

Analyzed cancellation flights with a focus on cancellation percentages, reasons for cancellations, and trends over months. Visualized data through charts depicting cancellation flights by airport and reasons. [Cancellation Report] Cancellation

Delay Analysis Dashboard:

Explored average arrival and departure delays monthly. Calculated average delay times for each airport and identified the top 5 airports with the highest departure delays. [Delay Flights] delay

Airlines Analysis Dashboard:

Delved into airlines' departure and arrival delay times. Number of diverted flights and how it is distributed over airlines. Created a detailed breakdown of delay times for each airline. [Airline Delay Report] Airlinr

Geospatial Map Dashboard:

Utilized a map chart to geolocate US airports and visualize flight volumes for each location. [Map] Map This project showcases the power of Power BI in transforming raw data into actionable insights, offering a deep dive into the complexities of flight operations and delays.

Project File

here is the pbix file, feel free to download it on your locl device to interact with it.
https://1drv.ms/u/c/2fadf0e7763a5ead/EcYRbZ-xhZFHn2ptNGR5Z-EBV_0Fm9DoFFRQLP4jlGMPjA?e=6gcHU9

Feel free to contact me for any info

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Using Python and Power BI to analyze air flights dataset from Kaggle

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