This repository contains an in-depth exploratory data analysis (EDA) on flight ticket and Zomato delivery data. The analysis aims to uncover valuable insights and patterns in these domains using Python and popular data analysis libraries numpy, pandas, matplotlib, seaborn

1.Flight Ticket Analysis: Explore the dataset of flight ticket information, including prices, destinations, airlines, and more. Gain insights into pricing trends, popular destinations, and airlines' market share.

2.Zomato Delivery Analysis: Investigate the Zomato delivery dataset, examining factors such as restaurant ratings, delivery times, customer reviews, and geographical distribution. Discover patterns related to food preferences, customer satisfaction, and delivery efficiency.

3.Data Visualization: Utilize data visualization techniques to present findings effectively. Used libraries such as Matplotlib and Seaborn to create meaningful visual representations, including plots, charts.

4.Jupyter Notebooks: Access Jupyter Notebooks that provide step-by-step code and explanations for each analysis. Reproduce the results, explore alternative approaches, and adapt the code to your specific needs.

By exploring this repository, you can gain valuable insights into flight ticket trends and Zomato delivery patterns, enabling better decision-making and deeper understanding of these domains.

Feel free to contribute, suggest improvements, or utilize the analysis as a starting point for your own projects. Happy exploring!