Zomato Data Analysis Project 🍽️📊
This repository contains my data analysis project focused on the Zomato dataset, where I explored restaurant trends, ratings, and consumer preferences across different cities. The project includes various analysis techniques, such as sentiment analysis, exploratory data analysis (EDA), and data visualizations.
Project Overview: Goal: To uncover insights into restaurant ratings, popular cuisines, price range versus ratings, and review sentiment analysis. Tools & Technologies: Python: Pandas, Matplotlib, Seaborn, and Numpy for data manipulation and visualization Natural Language Processing (NLP): Sentiment analysis on customer reviews
Key Insights: Analyzed the relationship between restaurant price range and customer ratings, revealing unexpected patterns. Identified top cuisines in major cities and compared regional preferences. Performed sentiment analysis on reviews to gain insights into customer experiences, identifying frequent words in positive and negative feedback.
What’s Included: Data Preprocessing: Cleaning, transforming, and exploring the dataset. Visualizations: Multiple charts showing trends, ratings distributions, and sentiments. Code: Python scripts and Jupyter notebooks of steps taken during the analysis.
