Zomato_Analysis
RoleData Analytics
Year2026
Project Details
this project analyses Zomato restaurant data to uncover key insights into customer preferences, restaurant performance, and market trends. The analysis includes data cleaning, exploratory data analysis (EDA), and visualization to study factors such as ratings, location, cuisine types, online delivery, and cost for two. The goal is to identify patterns that help understand customer behavior and support data-driven business decisions for restaurant strategy and market positioning.
Skills
Data AnalyticsContent AnalysisData WranglingExploratory Data AnalysisData VisualizationInsight GenerationMarket Trend Analysis
Tools
PythonNumPyPandasSeabornMatplotlib
- This project performs Exploratory Data Analysis (EDA) on a large Zomato dataset containing 2,11,000+ restaurant records across multiple Indian cities.
- The dataset includes information such as restaurant name, city, locality, cuisines, price range, ratings, votes, delivery, table booking, and cost for two.
- Python libraries Pandas, NumPy, Matplotlib, Seaborn, and WordCloud were used for data cleaning, analysis, and visualization.
- Initial steps involved loading the dataset, inspecting its structure, data types, and generating descriptive statistics.
- Duplicate records were removed to ensure data consistency.
- Missing values were handled by filling them with the mode of respective columns.
- City-wise and locality-wise analysis was performed to identify areas with the highest concentration of restaurants.
- Visualizations were created to analyze:
- Additional analysis identified top restaurant chains, average ratings by city, and unique cuisines per city.
- A word cloud was generated to visualize the most common cuisines preferred by customers.
- Overall, the project provides insights into customer preferences, pricing impact, service availability, and restaurant performance across India.
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