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Excel · Data Analysis

Swiggy Food
Analysis Dashboard

An interactive Excel dashboard analyzing customer preferences, restaurant distribution, delivery performance, and pricing — transforming raw Swiggy food delivery data into actionable insights.

🛠️ Microsoft Excel 📊 Pivot Tables 📁 Data Analysis 🍔 Food Delivery
Swiggy Food Analysis Dashboard · Microsoft Excel

Project Overview &
Problem Statement

The Swiggy Food Analysis Dashboard is an interactive data analysis project built using Microsoft Excel. It provides insights into customer preferences, restaurant distribution, delivery performance, pricing, and ratings across different cities.

Food delivery platforms generate large volumes of data, but raw data is difficult to interpret. Key challenges include identifying popular food categories, understanding delivery time differences across cities, analyzing pricing variations by area, and evaluating customer ratings and service quality.

The objective was to analyze restaurant distribution by food category, understand customer preferences, evaluate delivery time across cities, compare pricing across areas, and analyze ratings across cities — all within a clean, interactive Excel dashboard.

Project Details
Category Data Dashboard
Tool Microsoft Excel
Data Prep Pivot Tables · Data Cleaning
Domain Food Delivery
Filters City · Food Category
Source Files GitHub →

Project at a Glance

🍽️
10+
Food Categories
🏙️
5
Cities Analyzed
📊
5
Chart Visualizations
🧩
3
Deliverables

Key Insights

01
South Indian is the Most Popular Category
South Indian food tops the popularity chart across all categories, reflecting strong regional cuisine demand on the Swiggy platform in analyzed cities.
02
Indian & North Indian Cuisines in High Demand
Indian and North Indian cuisines closely follow South Indian food in customer preference, indicating a dominant appetite for traditional comfort foods.
03
Kolkata Has Higher Delivery Times
Kolkata consistently shows higher average delivery times compared to other cities, pointing to potential logistical challenges or higher order volumes in that market.
04
Pricing Varies Significantly by Area
Average pricing across different areas shows considerable variation, revealing opportunities for location-specific pricing strategies and targeted promotions.
05
Hyderabad Leads in Customer Ratings
Hyderabad records the highest average customer ratings among all cities, suggesting superior service quality, faster delivery, or better restaurant partnerships in the region.
06
Restaurant Distribution Reflects Food Trends
The donut chart distribution of restaurants by food type closely mirrors customer preferences, validating that Swiggy's supply aligns with market demand across cuisine segments.

Tools & Technologies

📗 Microsoft Excel
📊 Pivot Tables
🍩 Donut Charts
🥧 Pie Charts
📉 Column Charts
📊 Bar Charts
🧹 Data Cleaning
🔧 Missing Value Handling

Key Features

🍩
Restaurant Count by Food Type
A donut chart visualizes the distribution of restaurants across food categories, making it easy to spot which cuisines dominate the platform.
🥧
Popularity by Food Category
A pie chart breaks down customer preference percentages by food category, highlighting the most ordered and most loved cuisine types.
📈
Avg. Delivery Time by City
A column chart compares average delivery times across cities, providing a clear picture of operational efficiency and logistics performance city-by-city.
💰
Avg. Price by Area
A bar chart contrasts average food pricing across different areas, helping identify premium zones and budget-friendly markets within the dataset.
Avg. Ratings by City
A bar chart ranks cities by average customer ratings, revealing which cities deliver the best overall food and service experience on Swiggy.
🧹
Data Cleaning & Preparation
Raw Swiggy data was cleaned, missing values handled, and Pivot Tables used to restructure the dataset before building the final interactive dashboard.

Dataset Information

The dataset is based on Swiggy food delivery data, preprocessed using Microsoft Excel with data cleaning techniques and Pivot Tables to enable meaningful analysis and visualization.

Data fields included:

  • Food categories and cuisine types
  • Restaurant details and distribution
  • Delivery time metrics per city
  • Pricing information by area
  • Customer ratings across cities
  • City and area-level geographic data
📁 Project Files — via GitHub
📗
swiggy-data-insights-dashboard.xlsx
Excel Dashboard File
GitHub
📑
swiggy-data-insights-presentation.pptx
PowerPoint Presentation
GitHub
📄
swiggy-data-insights-report.pdf
Project Report (PDF)
GitHub

All files hosted on GitHub — click any row to download.

Takeaway

This dashboard converts raw Swiggy food delivery data into meaningful insights, helping food businesses and platform operators understand market dynamics and customer behavior. By leveraging Excel's Pivot Tables and chart capabilities, it demonstrates how data visualization techniques can bridge the gap between raw operational data and strategic decisions — from city-level delivery optimization to cuisine-specific targeting and customer satisfaction improvement.

Interested in
collaborating ?

Feel free to reach out for feedback, collaboration, or any data analytics opportunities.