Project – 15 (with Dashboard) | Q-Commerce Data Analysis | Python Coding for Data Science
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Ever wondered how apps like Blinkit, Zepto, Swiggy Instamart, Dunzo, JioMart, BigBasket, Amazon Now actually work behind the scenes?
How do they decide delivery times?
Why do some platforms get better ratings?
Which cities bring the most revenue?
Do discounts really help business growth?
👉 In this video, you’ll discover the answers through a full end-to-end Data Analytics project using Python.
This is Project-15 of my 100 Real-World Data Analytics Projects Playlist, where I build projects that go beyond theory and simulate real industry-level work.
🚀 What makes this project different?
✅ Understanding messy real-world data
✅ Cleaning missing values & outliers properly
✅ Performing Exploratory Data Analysis (EDA)
✅ Asking real business questions
✅ Creating powerful visualizations
✅ Building a full KPI Dashboard in Python
✅ Extracting meaningful business insights
If you’re serious about becoming a Data Analyst or Data Scientist, this is exactly the kind of project you should be building.
📌 What you’ll learn in this video
By the end of this project, you will understand:
✔ How to clean real-world datasets using Pandas
✔ How to handle missing values like a professional analyst
✔ How to detect and treat outliers correctly
✔ How to perform Exploratory Data Analysis (EDA)
✔ How to visualize data using Matplotlib & Seaborn
✔ How to convert charts into real business insights
✔ How to build a dashboard using only Python
✔ How to structure portfolio-ready projects
✔ How to think like a Data Analyst, not just a coder
These are exactly the skills recruiters look for in Data Analyst & Data Science roles.
🧠 Who should watch this?
This video is perfect for:
🎯 Beginners learning Data Analysis
🎯 Students building Data Science projects
🎯 Anyone preparing for Data Analyst interviews
🎯 Python learners who want real project experience
🎯 People building a strong GitHub / portfolio
🎯 Anyone doing Kaggle projects
🎯 Professionals transitioning into analytics
If you’re watching this, you’re already ahead of 90% of learners.
🛠 Tools used: Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, Plotly.
📌 Watch till the end to see the final dashboard and insights!
If you find this project helpful:
👍 Like the video
📌 Subscribe for more Real Python Projects
💬 Comment "Project" if you want the dataset and notebook
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You must check our other Data Analytics Projects :
Project 14 - • Project – 14 (with Dashboard) | Salary Dat...
Project 13 - HR Data Analytics - • Real Project – 13 | HR Data Analysis | Pyt...
Project 12 - AI Market Financial Data Analysis - • Real Project – 12 | AI' Financial Market D...
Project 11 - Airlines' Flights Data Analysis - • Analyse Airlines' Flights Dataset like a P...
Project 10 - Spotify-YouTube Data Analysis - • Project - 10 | Data Analysis with Python |...
Project 9 - • Analyse Sales Data like a Pro with Python ...
Project 8 - • Project - 8 | Data Analysis with Python | ...
Project 7 - • Project - 7 | Data Analysis with Python | ...
Project 6 - • Project - 6 | Data Analysis with Python | ...
Project 5 - • Project - 5 | Data Analysis with Python | ...
Project 4 - • Project - 4 | Data Analysis with Python | ...
Project 3 - • Project - 3 | Data Analysis with Python | ...
Project 2 - • Project - 2 | Data Analysis with Python | ...
Project 1 - • Project - 1 | Data Analysis with Python | ...
ut11amfri
#python #dataanalytics #datascience #project
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