Food Delivery App Data Analysis using Python | Real-World Logistics Analytics

In this video, we perform end-to-end Data Analysis on a Food Delivery / Logistics dataset using Python & Pandas 📊🍔 CODE USED IN VIDEO 👇 import pandas as pd data = { "Order_ID": [1,2,3,4,5,6,7], "Order_Date": pd.to_datetime([ "2024-01-05","2024-01-06","2024-01-07", "2024-01-08","2024-01-09","2024-01-10","2024-01-11" ]), "City": ["Delhi","Delhi","Mumbai","Pune","Mumbai","Delhi","Pune"], "Delivery_Partner": ["Zomato","Swiggy","Zomato","Swiggy","Zomato","Zomato","Swiggy"], "Distance_km": [5.2, 8.5, 3.1, 6.4, 4.8, 10.2, 5.5], "Delivery_Time": [30,45,25,40,35,50,28], "Order_Value": [450, 700, 380, 520, 600, 800, 420], "Rating": [4.5,3.8,4.7,4.0,4.2,3.5,4.6] } This is a real-world case study, exactly the kind of analysis companies expect from Data Analysts, Business Analysts, and Data Scientists in interviews. 🚀 What you’ll learn in this video: ✔ How to analyze food delivery performance data ✔ City-wise delivery time & rating analysis ✔ Relationship between delivery speed and customer ratings ✔ Identifying poor service orders using data ✔ Finding best-performing cities using Pandas ✔ How to think like an analyst, not just write code 🧩 Tools & Concepts Used: Python Pandas GroupBy & Aggregations Correlation Analysis Real-world business questions Interview-oriented analytics approach 🎯 Why this video is important: ✅ Highly interview-relevant ✅ Based on real industry-like dataset ✅ Perfect resume project ✅ Ideal for beginners to intermediate learners ✅ Shows problem-solving mindset, not just syntax If you are preparing for: Data Analyst interviews Business Analyst roles Product / Operations analytics Python for Data Analysis 👉 This project is a MUST-WATCH. 📌 Dataset & code discussion included step-by-step 📌 Easy explanations in Hinglish 📌 Practical learning, no theory overload Here you will learn the new-edge technologies like Data Science, Machine Learning, SQL, Python, Power BI, Tableau, and other modern tools in the most easy, simple, and interactive way. My mission is to make complex concepts super simple so that even beginners can understand and professionals can revise quickly. Python Programming – from beginner to advanced with real-world projects. SQL (Structured Query Language) – Queries, Joins, Subqueries, Window Functions, and all important concepts for interviews and job readiness. Pandas & NumPy – Data analysis libraries explained step-by-step with datasets that are relatable to Indian and global contexts. Data Visualization – Using Matplotlib, Seaborn, and Plotly to create impactful charts and dashboards. Power BI & Tableau – Business Intelligence tools for building interactive dashboards and reports. Machine Learning Basics – Regression, Classification, Clustering explained in an easy and practical way. Interview Preparation – Real interview questions, mock interview problems, and answers explained so you can crack your dream job.