Full Exploratory Data Analysis (EDA) in Python | Sales Data Project for Beginners
Python Data Analysis Project | Exploratory Data Analysis (EDA) in Python | Pandas & Matplotlib Tutorial
In this video, we perform a complete Exploratory Data Analysis (EDA) in Python using a real-world Sales Dataset with Pandas and Matplotlib.
If you want to become a Data Analyst, learning how to perform Exploratory Data Analysis (EDA) is a must-have skill. In this step-by-step Python Data Analysis project, you will learn how professionals clean datasets, explore data, and extract meaningful business insights.
This tutorial is perfect for beginner Data Analysts, students building portfolio projects, and anyone preparing for Data Analyst interviews.
📊 What You Will Learn in This Python Data Analysis Project
✔️ Data Loading & Dataset Overview (.head(), .info(), .describe())
✔️ Checking Data Types
✔️ Handling Missing Values
✔️ Detecting & Removing Duplicate Records
✔️ Feature Engineering (Profit Margin, Month, Year Extraction)
✔️ Grouping & Aggregation with Pandas
✔️ Data Visualization (Bar Charts, Line Charts, Histogram)
✔️ Extracting Business Insights from Sales Data
By the end of this tutorial, you will understand how to perform Exploratory Data Analysis in Python like a professional Data Analyst.
👨💻 Who This Video Is For
✔ Beginner Data Analysts
✔ Python for Data Analysis learners
✔ Students building Data Analyst portfolio projects
✔ Anyone preparing for Data Analyst technical interviews
🛠 Tools Used
Python
Pandas
Matplotlib
Jupyter Notebook
📂 Dataset used in this project
https://drive.google.com/file/d/1gqPz...
🎯 This video is part of my Python Data Analysis Project Series designed to help beginners build real Data Analyst portfolio projects.
⏱ Video Chapters
00:00 Introduction
03:20 What is Exploratory Data Analysis
07:10 Data Loading & Dataset Overview
14:30 Checking Data Types
19:00 Statistical Summary
24:15 Handling Missing Values
30:40 Duplicate Detection & Removal
36:00 Feature Engineering
43:20 Sales by Region Analysis
48:30 Profit by Category
52:40 Monthly Sales Trend
56:30 Data Visualization
01:02:00 Business Insights & Conclusion
🔎 Keywords
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