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Sales Data Analysis Project for Beginners Using Data Science

Sales Data Analysis Project for Beginners Using Data Science

The Sales Data Analysis project is a practical data science project that examines historical sales data to uncover revenue trends, top-performing products, quarterly performance, and customer insights. It uses Python with pandas, Matplotlib, and Seaborn to clean, aggregate, and visualize real-world sales datasets. Built entirely in Google Colab, the project is beginner-friendly, end-to-end, and demonstrates how raw data is transformed into actionable business insights through structured analysis and visualization.

6 Modules

31 Lessons

English

0.5 Hr

Reading Plan

MODULE 1

Introduction

4 mins

Introduction

1 min

What Is Data Science?

1 min

What Is Sales Data Analysis?

1 min

Aim of the Project

1 min

MODULE 2

Pre-requisites and Tech Stack Used

4 mins

Pre-requisites & Tech Stack Used

1 min

Basic Requirements

1 min

Tech Stack Used

1 min

Input and Output

1 min

MODULE 3

Necessary Concepts

7 mins

Necessary Concepts

1 min

Data Cleaning

1 min

Handling Missing Values

1 min

Data Type Conversion

1 min

Data Aggregation and Grouping

1 min

Exploratory Data Analysis (EDA) and Data Visualization

1 min

Charts Used in the Analysis

1 min

MODULE 4

Step-by-Step Implementation

6 mins

Step-by-Step Implementation

1 min

Dataset Download and Environment Setup

1 min

Loading the Dataset

1 min

Understanding the Dataset

1 min

Data Cleaning and Preparation

1 min

Exploratory Data Analysis and Visualization

1 min

MODULE 5

Data Analysis and Insights From Sales Data

5 mins

Data Analysis and Insights From Sales Data

1 min

Revenue Trends Over Time

1 min

Conclusion

5 mins

Conclusion

1 min

Learning Outcome

1 min

Live Output and Analysis Overview

1 min

MCQs

1 min

Resources

1 min

Contributors

Jebasta

Sales Data Analysis Project for Beginners Using Data Science

Learn how to analyze real-world sales data using Python to uncover revenue trends, top products, quarterly performance, and customer insights. This beginner-friendly handbook guides you through data cleaning, aggregation, exploratory analysis, and visualization using Pandas, Matplotlib, and Seaborn in Google Colab.

Sales Data Analysis - Datascience project

This handbook helps learners gain hands-on experience in data analysis by working with a real-world sales dataset. It explains how to clean, aggregate, and visualize sales data to uncover revenue trends, top products, quarterly performance, and customer insights, all in a clear and beginner-friendly way using Python, Pandas, Matplotlib, and Seaborn

Sales Data Analysis - Beginner Datascience project

This project is ideal for beginners who want to get started with data analysis. It’s perfect for students, freshers, and anyone with basic Python knowledge who wants to understand how real-world sales data can be analyzed and visualized using practical, hands-on implementation.

Prerequisites

This course is suitable for:

Basic knowledge of Python programming
Basic understanding of data analysis concepts (columns, rows, missing values)
A Google account to access Google Colab
Access to the sales dataset in CSV format
Internet connection to upload the dataset and run the project in Colab

Run & Test your Code with our very own IDE that supports 16 languages

Open IDE

6 Modules

31 Lessons

English

0.5 Hr

Contributors

Jebasta

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