Sales Data Analysis

Simple exploratory and analysis notebook for sales data.

Overview

This repository contains a single Jupyter Notebook that performs exploratory data analysis and basic visualizations on sales data. It's intended as a lightweight starting point for analysts to inspect, clean, and visualize sales datasets.

Files

• sales_dataAnalysis.ipynb - Main analysis notebook.

Requirements

• Python 3.8+ recommended
• Jupyter / JupyterLab
• Common data libraries: pandas, numpy, matplotlib, seaborn

You can install typical dependencies with:

pip install -r requirements.txt

If no requirements.txt exists, install these packages manually:

pip install pandas numpy matplotlib seaborn jupyter

Usage

1. Open the notebook:

jupyter notebook sales_dataAnalysis.ipynb

2. Run cells in order. The notebook includes sections for data loading, cleaning, EDA, and plotting.

Data

Place your CSV or Excel sales files in a data/ directory (create if missing) and update the notebook paths accordingly. The notebook includes placeholder code to read data/sales.csv.