# 📊 Pandas CSV Analysis
A Python-based data analysis project developed as part of the **Syntecxhub Data Science Internship**. This project demonstrates how to read, analyze, filter, summarize, and visualize CSV data using **Pandas** and **Matplotlib**.
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## 📌 Project Overview
The objective of this project is to perform basic data analysis on a CSV dataset by applying essential data analysis techniques using Python. The project covers data loading, exploration, statistical analysis, filtering, visualization, and exporting processed data.
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## 🎯 Objectives
- Read CSV data using Pandas
- Explore and inspect the dataset
- Generate descriptive statistics
- Filter and analyze specific records
- Export processed data to CSV
- Create visualizations for better insights
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## 🛠️ Technologies Used
- Python 3
- Pandas
- Matplotlib
- Jupyter Notebook
- CSV Dataset
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## 📂 Project Structure
Syntecxhub\_Pandas\_CSV\_Analysis/
│
├── data/
│ └── SampleSuperstore.csv
│
├── notebook/
│ └── Pandas\_CSV\_Analysis.ipynb
│
├── output/
│ ├── filtered\_data.csv
│ └── summary\_statistics.csv
│
├── images/
│ ├── sales\_by\_category.png
│ └── profit\_by\_region.png
│
├── requirements.txt
└── README.md
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## 📈 Features
- Read CSV dataset into a Pandas DataFrame
- Display dataset information
- View first and last records
- Generate descriptive statistics
- Calculate mean, median, minimum, maximum, and count
- Filter records based on conditions
- Select specific columns
- Export filtered data
- Create data visualizations using Matplotlib
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## 📊 Visualizations
This project includes:
- Sales by Category
- Profit by Region
The generated charts are available in the **images/** folder.
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##
### Clone the repository
git clone https://github.com/V-Nitheeshwaran/Syntecxhub\_Pandas\_CSV\_Analysis.git
### Navigate to the project folder
cd Syntecxhub\_Pandas\_CSV\_Analysis
### Install dependencies
pip install -r requirements.txt
### Launch Jupyter Notebook
jupyter notebook
Open:
notebook/Pandas\_CSV\_Analysis.ipynb
Run all cells to reproduce the analysis.
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## 📋 Requirements
pandas
matplotlib
openpyxl
jupyter
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## 📁 Dataset
The project uses the **Sample Superstore** dataset for demonstrating data analysis concepts such as data exploration, filtering, summary statistics, and visualization.
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## 🚀 Learning Outcomes
Through this project, I gained hands-on experience in:
- Data manipulation using Pandas
- Data exploration and cleaning
- Statistical analysis
- Data filtering and slicing
- Exporting processed data
- Data visualization using Matplotlib
- Organizing a professional data analytics project
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## 💼 Internship Information
**Organization:** Syntecxhub
**Domain:** Data Science Internship
**Task:** Week 1 – Pandas CSV Reader & Basic Analysis
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## 👨💻 Author
**Nitheeshwaran V**
📧 Email: nitheeshwaran74@gmail.com
🔗 LinkedIn: *(Add your LinkedIn URL)*
💻 GitHub: https://github.com/V-Nitheeshwaran
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## ⭐ Support
If you found this project helpful, consider giving it a ⭐ on GitHub.
Thank you for visiting this repository!