Data Analysis with Python - Course Repository

Welcome to my repository for the "Data Analysis with Python" course! In this project, I have explored various tools and techniques used in the field of data analysis, leveraging the power of Python libraries like NumPy, Pandas, Matplotlib, and SciPy. This repository contains all the code, exercises, and resources I've worked on during the course.

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📚 Course Overview

In this course, I learned how to analyze and manipulate data using some of the most popular Python libraries. Below are the key topics covered:

• NumPy: Efficient numerical computations, working with arrays, and matrix operations.
• Pandas: Data wrangling, cleaning, and manipulation of tabular data using DataFrames.
• Matplotlib: Data visualization using a variety of plotting techniques.
• SciPy: Scientific and statistical operations to enhance data analysis workflows.

🛠️ Technologies Used

• Python 3.x
• NumPy - NumPy Documentation
• Pandas - Pandas Documentation
• Matplotlib - Matplotlib Documentation
• SciPy - SciPy Documentation

🧑‍🏫 Course Structure

This course consists of the following modules:

1. Introduction to NumPy

   • Basics of arrays, matrix operations, and broadcasting.

2. Data Wrangling with Pandas

   • Loading datasets, handling missing data, grouping, and transforming data.

3. Data Visualization with Matplotlib

   • Creating various types of plots: line, bar, histogram, scatter, etc.

4. Statistical Analysis with SciPy

   • Statistical tests, probability distributions, and regression analysis.

📈 Course Outcomes

By the end of this course, I was able to:

• Handle large datasets with Pandas efficiently.
• Perform advanced data analysis techniques with NumPy and SciPy.
• Create insightful visualizations to present data and analysis results.
• Apply statistical methods to test hypotheses and model data.

🚀 Project Folder Structure

Here’s a quick look at the folder structure of this repository: