Mini Project - Advanced Data Science Course at BIU

Description

This project includes two main tasks:

1. Covariance and Correlation Analysis with the Iris Dataset.
2. Laptop Price Analysis using Pandas, NumPy, and Visualization Libraries.

Features

• Implement covariance and correlation calculations from scratch.
• Validate results with NumPy and visualize them.
• Analyze and visualize laptop pricing trends by brand, RAM, CPU, and storage.

Install Dependencies

These are the required packages needed for the project to run. Note, create a virtual environment first to install all the requirements Since this project was done with a MacBook, here are the steps to create a virtual environment, and activate it

Step 1: Create a Virtual Environment called 'venv_name', you can change the name to any name, the name I used is venv

python3 -m venv venv_name

Step 2: Activate your virtual environment

source venv_name/bin/activate

To know your virtual environment has been activated, the name of your virtual environment comes up as a prefix in your terminal After activating the virtual environment, you can now install these packages

Step 3: To install these packages, run the following command:

pip install -r requirements.txt

Datasets

Datasets used in this notebook are the iris dataset and laptop price dataset which are included in the folder "Dataset"

Detailed Documentation and Analysis

The documentation and detailed explanation of the analysis are found in the pdf titled "Mini Project-Folasewa-B02294068.pdf"

Ipynb Notebook

The jupyter notebook is titled "Mini_Project_Folasewa_DS.ipynb"