Python-Libraries-for-Data-Analysis

Overview

This project demonstrates essential data manipulation tasks using NumPy and Pandas. It covers array operations, data handling, and dataset transformations to extract meaningful insights efficiently.

Technologies Used

• Python
• NumPy
• Pandas

Features

NumPy

• Created single and multi-dimensional arrays
• Utilized built-in mathematical functions
• Performed array slicing, indexing, and conditional selection

Pandas

• Worked with Series and DataFrames
• Read and processed CSV and HTML data
• Applied sorting, filtering, and missing value handling
• Used .apply() for function applications
• Merged datasets with pd.concat() and pd.merge()

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/numpy-pandas-project.git

2. Install required libraries:

   pip install numpy pandas

3. Run the script:

   python script.py

Usage

• Modify the dataset paths in the script as needed.
• Run the script to see NumPy and Pandas in action.
• Experiment with different operations to understand data handling better.

License

This project is open-source and available under the MIT License.