Coursera Python Project for Data Science from IBM

This repository contains the final project for the Coursera Python Project for Data Science from IBM course. The project demonstrates how Python can be applied to analyze and visualize data using essential data science libraries.

Project Overview

Final Project: Data Analysis with Python

The final project involves the complete data analysis process using Python. The goal is to import, clean, analyze, and visualize data to draw meaningful insights. Below are the key components of the project:

• Data Cleaning: Handling missing or inconsistent data.
• Exploratory Data Analysis (EDA): Summarizing the main characteristics of the data using visualizations.
• Data Visualization: Using Matplotlib and Seaborn to create informative graphs and charts that help interpret the data.
• Reporting Results: Interpreting and presenting the findings.

Technologies Used

• Python 3.x: Core language for the project.
• Pandas: Used for data manipulation and analysis, especially with dataframes.
• NumPy: Used for numerical computations.
• Matplotlib: Primary library for creating static, animated, and interactive visualizations.
• Seaborn: Built on top of Matplotlib, used for making attractive and informative statistical graphics.

Link to the Watson Proyect

• View the visualizations here:
• Python 3.x**: Core language for the project.