Introduction
Why Python for Data Science?
Versatility and ease of use
Extensive libraries and tools
Community support
Python's Role in Data Science:
Data collection, cleaning, visualization, and machine learning
Key Features of Python
Open-source and cross-platform
Supports procedural, object-oriented, and functional programming
Rich ecosystem of libraries:
NumPy for numerical computing
Pandas for data manipulation
Matplotlib and Seaborn for visualization
Python Workflow for Data Science
Data Collection:
Sources: CSV, APIs, Databases
Tools: requests, pandas
Data Cleaning:
Handling missing data, duplicates
Libraries: pandas
Data Visualization:
Charts and plots using matplotlib and seaborn
Machine Learning:
Build predictive models using scikit-learn
