Abstract¶
This notebook serves as a short reference to Python programming, numerical methods, data analysis, artificial intelligence related algorithms and visualization techniques. The content covers essential Python concepts, introduces interactive computing with Jupyter, and explores numerical approaches for solving mathematical problems. Additionally, it demonstrates how to analyze and visualize data using Python’s powerful libraries, enabling users to extract meaningful insights from both structured and unstructured datasets. The notebook emphasizes hands-on learning, providing directly executable code to facilitate understanding and application in real-world scenarios.
Introduction¶
Data analysis involves inspecting, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making. Python provides powerful libraries for data analysis, making it a popular choice among data scientists and analysts.
Installation¶
Besides python, we may need to install,
numpy: for numerical operationsscipy: for scientific computingmatplotlib: for plotting and visualizationpandas: for data manipulation and analysis