Python

🐍 Python Basics

• **Getting Started** - Introduction to Python programming
• **Installation** - Setting up Python on your system
• **First Program** - Write and run your first Python script
• **Variables and Datatypes** - Working with data in Python
• **Operators** - Arithmetic, comparison, and logical operations
• **Conditionals** - If statements and control flow
• **Loops** - For and while loops for iteration
• **Functions** - Defining and using functions

🐍 Developer tools

• UV -- alternative to pip and virtualenv

  all-in-one tool for managing Python environments and dependencies. Fast, user-friendly, and designed for modern Python development.

• Ruff -- extremely fast Python linter and formatter

  replaces tools like Flake8, Black, and isort with a single, blazingly fast alternative written in Rust.

• Poetry -- dependency management and packaging

  simplifies package management with dependency resolution, virtual environments, and publishing capabilities.

• Pytest -- testing framework

  powerful and flexible testing tool that makes it easy to write simple and scalable test cases.

• IPython -- enhanced interactive Python shell

  provides rich introspection, tab completion, and magic commands for a better REPL experience.

• Jupyter -- interactive notebooks

  create and share documents with live code, visualizations, and narrative text for data science and analysis.

📦 Data Structures

• **Lists and Tuples** - Ordered collections of data
• **Dictionaries and Sets** - Key-value pairs and unique collections
• **Strings** - Text manipulation and formatting

Working with Data

• **Input and Output** - Reading and writing data
• **Development Environment** - IDEs and tools for Python

🐼 Pandas - Data Analysis

Pandas is the go-to library for data manipulation and analysis in Python. Perfect for working with structured data, CSV files, and data science projects.

Getting Started with Pandas

• **Getting Started with Pandas** - Introduction to the library
• **DataFrame and Series** - Core data structures
• **Selection and Filtering** - Querying your data

Data Manipulation

• **Data Cleaning** - Handling missing values and duplicates
• **GroupBy Operations** - Aggregating and summarizing data
• **Merging and Joining** - Combining multiple datasets
• **Reshaping** - Pivot, melt, and transform data

Analysis & Reference

• **Statistical Operations** - Descriptive statistics and analysis
• **Time Series** - Working with dates and time-based data
• **DataFrame Methods** - Common operations and techniques
• **DataFrame Quick Reference** - Cheat sheet for Pandas
• **Stata Files** - Working with .dta files