Introduction to Python

Welcome to the Introduction to Python repository!
This collection of Jupyter notebooks is designed to help beginners get started with Python programming through practical, hands-on examples.

Each notebook focuses on a different aspect of the Python ecosystem — from language fundamentals to working with data and visualization.

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Author

João Brogueira de Sousa
Assistant Professor in Economics, Nova SBE

If you have questions, suggestions, or find an issue, feel free to reach out or open an issue on GitHub.

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Contents

This repository includes the following notebooks:

0. Getting Started: What is Python, Setup & Git/GitHub
   How it’s used, how scripts and notebooks differ, and how Python executes code. Installing Python/Miniconda, setting up Jupyter, running scripts and notebooks, basic command-line workflow, Git fundamentals (clone, commit, push), and using GitHub to share work.

1. Python Essentials
   Assignment statements, data types, and operators
   Learn how to declare variables, work with different data types (strings, numbers, booleans, etc.), and use basic operators to manipulate data.

2. Methods and Functions, Modules, Conditionals, and Loops
   Explore how to organize your code into reusable functions, use built-in and custom modules, and control program flow with conditionals and loops.

3. Working with Data: Pandas, Aggregations, and Transforms
   Get familiar with the pandas library to load, manipulate, and analyze datasets.
   Learn how to use aggregations, transforms, and apply operations efficiently.

4. Plotting with Matplotlib
   Discover how to create and customize plots using the matplotlib library — from basic line charts to more advanced visualizations.

5. Scraping Data with Python
   Learn how to collect data from websites and datasets.

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How to Use

You can explore the notebooks in two ways:

Option 1 — Run Online (No Installation)

You can open and run the notebooks directly in your browser using one of these platforms:

• Google Colab
• Binder

Open in Binder

Option 2 — Run Locally (with Conda)

1. Clone this repository

   git clone https://github.com/jbrogueira/python_intro.git
   cd python_intro

2. Install Conda (if you don’t have it already)
   You can install Conda by downloading one of the following distributions:

   • Anaconda — includes many data science packages by default.
   • Miniconda — a lightweight alternative that lets you install only what you need.

   After installation, make sure Conda is available by running:

   conda --version

3. Create and activate the conda environment

   conda env create -f environment.yml
   conda activate intro-python

4. Start Jupyter

   jupyter notebook

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Learning Goals

By the end of these notebooks, you will be able to:

• Understand Python syntax and basic programming constructs
• Write and organize your own functions and modules
• Analyze and transform data using pandas
• Visualize data using matplotlib
• Retrieve and process data from the web

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Recommended Resources

• Python Official Documentation
• Pandas Documentation
• Matplotlib Documentation
• QuantEcon Python Lectures

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About

These notebooks were prepared for students at Nova SBE as part of an introductory series on Python programming for economics.
They are intended as a practical companion for self-learning and classroom use.

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License

This project is licensed under the MIT License.