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Course Overview

The goal of this course is to give the students a working knowledge of how to use Python to perform data analytics. We will introduce Python data structures (e.g., strings, lists, tuples, dictionaries, NumPy ndarrays, and Pandas DataFrames) and ways to manipulate data (e.g., selection, iteration, and visualization). We will also cover functions and classes. Students will design, implement, and test Python programs.

Syllabus (tentative)

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Textbooks

• A Byte of Python, Swaroop C H , Online (Free).
• How to Think Like a Computer Scientist, Brad Miller and David Ranum, Online (Free).
• Starting Out with Python, 5th Edition, Tony Gaddis, Pearson, ISBN-13: 978-0135929032 (Choice).
• Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, 2nd Edition, Wes McKinney, O'Reilly, ISBN-13: 978-1491957660 (Choice).

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Software Tools

Python Installer | The official installer of Python | Download (version 3.9 or above)

Google Colaboratory | Write and execute Python code and Jupyter Notebooks through the browser, and is suited to data analysis and education. | Experience colab in a browser (zero configuration required)

Visual Studio Code | A freeware source-code editor made by Microsoft for Windows, Linux and macOS. | Download Visual Studio Code and install its Python extension

PyCharm | A Python IDE for professional developers. | Download (community version)

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Useful Links

Python Programming

• Python Notes, Thomas Cokelaer, Online, 2014.
• PythonTutor.com, a tool visualizes what the computer is doing step-by-step as it executes.

Python Data Analytic Tools

• NumPy, the fundamental package for scientific computing with Python.
• Pandas, Python Data Analysis Library.
• Matplotlib, a Python 2D plotting library.
• Scikit Learn, tools for data mining and data analysis.