Python Data Analysis

In this course, you will get to learn the fundamentals of Data Analysis with Python. We’ll cover how to work with arrays in Python, how to work with Python tabular for data manipulation and data analysis, and finally data visualisation with Python. To go through the course smoothly, we recommend you use Jupyter Notebooks from Anaconda or the Ipython Notebook on VS Code (make sure you have VS Code installed). If you are struggling to find a proper ipython-based development environment, you can also work with Google Colab. Here is an overview of the content breakdown:

1. Week 1: Numpy Arrays and Pandas Foundations
2. Week 2: Pandas Data Cleaning and Basic Matplotlib Visualisations
3. Week 3: Advanced Visualisation with Matplotlib, Seaborn, Geopandas
4. Week 4: SQL Programming (Querying Relational Databases)
5. Week 5: Capstone Exploratory Data Analysis Project

Attribution and Acknowledgement

This content in this course is attributed to Jake VanderPlas, the author of the Python Data Science Handbook and a Senior Software Engineer at Google Research. The content in this course is specifically licensed from the Python Data Science Handbook under the CC-BY-NC-ND license. The projects, supporting notes, and curriculum breakdown to accompany the content are curated by the Chaptr Data Science team, technical mentors to the program.