NumPy and Jupyter Notebooks
Work with typed arrays and vectorized operations, then present a reproducible analysis in a notebook with honest labels and visible assumptions.
Basic Python and understanding of arrays.
Create and manipulate NumPy arrays for efficient numerical computing, perform vectorized operations, and build interactive Jupyter notebooks with code and markdown.
Read in order, or jump to what you need.
Every lesson builds on the one before it. Open any lesson to read the explanation, run the examples, and try the practice challenges.
- 09.01NumPy Fundamentals4 min
Create shaped arrays, replace loops with vectorized operations, and summarize data along the correct axis.
- 09.02Jupyter Notebooks4 min
Turn an analysis into a reproducible narrative with code cells, markdown explanations, labeled charts, and a clean run order.
- 09.03Project: A Reproducible Data Analysis NotebookProject4 min
Answer one revenue question with NumPy, make every cleaning decision visible, and ship an executed notebook that another person can rerun.
Ready to move on?
Create a Jupyter notebook that imports NumPy, performs statistical analysis on a dataset, and documents the findings with markdown cells.
Open the module self-check