B1PythonBeginnerAbout 120 min to complete
Introduction to NumPy
The array — the single data structure underneath pandas, scikit-learn, and every scientific Python library.
Notebook
About 120 minutes to complete
Enrol to read the notebook and download it to run.
What this module covers
The array — the single data structure underneath pandas, scikit-learn, and every scientific Python library.
By the end of it
- Explain why NumPy is fast, in terms of memory layout and typed storage
- Create arrays with array, zeros, ones, arange, linspace, full, and eye
- Inspect arrays via shape, ndim, size, dtype, itemsize, and nbytes
- Choose dtypes deliberately, and recognise integer overflow and precision loss
- Index and slice 1-D and multi-dimensional arrays with [row, col] syntax
- Distinguish views from copies — the single most important NumPy gotcha
- Reshape arrays with reshape, ravel, flatten, and .T, and explain -1
- Measure the memory and speed difference against Python lists