Numpy for Beginners: Quick Reference for Common Functions arange and zeros

This article introduces two basic numerical array creation functions in Python Numpy: `arange` and `zeros`. `arange` is used to generate ordered arrays, similar to Python's built-in `range` but returns a Numpy array. Its syntax includes `start` (default 0), `stop` (required, exclusive), `step` (default 1), and `dtype`. Examples: The default parameters generate an array from 0 to 4; specifying `start=2, step=2` generates [2, 4, 6, 8] (note that `stop` is not included). When the step is a decimal, attention should be paid to floating-point precision. `zeros` is used to generate arrays filled with zeros, commonly for initialization. Its syntax parameters are `shape` (required, integer or tuple) and `dtype` (default float). Examples: `zeros(5)` generates a 1D array [0.0, 0.0, 0.0, 0.0, 0.0]; `zeros((2, 3))` generates a 2×3 2D array. Specifying `dtype=int` can produce arrays of integer zeros. Note that `shape` must be clearly specified, and a tuple should be passed for multi-dimensional arrays. Both are core tools for Numpy beginners. `arange` constructs ordered data,