Python Tutorial
NumPy Sorting Arrays
sort returns a sorted copy. For 2D arrays, choose the axis.
1D Sort
import numpy as np
print(np.sort(np.array([3, 1, 2, 4])))
print(np.sort(np.array(["banana", "apple", "cherry"])))2D Sort
m = np.array([[3, 2, 4], [5, 0, 1]])
print(np.sort(m)) # sort each row
print(np.sort(m, axis=0)) # sort each columnargsort
Get the indexes that would sort the array:
arr = np.array([30, 10, 20])
print(np.argsort(arr)) # [1 2 0]📘 Real-World Deep Dive
Knowing <strong>NumPy Sort (NumPy)</strong> well is what turns NumPy from a curiosity into a daily tool — you'll reach for it in nearly every real project.
Real-Life Scenario
An end-to-end usage of NumPy Sort that you'd actually see in a data pipeline or analytics notebook.
Real-Life Example
import numpy as np
a = np.array([3, 1, 2, 4])
print(np.sort(a)) # new array
a.sort() # in-place
print(a)Expected Output
(see source)Common mistakes
- NumPy uses 0-based, C-order indexing — the rightmost axis is the *fastest-varying* one. Mixing it with Fortran-order arrays is a common surprise.
np.array([[1,2],[3,4]], dtype=int)is fine, but a ragged Python list produces dtype=object and silently disables vectorisation.- In-place ops (
a *= 2) sometimes break views instead of returning a new array; usenp.multiply(a, 2, out=...)if explicitness matters. - Treating NumPy Sort as a black box without reading the docs — the API has subtle defaults that bite when you scale.
🚀 Performance & Best Practices
- Vectorise: replace Python
forloops with ufuncs; you can expect 10–100× speedups. - Pre-allocate output arrays with
np.emptyinstead of growing them withnp.append. - Keep data in float32 unless you need float64 precision — half the memory, double the cache locality.
- When working with NumPy, prefer vectorised / batched operations over Python loops.
🧪 Try It Yourself
- Reproduce the snippet on a representative slice of your own data.
- Profile the snippet with
cProfileortimeitand find the single biggest improvement. - Generalise the snippet into a small, reusable function you can drop into future projects.