NUMPY Tutorial

🔹 NumPy Array Sort

Sorting is a fundamental operation in data processing. NumPy provides efficient functions to sort arrays in various ways — along axes, in ascending or descending order, and more.

✅ Key Functions for Sorting

• np.sort() — Returns a sorted copy of an array without modifying the original.
• ndarray.sort() — Sorts the array in-place, modifying the original array.
• np.argsort() — Returns the indices that would sort an array.

🎯 Basic Syntax

sorted_array = np.sort(array, axis=-1, kind='quicksort', order=None)

axis parameter determines the axis along which to sort:

• axis=-1 (default): Sorts along the last axis.
• axis=0: Sorts each column (for 2D arrays).
• axis=1: Sorts each row (for 2D arrays).
• axis=None: Flattens the array before sorting.

kind specifies the sorting algorithm:

• 'quicksort' — Fast but unstable (default).
• 'mergesort' — Stable sort.
• 'heapsort' — Not stable.
• 'stable' — Stable sort, available in newer versions.

✅ Examples

import numpy as np

# Example 1: Sort a 1D array (returns sorted copy)
arr = np.array([3, 1, 4, 1, 5, 9, 2])
sorted_arr = np.sort(arr)
print("Original array:", arr)
print("Sorted array:", sorted_arr)
# Output:
# Original array: [3 1 4 1 5 9 2]
# Sorted array: [1 1 2 3 4 5 9]

# Example 2: Sort a 2D array along rows (axis=1)
arr_2d = np.array([[3, 7, 5], [9, 1, 4]])
sorted_rows = np.sort(arr_2d, axis=1)
print("\nSorted each row:")
print(sorted_rows)
# Output:
# [[3 5 7]
#  [1 4 9]]

# Example 3: Sort a 2D array along columns (axis=0)
sorted_cols = np.sort(arr_2d, axis=0)
print("\nSorted each column:")
print(sorted_cols)
# Output:
# [[3 1 4]
#  [9 7 5]]

# Example 4: In-place sorting using ndarray.sort()
arr2 = np.array([10, 7, 8, 6, 9])
print("\nBefore in-place sort:", arr2)
arr2.sort()
print("After in-place sort:", arr2)
# Output:
# Before in-place sort: [10  7  8  6  9]
# After in-place sort: [ 6  7  8  9 10]

# Example 5: Using argsort() to get indices that would sort the array
arr3 = np.array([50, 10, 20, 40])
indices = np.argsort(arr3)
print("\nIndices that sort the array:", indices)
print("Sorted array using indices:", arr3[indices])
# Output:
# Indices that sort the array: [1 2 3 0]
# Sorted array using indices: [10 20 40 50]

🧰 Additional Tips

• To sort in descending order, use [::-1] on the sorted array: np.sort(arr)[::-1]
• Sorting structured arrays can be done using the order parameter.

⚠️ Common Errors

• Using axis values that do not exist in the array shape causes AxisError.
• Modifying arrays in-place will change the original data — use with care.

🔎 Summary

• np.sort() returns a sorted copy without modifying the original array.
• ndarray.sort() sorts the array in-place.
• np.argsort() returns indices to sort the array, useful for indirect sorting.
• Sorting can be done along any axis for multi-dimensional arrays.