|
| 1 | +# Sorting NumPy Arrays |
| 2 | +- Sorting arrays is a common operation in data manipulation and analysis. |
| 3 | +- NumPy provides various functions to sort arrays efficiently. |
| 4 | +- The primary methods are `numpy.sort`,`numpy.argsort`, and `numpy.lexsort` |
| 5 | + |
| 6 | +### 1. numpy.sort() |
| 7 | + |
| 8 | +The `numpy.sort` function returns a sorted copy of an array. |
| 9 | + |
| 10 | +#### Syntax : |
| 11 | + |
| 12 | +```python |
| 13 | +numpy.sort(arr, axis=-1, kind=None, order=None) |
| 14 | +``` |
| 15 | +- **arr** : Array to be sorted. |
| 16 | +- **axis** : Axis along which to sort. (By Default is -1) |
| 17 | +- **kind** : Sorting algorithm. Options are 'quicksort', 'mergesort', 'heapsort', and 'stable'. (By Default 'quicksort') |
| 18 | +- **order** : When arr is an array with fields defined, this argument specifies which fields to compare first. |
| 19 | + |
| 20 | +#### Example : |
| 21 | + |
| 22 | +```python |
| 23 | +import numpy as np |
| 24 | + |
| 25 | +arr = np.array([1,7,0,4,6]) |
| 26 | +sarr = np.sort(arr) |
| 27 | +print(sarr) |
| 28 | +``` |
| 29 | + |
| 30 | +**Output** : |
| 31 | +```python |
| 32 | +[0 1 4 6 7] |
| 33 | +``` |
| 34 | + |
| 35 | +### 2. numpy.argsort() |
| 36 | + |
| 37 | +The `numpy.argsort` function returns the indices that would sort an array. Using those indices you can sort the array. |
| 38 | + |
| 39 | +#### Syntax : |
| 40 | + |
| 41 | +```python |
| 42 | +numpy.argsort(a, axis=-1, kind=None, order=None) |
| 43 | +``` |
| 44 | +- **arr** : Array to be sorted. |
| 45 | +- **axis** : Axis along which to sort. (By Default is -1) |
| 46 | +- **kind** : Sorting algorithm. Options are 'quicksort', 'mergesort', 'heapsort', and 'stable'. (By Default 'quicksort') |
| 47 | +- **order** : When arr is an array with fields defined, this argument specifies which fields to compare first. |
| 48 | + |
| 49 | +#### Example : |
| 50 | + |
| 51 | +```python |
| 52 | +import numpy as np |
| 53 | + |
| 54 | +arr = np.array([2.1,7,4.2,4.3,6]) |
| 55 | +indices = np.argsort(arr) |
| 56 | +print(indices) |
| 57 | +s_arr = arr[indices] |
| 58 | +print(s_arr) |
| 59 | +``` |
| 60 | + |
| 61 | +**Output** : |
| 62 | +```python |
| 63 | +[0 2 3 4 1] |
| 64 | +[2.1 4.2 4.3 6. 7. ] |
| 65 | +``` |
| 66 | + |
| 67 | +### 3. np.lexsort() |
| 68 | + |
| 69 | +The np.lexsort function performs an indirect stable sort using a sequence of keys. |
| 70 | + |
| 71 | +#### Syntax : |
| 72 | + |
| 73 | +```python |
| 74 | +numpy.lexsort(keys, axis=-1) |
| 75 | +``` |
| 76 | +- **keys**: Sequence of arrays to sort by. The last key is the primary sort key. |
| 77 | +- **axis**: Axis to be indirectly sorted.(By Default -1) |
| 78 | + |
| 79 | +#### Example : |
| 80 | + |
| 81 | +```python |
| 82 | +import numpy as np |
| 83 | + |
| 84 | +a = np.array([5,4,3,2]) |
| 85 | +b = np.array(['a','d','c','b']) |
| 86 | +indices = np.lexsort((a,b)) |
| 87 | +print(indices) |
| 88 | + |
| 89 | +s_arr = a[indices] |
| 90 | +print(s_arr) |
| 91 | + |
| 92 | +s_arr = b[indices] |
| 93 | +print(s_arr) |
| 94 | +``` |
| 95 | + |
| 96 | +**Output** : |
| 97 | +```python |
| 98 | +[0 3 2 1] |
| 99 | +[2 3 4 5] |
| 100 | +['a' 'b' 'c' 'd'] |
| 101 | +``` |
| 102 | + |
| 103 | +NumPy provides powerful and flexible functions for sorting arrays, including `np.sort`, `np.argsort`, and `np.lexsort`. |
| 104 | +These functions support sorting along different axes, using various algorithms, and sorting by multiple keys, making them suitable for a wide range of data manipulation tasks. |
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