{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "06ac89df",
   "metadata": {},
   "source": [
    "# Sort\n",
    "\n",
    "As in Python’s `list`, NumPy arrays can be sorted in-place using the [numpy.sort](https://numpy.org/doc/stable/reference/generated/numpy.sort.html) method. You can sort any one-dimensional section of values in a multidimensional array in place along an axis by passing the axis number to sort:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a4099946",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-17T14:57:14.908069Z",
     "iopub.status.busy": "2026-05-17T14:57:14.907839Z",
     "iopub.status.idle": "2026-05-17T14:57:14.955254Z",
     "shell.execute_reply": "2026-05-17T14:57:14.954891Z",
     "shell.execute_reply.started": "2026-05-17T14:57:14.908053Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.7740598 , 0.20912608, 0.17613129],\n",
       "       [0.2691818 , 0.84813834, 0.6284038 ],\n",
       "       [0.61870574, 0.86602031, 0.77810677],\n",
       "       [0.58221564, 0.18867566, 0.61433336],\n",
       "       [0.19384893, 0.97196918, 0.58002664],\n",
       "       [0.56652261, 0.968951  , 0.0066615 ],\n",
       "       [0.56644055, 0.47526286, 0.8142787 ]])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "\n",
    "rng = np.random.default_rng()\n",
    "data = rng.random((7, 3))\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b2d7e426",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-17T14:57:14.955765Z",
     "iopub.status.busy": "2026-05-17T14:57:14.955663Z",
     "iopub.status.idle": "2026-05-17T14:57:14.959109Z",
     "shell.execute_reply": "2026-05-17T14:57:14.958871Z",
     "shell.execute_reply.started": "2026-05-17T14:57:14.955756Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.19384893, 0.18867566, 0.0066615 ],\n",
       "       [0.2691818 , 0.20912608, 0.17613129],\n",
       "       [0.56644055, 0.47526286, 0.58002664],\n",
       "       [0.56652261, 0.84813834, 0.61433336],\n",
       "       [0.58221564, 0.86602031, 0.6284038 ],\n",
       "       [0.61870574, 0.968951  , 0.77810677],\n",
       "       [0.7740598 , 0.97196918, 0.8142787 ]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.sort(0)\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bccf7aeb",
   "metadata": {},
   "source": [
    "`np.sort`, on the other hand, returns a sorted copy of an array instead of changing the array in place:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4d6e17da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-17T14:57:14.959673Z",
     "iopub.status.busy": "2026-05-17T14:57:14.959578Z",
     "iopub.status.idle": "2026-05-17T14:57:14.961964Z",
     "shell.execute_reply": "2026-05-17T14:57:14.961734Z",
     "shell.execute_reply.started": "2026-05-17T14:57:14.959665Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.0066615 , 0.18867566, 0.19384893],\n",
       "       [0.17613129, 0.20912608, 0.2691818 ],\n",
       "       [0.47526286, 0.56644055, 0.58002664],\n",
       "       [0.56652261, 0.61433336, 0.84813834],\n",
       "       [0.58221564, 0.6284038 , 0.86602031],\n",
       "       [0.61870574, 0.77810677, 0.968951  ],\n",
       "       [0.7740598 , 0.8142787 , 0.97196918]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sort(data, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "97af8303",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-17T14:57:14.962477Z",
     "iopub.status.busy": "2026-05-17T14:57:14.962390Z",
     "iopub.status.idle": "2026-05-17T14:57:14.964874Z",
     "shell.execute_reply": "2026-05-17T14:57:14.964505Z",
     "shell.execute_reply.started": "2026-05-17T14:57:14.962470Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.19384893, 0.18867566, 0.0066615 ],\n",
       "       [0.2691818 , 0.20912608, 0.17613129],\n",
       "       [0.56644055, 0.47526286, 0.58002664],\n",
       "       [0.56652261, 0.84813834, 0.61433336],\n",
       "       [0.58221564, 0.86602031, 0.6284038 ],\n",
       "       [0.61870574, 0.968951  , 0.77810677],\n",
       "       [0.7740598 , 0.97196918, 0.8142787 ]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.13 Kernel",
   "language": "python",
   "name": "python313"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.0"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}