{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "caa5b23d-5ac6-4e7e-9155-70eba6a08474",
   "metadata": {},
   "source": [
    "# Lesson 09 demo: Numpy\n",
    "\n",
    "## 1. Set up"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9348f9a-10d0-4acb-968b-7f263f1e037b",
   "metadata": {},
   "source": [
    "To install numpy:\n",
    "\n",
    "```text\n",
    "pip install numpy\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "72553e7f-1f9e-4d43-8cd3-1855560a3adf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cad98d1f-a645-4db7-81f4-01ad24a14c88",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Numpy version: 2.2.6\n"
     ]
    }
   ],
   "source": [
    "print(f\"Numpy version: {np.__version__}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ef3cee2-4852-47e1-a90d-ec8a20a0352d",
   "metadata": {
    "tags": [],
    "toc-hr-collapsed": true
   },
   "source": [
    "## 2. Creating arrays\n",
    "\n",
    "### 2.1. From a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "02bcb75f-e891-444c-8f18-76c7089f26c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_arr = np.array([1, 2, 3, 4, 5])\n",
    "type(my_arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eb25dab0-708c-43bb-b6c7-a7e8a38449a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]]\n"
     ]
    }
   ],
   "source": [
    "my_arr = np.array([\n",
    "    [1, 2, 3],\n",
    "    [4, 5, 6]\n",
    "])\n",
    "\n",
    "print(my_arr)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6ad3d7a-77ef-4c52-8266-7bfa9ead0064",
   "metadata": {},
   "source": [
    "### 2.2. Using built-functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7e685562-1815-4e87-9ac1-0abc331215af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0. 0. 0. 0.]\n",
      " [0. 0. 0. 0.]\n",
      " [0. 0. 0. 0.]]\n"
     ]
    }
   ],
   "source": [
    "zero_array = np.zeros((3,4))\n",
    "print(zero_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "365b2917-aeac-4470-bc66-838417a004dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1. 1. 1. 1.]\n",
      " [1. 1. 1. 1.]\n",
      " [1. 1. 1. 1.]]\n"
     ]
    }
   ],
   "source": [
    "constant_array = np.full((3,4), 1.0)\n",
    "print(constant_array)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e186681a-05b1-4573-9b79-22c6360494e4",
   "metadata": {},
   "source": [
    "## 3. Array attributes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1e6d4d31-ad33-4ee7-9b91-b1a78c3c33c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 4)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "constant_array.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fb58df7f-e764-4db6-b8b1-4e9aad8b0cae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "constant_array.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c0c35d4e-3691-454a-9be6-beb6ff617a69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "96"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "constant_array.nbytes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d07e1fc-128d-421c-bbcd-250e00e4b2cc",
   "metadata": {
    "tags": [],
    "toc-hr-collapsed": true
   },
   "source": [
    "## 4. Array functions & operations\n",
    "\n",
    "### 4.1. Arithmetic operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b849b698-38a9-4e05-b2b3-78200a850b66",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([10,20,30,40])\n",
    "b = np.array([1,2,3,4])\n",
    "c = np.array([1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5e69a084-183c-4948-a99f-58d4f241fd90",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11 22 33 44]\n"
     ]
    }
   ],
   "source": [
    "print(a + b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bdc6d525-fbe6-4067-9645-675953b73097",
   "metadata": {},
   "outputs": [],
   "source": [
    "a_list = [10,20,30,40]\n",
    "b_list = [1,2,3,4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "838958f0-fb41-4909-b233-af369495d89d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10, 20, 30, 40, 1, 2, 3, 4]\n"
     ]
    }
   ],
   "source": [
    "print(a_list + b_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e845aa85-b22c-4cb8-9baa-2cb1f60d52b3",
   "metadata": {},
   "source": [
    "### 4.2 Statistical methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "75b9e7ba-143e-4def-a927-ce30afb64547",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25.0\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f25a74c5-1e46-4bd3-a2ff-b2396f938798",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(a))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fca9295e-9afe-46f4-bf43-e323d05391f3",
   "metadata": {},
   "source": [
    "### 4.3. Methods on axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "25a85ce0-5be4-4959-aa6f-af302914e8ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[10 20 30 40]\n",
      " [ 1  2  3  4]]\n"
     ]
    }
   ],
   "source": [
    "arr_2d = np.array([\n",
    "    [10,20,30,40],\n",
    "    [1,2,3,4]\n",
    "\n",
    "])\n",
    "\n",
    "print(arr_2d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f7928c69-4ff3-4c24-8bfe-429f87eb7053",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 4)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_2d.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eff06f00-4bf4-44c2-b825-6470e9a0d976",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "13.75\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(arr_2d))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2861fd4e-8980-47c7-905f-a66f2ee255d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 5.5 11.  16.5 22. ]\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(arr_2d, axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "27c26538-deae-45d9-948f-5fe06bfac8f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[25.   2.5]\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(arr_2d, axis=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "1cf68037-c132-4824-ad0b-905774f56d3a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 2, 4)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_2d.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1a2d3c8-1020-4cbb-a1ef-f69ec68d76a9",
   "metadata": {},
   "source": [
    "### 4.4. Shape manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "47902f23-e34c-428d-856d-64be29cfdd81",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  1  2  3  4  5  6  7  8  9 10 11]\n"
     ]
    }
   ],
   "source": [
    "arr = np.arange(12)\n",
    "print(arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8456a09d-c181-4105-a343-95f6cc6ac9a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0  1  2  3  4  5]\n",
      " [ 6  7  8  9 10 11]]\n"
     ]
    }
   ],
   "source": [
    "new_arr = arr.reshape(2,6)\n",
    "print(new_arr)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfe59328-be77-4c58-8608-9808cde8b4f7",
   "metadata": {},
   "source": [
    "## Selecting data\n",
    "\n",
    "### 5.1. Indexing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "e89fea5d-12c9-48f4-ade9-fe2c55f65b56",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 20 30 40 50]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([10, 20, 30, 40, 50])\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "93b9727e-94b9-4b69-b5a1-f68ea709b8fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n"
     ]
    }
   ],
   "source": [
    "print(a[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "34ba6004-1096-4c1b-a5b4-19738c0c4fe2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20\n"
     ]
    }
   ],
   "source": [
    "print(a[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "a12f27b3-797a-4c12-a423-2a83719ca990",
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "index -10 is out of bounds for axis 0 with size 5",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[68], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43ma\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m]\u001b[49m)\n",
      "\u001b[0;31mIndexError\u001b[0m: index -10 is out of bounds for axis 0 with size 5"
     ]
    }
   ],
   "source": [
    "print(a[-10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "e8fb15bf-e58c-47f9-b37f-944989baa7f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[10 20 30 40]\n",
      " [ 1  2  3  4]\n",
      " [ 5  6  7  8]]\n"
     ]
    }
   ],
   "source": [
    "arr_2d = np.array([\n",
    "    [10, 20, 30, 40],\n",
    "    [1, 2, 3, 4],\n",
    "    [5, 6, 7, 8]\n",
    "])\n",
    "print(arr_2d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "72d5477e-4588-44da-bd71-bad5abb9c887",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 20 30 40]\n"
     ]
    }
   ],
   "source": [
    "print(arr_2d[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "360ad9d0-6bb0-44f1-b29f-ddab82ea35c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 20 30 40]\n"
     ]
    }
   ],
   "source": [
    "first_row = arr_2d[0]\n",
    "print(first_row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "2c2e8e30-41ee-4efe-86e9-1672fb4124df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40\n"
     ]
    }
   ],
   "source": [
    "last_ele_first_row = first_row[-1]\n",
    "print(last_ele_first_row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "2eb54858-f72e-4873-9514-42f2ca493e1b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n"
     ]
    }
   ],
   "source": [
    "print(arr_2d[1][2])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38cc1f9d-7683-4642-9205-9d57a281640d",
   "metadata": {},
   "source": [
    "### 5.2. Slicing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "148f1cfe-1529-4d59-a3d7-211a0f8f2a32",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[10 20 30 40]\n",
      " [ 1  2  3  4]\n",
      " [ 5  6  7  8]]\n"
     ]
    }
   ],
   "source": [
    "print(arr_2d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "3dfe2957-e953-44fb-86ea-63131bb47009",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 20 30 40]\n"
     ]
    }
   ],
   "source": [
    "print(arr_2d[0, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "7bd37c75-71c9-4271-b3b0-177f219db8f5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10  1  5]\n"
     ]
    }
   ],
   "source": [
    "print(arr_2d[:, 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "26434514-43c0-40d9-9b79-7904377b4d22",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[20 30 40]\n"
     ]
    }
   ],
   "source": [
    "print(arr_2d[0, 1:4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61f92ab9-db2a-4190-93d4-f5d1526412f6",
   "metadata": {},
   "source": [
    "### 5.3. Filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "aba91c76-e76f-4718-bc89-a2c86969fc3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 20 30 40 50 60 70]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([10,20,30,40,50,60,70])\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "8d7ccbc1-1e4e-4e01-8d1a-54b29b17c079",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "b = 50\n",
    "print(b < 60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "2adf9272-db34-4473-8365-c350b353e40f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[False False  True  True  True  True  True]\n"
     ]
    }
   ],
   "source": [
    "mask = a > 20\n",
    "print(mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "03fe7ec5-0f02-4834-8162-b45a5a94b7d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[30 40 50 60 70]\n"
     ]
    }
   ],
   "source": [
    "print(a[mask])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "95ea146c-76e3-4f6e-bae8-ce884ca74a43",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[30 40 50 60 70]\n"
     ]
    }
   ],
   "source": [
    "print(a[a > 20])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fa6e44e-4436-4526-b126-19801b983093",
   "metadata": {},
   "source": [
    "## 6. A note about copies vs 'views'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "bbbfa87a-3bff-4034-8c42-4b0876b72576",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[30 40 50]\n"
     ]
    }
   ],
   "source": [
    "copy_a = a[2:5].copy()\n",
    "print(copy_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "354edb23-4be3-4859-a168-c3b63cf0c5bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 30 100  50]\n"
     ]
    }
   ],
   "source": [
    "copy_a[1] = 100\n",
    "print(copy_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "5e35c5dc-7303-4c4d-ac76-434c4ed03275",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 20 30 40 50 60 70]\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "462db0ae-13a5-4020-b81f-30ce61f0dda9",
   "metadata": {},
   "outputs": [],
   "source": [
    "b = a[2:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "798bc8e0-55b6-4958-b554-a1fa0c387582",
   "metadata": {},
   "outputs": [],
   "source": [
    "b[1] = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "43d1fcb6-da48-4549-a9aa-9ce6bf5f743a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 30 100  50]\n"
     ]
    }
   ],
   "source": [
    "print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "b55e40a4-2cfc-4ea6-b8f1-334960ba7067",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 10  20  30 100  50  60  70]\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "a69313c0-03b2-4866-85ba-72762bcb2650",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "140300009313584"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "30676988-4909-4360-a7a2-6239c0b81169",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "140300009313776"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id(b)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca311e1e-6a6c-437a-8791-1a058d19fca9",
   "metadata": {},
   "source": [
    "## 7. Data types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "039bbbe1-f0fb-41e4-95df-828b19bf8959",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([1.8,2,3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "ccbb09a8-9f14-4b82-a2ed-c6dd5ab05ff9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "b9de6f22-d9cf-4563-ad1b-91dea3965ef7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = a.astype(np.float64)\n",
    "b.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "1206ec36-d7d6-456e-b5ff-a3149502deac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float32')"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = a.astype(np.float32)\n",
    "c.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "d76a7c39-8793-4f38-85fd-1ee510d07c96",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1. 2. 3.]\n"
     ]
    }
   ],
   "source": [
    "print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "df7acf9c-1fcf-44e4-8b7c-4c83f8aa7bf2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1. 2. 3.]\n"
     ]
    }
   ],
   "source": [
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "c765c051-7949-44fb-8515-a9fa123938c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "24\n"
     ]
    }
   ],
   "source": [
    "print(b.nbytes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "c70047ba-5e71-4448-a8e4-5f6fabaeb87c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12\n"
     ]
    }
   ],
   "source": [
    "print(c.nbytes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "62b8a04e-22eb-4943-a5d7-cd8794504080",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3]\n"
     ]
    }
   ],
   "source": [
    "print(a.astype(np.int32))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (myenv)",
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