02_numpy/5_iterating_array.ipynb

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 "cells": [
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   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1,  2,  3],\n",
       "       [ 4,  5,  6,  7],\n",
       "       [ 8,  9, 10, 11]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(12).reshape(3, 4)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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      "10\n",
      "11\n"
     ]
    }
   ],
   "source": [
    "for row in a:\n",
    "    for cell in row:\n",
    "        print(cell)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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      "10\n",
      "11\n"
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   ],
   "source": [
    "for row in a.flatten():\n",
    "    print(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "0\n",
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      "10\n",
      "11\n"
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    }
   ],
   "source": [
    "for x in np.nditer(a, order='C'):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "4\n",
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      "6\n",
      "10\n",
      "3\n",
      "7\n",
      "11\n"
     ]
    }
   ],
   "source": [
    "for x in np.nditer(a, order='F'):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 4 8]\n",
      "[1 5 9]\n",
      "[ 2  6 10]\n",
      "[ 3  7 11]\n"
     ]
    }
   ],
   "source": [
    "for x in np.nditer(a, order='F', flags=['external_loop']):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in np.nditer(a, op_flags=['readwrite']):\n",
    "    x[...]=x*x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  0,   1,   4,   9],\n",
       "       [ 16,  25,  36,  49],\n",
       "       [ 64,  81, 100, 121]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 3],\n",
       "       [ 7],\n",
       "       [11]])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = np.arange(3, 15, 4).reshape(3, 1)\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 3\n",
      "1 3\n",
      "4 3\n",
      "9 3\n",
      "16 7\n",
      "25 7\n",
      "36 7\n",
      "49 7\n",
      "64 11\n",
      "81 11\n",
      "100 11\n",
      "121 11\n"
     ]
    }
   ],
   "source": [
    "for x,y in np.nditer([a,b]):\n",
    "    print(x,y)"
   ]
  }
 ],
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