numpy/6 Multi Array Manipulation.ipynb

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   "cell_type": "code",
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   "source": [
    "import numpy as np"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----"
   ]
  },
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   "metadata": {},
   "source": [
    "## Iterating over entire array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  5 10]\n",
      "[15 20 25]\n",
      "[30 35 40]\n",
      "0\n",
      "15\n",
      "30\n",
      "5\n",
      "20\n",
      "35\n",
      "10\n",
      "25\n",
      "40\n"
     ]
    }
   ],
   "source": [
    "a = np.arange(0, 45, 5).reshape(3, 3)\n",
    "\n",
    "for i in a:\n",
    "    print(i)\n",
    "\n",
    "for i in np.nditer(a, order=\"F\"):\n",
    "    print(i)\n",
    "\n",
    "# Order F -> column wise, Default -> C -> Row wise\n",
    "# Or you can ofc flatten the aray and iterate through it the normal way"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "# Joining arrays\n",
    "### Axis = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2],\n",
       "       [3, 4],\n",
       "       [5, 6],\n",
       "       [7, 8]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(1, 5).reshape(2, 2)\n",
    "b = np.arange(5, 9).reshape(2, 2)\n",
    "\n",
    "# While joining, note that all dimensions except\n",
    "# the concatenation dimension must be equal in both the arrays\n",
    "\n",
    "# Joining 2 arrays along axis 0\n",
    "c = np.concatenate((a, b))\n",
    "c"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Axis = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 5, 6],\n",
       "       [3, 4, 7, 8]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Joining 2 arrays along axis 1\n",
    "c = np.concatenate((a, b), axis=1)\n",
    "c"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Axis = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5, 6, 7, 8])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Joining 2 arrays along axis None -> flattens arrays before joining\n",
    "c = np.concatenate((a, b), axis=None)\n",
    "c"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Axis = 0 (3d array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[1, 2],\n",
       "        [3, 4]],\n",
       "\n",
       "       [[5, 6],\n",
       "        [7, 8]]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(1, 5).reshape(1, 2, 2)\n",
    "b = np.arange(5, 9).reshape(1, 2, 2)\n",
    "\n",
    "# Joining 2 arrays along axis 0\n",
    "c = np.concatenate((a, b))\n",
    "c"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "# Spliting arrays\n",
    "### Split by division"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([10, 11, 12, 13]), array([14, 15, 16, 17]), array([18, 19, 20, 21])]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(10, 22)\n",
    "np.split(a, 3)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Split by position"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([10, 11, 12, 13]),\n",
       " array([14, 15, 16]),\n",
       " array([17]),\n",
       " array([18, 19, 20, 21])]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.split(a, [4, 7, 8])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "# Resizing arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 3],\n",
       "       [4, 5, 6]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(1, 7).reshape(2, -1)\n",
    "a"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using resize as reshape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]]\n"
     ]
    }
   ],
   "source": [
    "b = np.resize(a, (3, 2))\n",
    "print(b)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using resize as resize lol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 3, 4, 5],\n",
       "       [6, 1, 2, 3, 4],\n",
       "       [5, 6, 1, 2, 3]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = np.resize(a, (3, 5))\n",
    "b"
   ]
  }
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