numpy2.ipynb


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   "cell_type": "code",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "42\n",
      "()\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "x = np.array(42)\n",
    "print(np.ndim(x))\n",
    "print(x)\n",
    "print(np.shape(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<type 'numpy.ndarray'>\n",
      "1\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(7,)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a=np.array([1,2,3,4,5,6,7])\n",
    "print(type(a))\n",
    "print(np.ndim(a))\n",
    "np.shape(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "('shape before modification is', (2, 3))\n",
      "[[1 2 3]\n",
      " [4 5 6]]\n",
      "after reshaping\n",
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]]\n",
      "('shape after modification is', (3, 2))\n"
     ]
    }
   ],
   "source": [
    "b=np.array([ [1,2,3],\n",
    "            [4,5,6] ])\n",
    "print(np.ndim(b))\n",
    "print('shape before modification is',np.shape(b))\n",
    "print(b)\n",
    "print('after reshaping')\n",
    "b.shape=(3,2)\n",
    "print(b)\n",
    "print('shape after modification is',np.shape(b))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(2, 2, 2)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c=[ [[1,2],[3,4]],\n",
    "    [[5,6],[7,8]] ]\n",
    "print(np.ndim(c))\n",
    "np.shape(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]]\n"
     ]
    }
   ],
   "source": [
    "change_array = np.array([1,2,3,4,5,6])\n",
    "change_array.shape = (3, 2)\n",
    "print change_array      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "o = np.array([1,2,3,4,5])\n",
    "print(o[0])\n",
    "print(o[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3, 4]\n"
     ]
    }
   ],
   "source": [
    "c=[ [[1,2],[3,4]],\n",
    "    [[5,6],[7,8]] ]\n",
    "print(c[0][1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4 5 6 7 8 9]\n",
      "[1 2 3 4]\n",
      "[4 5 6 7]\n",
      "8\n",
      "[2 3 4 5 6 7 8]\n",
      "[0 1 2]\n",
      "[8 9]\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "s = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])\n",
    "print(s[:])\n",
    "print(s[1:5])\n",
    "print(s[4:8])\n",
    "print(s[-2])\n",
    "print(s[2:-1])\n",
    "print(s[:3])\n",
    "print(s[8:])\n",
    "print(s[len(s)/2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "(5, 5)\n",
      "[33 34 35]\n",
      "[13 23 33 43 53]\n",
      "13\n",
      "23\n",
      "33\n",
      "43\n",
      "53\n"
     ]
    }
   ],
   "source": [
    "t = np.array([\n",
    "[11, 12, 13, 14, 15],\n",
    "[21, 22, 23, 24, 25],\n",
    "[31, 32, 33, 34, 35],\n",
    "[41, 42, 43, 44, 45],\n",
    "[51, 52, 53, 54, 55]])\n",
    "\n",
    "print(np.ndim(t))\n",
    "print(np.shape(t))\n",
    "print(t[2,2:])\n",
    "val=t[:,2]\n",
    "print(val)\n",
    "# displaying column result verically\n",
    "for i in val:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[1, 4, 7], [2, 5, 8], [3, 6, 9]]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l = [[1,2,3],[4,5,6],[7,8,9]]\n",
    "map(list, zip(*l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[1, 4, 7], [2, 5, 8], [3, 6, 9]]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(l).T.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[14]\n",
      " [24]\n",
      " [34]\n",
      " [44]\n",
      " [54]]\n",
      "[14 24 34 44 54]\n",
      "[14]\n",
      "[24]\n",
      "[34]\n",
      "[44]\n",
      "[54]\n"
     ]
    }
   ],
   "source": [
    "p = np.array([\n",
    "[11, 12, 13, 14, 15],\n",
    "[21, 22, 23, 24, 25],\n",
    "[31, 32, 33, 34, 35],\n",
    "[41, 42, 43, 44, 45],\n",
    "[51, 52, 53, 54, 55]])\n",
    "g=p[:,3:4]\n",
    "print(g)\n",
    "# OR\n",
    "print(p[:,3])\n",
    "# OR\n",
    "for i in g:\n",
    "    print(i)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<type 'numpy.ndarray'>\n",
      "int32\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2],\n",
       "       [3, 4, 5]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(6)\n",
    "print(type(a))\n",
    "print(a.dtype)\n",
    "a.shape=(3,2)\n",
    "b=a.reshape(2,3)\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 1 1 1]\n",
      "[[[[1. 1. 1. 1.]\n",
      "   [1. 1. 1. 1.]\n",
      "   [1. 1. 1. 1.]]\n",
      "\n",
      "  [[1. 1. 1. 1.]\n",
      "   [1. 1. 1. 1.]\n",
      "   [1. 1. 1. 1.]]]]\n",
      "[[0 0 0]\n",
      " [0 0 0]]\n"
     ]
    }
   ],
   "source": [
    "x=np.array([1,2,3,4])\n",
    "a=np.ones_like(x)\n",
    "print(a)\n",
    "s=np.ones(x)\n",
    "print(s)\n",
    "t=np.array([[4,5,6],[1,2,3]])\n",
    "b=np.zeros_like(t)\n",
    "print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 1  2 34  5]\n",
      " [54 43  5  6]]\n",
      "[[ 0  2 34  5]\n",
      " [54 43  5  6]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "x=np.array([[1,2,34,5],[54,43,5,6]],order='K')\n",
    "y=x.copy()\n",
    "y[0][0]=0\n",
    "print(x)\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 0, 0],\n",
       "       [0, 1, 0],\n",
       "       [0, 0, 1]])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.identity(3,dtype=int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0],\n",
       "       [1, 0, 0],\n",
       "       [0, 1, 0],\n",
       "       [0, 0, 1]])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.eye(4,3,k=-1,dtype=int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 0],\n",
       "       [0, 0, 1],\n",
       "       [0, 0, 0]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.eye(3,k=1,dtype=int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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