2_2_why-numpy-template.ipynb

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   "source": [
    "# Why NumPy?"
   ]
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   "source": [
    "import numpy as np"
   ]
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   "source": [
    "### Ndarrays"
   ]
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   "source": [
    "array_a = np.array([1,2,3])"
   ]
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      ]
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    "array_a"
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     "name": "stdout",
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     "text": [
      "[1 2 3]\n"
     ]
    }
   ],
   "source": [
    "print(array_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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   "outputs": [
    {
     "data": {
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       "(3,)"
      ]
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     "execution_count": 7,
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   "source": [
    "array_a.shape"
   ]
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   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "array_b = np.array([[1,2,3],[4,5,6]])"
   ]
  },
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   "cell_type": "code",
   "execution_count": 9,
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   "outputs": [
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      "text/plain": [
       "array([[1, 2, 3],\n",
       "       [4, 5, 6]])"
      ]
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     "execution_count": 9,
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    "array_b"
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   "cell_type": "code",
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     "text": [
      "[[1 2 3]\n",
      " [4 5 6]]\n"
     ]
    }
   ],
   "source": [
    "print(array_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 3)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "array_b.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "array_c = np.array([1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1])"
      ]
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     "execution_count": 13,
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   "source": [
    "array_c"
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   "cell_type": "code",
   "execution_count": 14,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1,)"
      ]
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     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "array_c.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "array_d = np.array(1)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 16,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(1)"
      ]
     },
     "execution_count": 16,
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     "output_type": "execute_result"
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   ],
   "source": [
    "array_d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "array_d.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "cell_type": "code",
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   "cell_type": "code",
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### List vs Array"
   ]
  },
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   "cell_type": "code",
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  },
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