071-logical-ops.ipynb

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   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt"
   ]
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   "execution_count": 2,
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      "text/plain": [
       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
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    "a = np.arange(10)\n",
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       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
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    "a"
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   "source": [
    "# Logical operations on arrays and scalars"
   ]
  },
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   "execution_count": 4,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([False, False,  True, False, False, False, False, False, False,\n",
       "       False])"
      ]
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     "execution_count": 4,
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    "a == 2"
   ]
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   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True,  True, False, False, False, False, False,\n",
       "       False])"
      ]
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     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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    "a <= 3"
   ]
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   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
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    {
     "data": {
      "text/plain": [
       "array([ True, False, False, False, False, False,  True, False, False,\n",
       "       False])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "np.logical_and(a % 3 == 0, a % 2 == 0)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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