mean_perf.ipynb

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   "cell_type": "code",
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
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   "outputs": [
    {
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     "text": [
      "The slowest run took 7.66 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "10000 loops, best of 3: 44.9 µs per loop\n"
     ]
    }
   ],
   "source": [
    "arr = np.zeros((100, 100), dtype=np.float64)\n",
    "%timeit np.mean(arr, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 loops, best of 3: 234 µs per loop\n"
     ]
    }
   ],
   "source": [
    "df = pd.DataFrame(np.zeros((100, 100), dtype=np.float64))\n",
    "%timeit df.mean(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
   },
   "outputs": [],
   "source": []
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