Std.ipynb

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   "source": [
    "import math\n",
    "import numpy as np\n",
    "import random"
   ]
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   "source": [
    "def mean(lst):\n",
    "    return sum(lst) / len(lst)\n",
    "\n",
    "\n",
    "def standard_deviation(lst):\n",
    "    m = mean(lst)\n",
    "    variance = sum([(value - m) ** 2 for value in lst])\n",
    "    return math.sqrt(variance / len(lst))"
   ]
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  {
   "cell_type": "code",
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   "metadata": {
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   "outputs": [],
   "source": [
    "lst = [random.random() for i in range(0,25)]"
   ]
  },
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     "text": [
      "The slowest run took 5.50 times longer than the fastest. This could mean that an intermediate result is being cached \n",
      "100000 loops, best of 3: 10 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit standard_deviation(lst)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
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   "outputs": [
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      "The slowest run took 4.05 times longer than the fastest. This could mean that an intermediate result is being cached \n",
      "10000 loops, best of 3: 37.8 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit np.std(lst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "def np_array(lst):\n",
    "    return np.array(lst)"
   ]
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   "execution_count": 7,
   "metadata": {
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     "text": [
      "The slowest run took 9.61 times longer than the fastest. This could mean that an intermediate result is being cached \n",
      "100000 loops, best of 3: 2.09 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit np_array(lst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "lsta = np_array(lst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000 loops, best of 3: 30.4 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit np.std(lsta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The slowest run took 4.02 times longer than the fastest. This could mean that an intermediate result is being cached \n",
      "10000 loops, best of 3: 35.6 µs per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit np.std(np_array(lst))"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
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   "source": []
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