{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# idioms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# group creator\n",
    "def create_frame(n, n_groups):\n",
    "    stamps = pd.date_range('20010101',periods=n,freq='ms')\n",
    "    random.shuffle(stamps.values)    \n",
    "    return DataFrame({'name'  : np.random.randint(0,n_groups,size=n),\n",
    "                      'stamp' : stamps,\n",
    "                      'value' : np.random.randint(0,n,size=n),\n",
    "                      'value2' : np.random.randn(n)})\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# unwrapping groupby"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df = create_frame(1000000,10000)\n",
    "\n",
    "def f_apply(df):\n",
    "    return df.groupby('name').value2.apply(lambda x: (x-x.mean())/x.std())\n",
    "def f_unwrap(df):\n",
    "    g = df.groupby('name').value2\n",
    "    v = df.value2\n",
    "    return (v-g.transform('mean'))/g.transform('std')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.allclose(f_apply(df),f_unwrap(df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loops, best of 3: 2.68 s per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit f_apply(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loops, best of 3: 635 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit f_unwrap(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = create_frame(1000000,100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loops, best of 3: 310 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit f_apply(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loops, best of 3: 267 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit f_unwrap(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# if then"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = create_frame(100000,1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def result_apply(df):\n",
    "    return df.value.apply(lambda x: np.nan if x < 30000 else x)\n",
    "def result_where(df):\n",
    "    return df.value.where(df.value>=30000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_apply(df).equals(result_where(df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 loops, best of 3: 43.7 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit result_apply(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 2.1 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%timeit result_where(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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