sf_salaries_5.ipynb

{
 "cells": [{
   "cell_type": "code",
   "execution_count": 11,
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    {
     "data": {
      "text/plain": [
       "count     38119.000000\n",
       "mean      66564.421924\n",
       "std       44053.783972\n",
       "min           0.000000\n",
       "25%                NaN\n",
       "50%                NaN\n",
       "75%                NaN\n",
       "max      318835.490000\n",
       "Name: BasePay, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_numeric(latest_salaries['BasePay'], errors='coerce').describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "base_pay_series = pd.to_numeric(latest_salaries['BasePay'], errors='coerce') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20074,)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "base_pay_series[base_pay_series * .7 < average_yearly_rent].shape"
   ]
  }
],
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