tz_FeatureEngineering_basic_CtoN.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# load data\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pandas import DataFrame\n",
    "train = pd.read_csv(\"train.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.ExterQual.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.ExterCond.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.BsmtCond.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.loc[train.BsmtCond.isnull(), 'BsmtCond'] = 'NoBsmt'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.BsmtCond.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.HeatingQC.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.KitchenQual.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.Functional.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "690"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.FireplaceQu.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.loc[train.FireplaceQu.isnull(), 'FireplaceQu'] = 'NoFireplace'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.FireplaceQu.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.GarageQual.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.loc[train.GarageQual.isnull(), 'GarageQual'] = 'NoGarage'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.GarageQual.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.loc[train.GarageCond.isnull(), 'GarageCond'] = 'NoGarage'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.GarageQual.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train = train.replace({\n",
    "                             'ExterQual': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1\n",
    "                                            },\n",
    "                             'ExterCond': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1\n",
    "                                            },\n",
    "                             'BsmtCond': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoBsmt': 0},\n",
    "                            'HeatingQC': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1\n",
    "                                            },\n",
    "                            'KitchenQual': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1},\n",
    "                             'Functional': {'Typ': 0,\n",
    "                                            'Min1': 1,\n",
    "                                            'Min2': 1,\n",
    "                                            'Mod': 2,\n",
    "                                            'Maj1': 3,\n",
    "                                            'Maj2': 4,\n",
    "                                            'Sev': 5,\n",
    "                                            'Sal': 6\n",
    "                                           },\n",
    "                            'FireplaceQu': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoFireplace': 0 \n",
    "                                            },\n",
    "                             'GarageQual': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoGarage': 0},\n",
    "                             'GarageCond': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoGarage': 0},\n",
    "                            })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.to_csv('train_basic_CtoN.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "'''\n",
    "从类别的数据到数值的数据\n",
    "ExterQual\n",
    "ExterCond\n",
    "BsmtQual（特殊处理）（还未处理）\n",
    "BsmtCond（将NA视为没有）\n",
    "BsmtExposure（特殊处理）(还未处理)\n",
    "HeatingQC\n",
    "KitchenQual\n",
    "Functional\n",
    "FireplaceQu（将NA视为没有）\n",
    "GarageQual（将NA视为没有）\n",
    "GarageCond（将NA视为没有）\n",
    "PoolQC（因为全是null所以不处理了）\n",
    "'''"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}