Gradient-Boosting Regression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Regression with Gradient Boosting Machines (GBMs)\n",
    "\n",
    "Gradient-boosting machines (GBMs) frequently achieve higher levels of accuracy than other learning algorithms. In this example, we use a dataset documenting housing prices in the Pacific Heights section of San Francisco and use a GBM to predict what a dwelling will sell for given the number of rooms, the square footage, and other factors.\n",
    "\n",
    "![](Images/san-francisco.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set()\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the dataset and examine its content and structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>address</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>finishedsqft</th>\n",
       "      <th>lastsolddate</th>\n",
       "      <th>lastsoldprice</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>neighborhood</th>\n",
       "      <th>totalrooms</th>\n",
       "      <th>usecode</th>\n",
       "      <th>yearbuilt</th>\n",
       "      <th>zipcode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2243 Franklin St</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1463</td>\n",
       "      <td>2/5/2016</td>\n",
       "      <td>1950000</td>\n",
       "      <td>37.795139</td>\n",
       "      <td>-122.425309</td>\n",
       "      <td>Pacific Heights</td>\n",
       "      <td>7</td>\n",
       "      <td>Condominium</td>\n",
       "      <td>1900</td>\n",
       "      <td>94109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2002 Pacific Ave APT 4</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3</td>\n",
       "      <td>3291</td>\n",
       "      <td>1/22/2016</td>\n",
       "      <td>4200000</td>\n",
       "      <td>37.794429</td>\n",
       "      <td>-122.428513</td>\n",
       "      <td>Pacific Heights</td>\n",
       "      <td>7</td>\n",
       "      <td>Condominium</td>\n",
       "      <td>1961</td>\n",
       "      <td>94109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1945 Washington St APT 411</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>653</td>\n",
       "      <td>12/16/2015</td>\n",
       "      <td>665000</td>\n",
       "      <td>37.792472</td>\n",
       "      <td>-122.425281</td>\n",
       "      <td>Pacific Heights</td>\n",
       "      <td>3</td>\n",
       "      <td>Condominium</td>\n",
       "      <td>1987</td>\n",
       "      <td>94109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1896 Pacific Ave APT 802</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2</td>\n",
       "      <td>2272</td>\n",
       "      <td>12/17/2014</td>\n",
       "      <td>2735000</td>\n",
       "      <td>37.794706</td>\n",
       "      <td>-122.426347</td>\n",
       "      <td>Pacific Heights</td>\n",
       "      <td>6</td>\n",
       "      <td>Condominium</td>\n",
       "      <td>1924</td>\n",
       "      <td>94109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1840 Washington St APT 603</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>837</td>\n",
       "      <td>12/2/2015</td>\n",
       "      <td>1050000</td>\n",
       "      <td>37.793212</td>\n",
       "      <td>-122.423744</td>\n",
       "      <td>Pacific Heights</td>\n",
       "      <td>3</td>\n",
       "      <td>Condominium</td>\n",
       "      <td>2012</td>\n",
       "      <td>94109</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      address  bathrooms  bedrooms  finishedsqft lastsolddate  \\\n",
       "0            2243 Franklin St        2.0         2          1463     2/5/2016   \n",
       "1      2002 Pacific Ave APT 4        3.5         3          3291    1/22/2016   \n",
       "2  1945 Washington St APT 411        1.0         1           653   12/16/2015   \n",
       "3    1896 Pacific Ave APT 802        2.5         2          2272   12/17/2014   \n",
       "4  1840 Washington St APT 603        1.0         1           837    12/2/2015   \n",
       "\n",
       "   lastsoldprice   latitude   longitude     neighborhood  totalrooms  \\\n",
       "0        1950000  37.795139 -122.425309  Pacific Heights           7   \n",
       "1        4200000  37.794429 -122.428513  Pacific Heights           7   \n",
       "2         665000  37.792472 -122.425281  Pacific Heights           3   \n",
       "3        2735000  37.794706 -122.426347  Pacific Heights           6   \n",
       "4        1050000  37.793212 -122.423744  Pacific Heights           3   \n",
       "\n",
       "       usecode  yearbuilt  zipcode  \n",
       "0  Condominium       1900    94109  \n",
       "1  Condominium       1961    94109  \n",
       "2  Condominium       1987    94109  \n",
       "3  Condominium       1924    94109  \n",
       "4  Condominium       2012    94109  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('Data/pacific-heights.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many rows and columns does the dataset contain?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(439, 13)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make sure there are no missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 439 entries, 0 to 438\n",
      "Data columns (total 13 columns):\n",
      "address          439 non-null object\n",
      "bathrooms        439 non-null float64\n",
      "bedrooms         439 non-null int64\n",
      "finishedsqft     439 non-null int64\n",
      "lastsolddate     439 non-null object\n",
      "lastsoldprice    439 non-null int64\n",
      "latitude         439 non-null float64\n",
      "longitude        439 non-null float64\n",
      "neighborhood     439 non-null object\n",
      "totalrooms       439 non-null int64\n",
      "usecode          439 non-null object\n",
      "yearbuilt        439 non-null int64\n",
      "zipcode          439 non-null int64\n",
      "dtypes: float64(3), int64(6), object(4)\n",
      "memory usage: 44.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Call `corr()` on the DataFrame to compute the pairwise correlation of all columns, and filter the results to show how much each column contributes to the dwelling's last-sold price."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "lastsoldprice    1.000000\n",
       "finishedsqft     0.840864\n",
       "bathrooms        0.768179\n",
       "totalrooms       0.670726\n",
       "bedrooms         0.606579\n",
       "zipcode          0.296032\n",
       "latitude         0.126480\n",
       "yearbuilt       -0.214365\n",
       "longitude       -0.309462\n",
       "Name: lastsoldprice, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix = df.corr()\n",
    "corr_matrix[\"lastsoldprice\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Factor out all the columns that have a correlation less than 0.2 as well as the latitude and longitude columns, which are roughly incorporated in the zip code. Also one-hot-encode the values in the \"usecode\" and \"zipcode\" columns so they can be included in the correlation (and in the model). It is easy to imagine that the dwelling's type and location could have an impact on the selling price."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th>bathrooms</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>finishedsqft</th>\n",
       "      <th>totalrooms</th>\n",
       "      <th>lastsoldprice</th>\n",
       "      <th>usecode_Condominium</th>\n",
       "      <th>usecode_Cooperative</th>\n",
       "      <th>usecode_Duplex</th>\n",
       "      <th>usecode_MultiFamily2To4</th>\n",
       "      <th>usecode_SingleFamily</th>\n",
       "      <th>usecode_Townhouse</th>\n",
       "      <th>zipcode_94109</th>\n",
       "      <th>zipcode_94115</th>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>837</td>\n",
       "      <td>3</td>\n",
       "      <td>1050000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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      ],
      "text/plain": [
       "   bathrooms  bedrooms  finishedsqft  totalrooms  lastsoldprice  \\\n",
       "0        2.0         2          1463           7        1950000   \n",
       "1        3.5         3          3291           7        4200000   \n",
       "2        1.0         1           653           3         665000   \n",
       "3        2.5         2          2272           6        2735000   \n",
       "4        1.0         1           837           3        1050000   \n",
       "\n",
       "   usecode_Condominium  usecode_Cooperative  usecode_Duplex  \\\n",
       "0                    1                    0               0   \n",
       "1                    1                    0               0   \n",
       "2                    1                    0               0   \n",
       "3                    1                    0               0   \n",
       "4                    1                    0               0   \n",
       "\n",
       "   usecode_MultiFamily2To4  usecode_SingleFamily  usecode_Townhouse  \\\n",
       "0                        0                     0                  0   \n",
       "1                        0                     0                  0   \n",
       "2                        0                     0                  0   \n",
       "3                        0                     0                  0   \n",
       "4                        0                     0                  0   \n",
       "\n",
       "   zipcode_94109  zipcode_94115  zipcode_94123  \n",
       "0              1              0              0  \n",
       "1              1              0              0  \n",
       "2              1              0              0  \n",
       "3              1              0              0  \n",
       "4              1              0              0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[['bathrooms', 'bedrooms', 'finishedsqft', 'totalrooms', 'usecode', 'zipcode', 'lastsoldprice']]\n",
    "df = pd.get_dummies(df, columns=['usecode', 'zipcode'])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now run the correlation again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "lastsoldprice              1.000000\n",
       "finishedsqft               0.840864\n",
       "bathrooms                  0.768179\n",
       "totalrooms                 0.670726\n",
       "usecode_SingleFamily       0.638482\n",
       "bedrooms                   0.606579\n",
       "zipcode_94123              0.228418\n",
       "zipcode_94115              0.071123\n",
       "usecode_Duplex             0.006292\n",
       "usecode_MultiFamily2To4   -0.019009\n",
       "usecode_Townhouse         -0.025467\n",
       "usecode_Cooperative       -0.025556\n",
       "zipcode_94109             -0.243927\n",
       "usecode_Condominium       -0.598575\n",
       "Name: lastsoldprice, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix = df.corr()\n",
    "corr_matrix[\"lastsoldprice\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remove the use-code columns that have little bearing on the output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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      ],
      "text/plain": [
       "   bathrooms  bedrooms  finishedsqft  totalrooms  lastsoldprice  \\\n",
       "0        2.0         2          1463           7        1950000   \n",
       "1        3.5         3          3291           7        4200000   \n",
       "2        1.0         1           653           3         665000   \n",
       "3        2.5         2          2272           6        2735000   \n",
       "4        1.0         1           837           3        1050000   \n",
       "\n",
       "   usecode_Condominium  usecode_SingleFamily  zipcode_94109  zipcode_94115  \\\n",
       "0                    1                     0              1              0   \n",
       "1                    1                     0              1              0   \n",
       "2                    1                     0              1              0   \n",
       "3                    1                     0              1              0   \n",
       "4                    1                     0              1              0   \n",
       "\n",
       "   zipcode_94123  \n",
       "0              0  \n",
       "1              0  \n",
       "2              0  \n",
       "3              0  \n",
       "4              0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.drop(['usecode_Duplex', 'usecode_MultiFamily2To4', 'usecode_Townhouse', 'usecode_Cooperative'], axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use Seaborn's handy [pairplot](https://seaborn.pydata.org/generated/seaborn.pairplot.html) function to visualize the relationships between non-categorical variables. Is there evidence of linearities?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1525b98db38>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df[['bathrooms', 'bedrooms', 'finishedsqft', 'totalrooms', 'lastsoldprice']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Split the data and train a GBM model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GradientBoostingRegressor(random_state=0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "x = df.drop('lastsoldprice', axis=1)\n",
    "y = df['lastsoldprice']\n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=0)\n",
    "\n",
    "model = GradientBoostingRegressor(random_state=0)\n",
    "model.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What is the model's mean absolute error (MAE?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "708895.8403811686"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import mean_absolute_error\n",
    "\n",
    "mean_absolute_error(y_test, model.predict(x_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What would a single-family home with 2 bathrooms, 2 bedrooms, 7 total rooms, and 2,000 square feet of space sell for in zip code 94115?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1999086.11626451])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict([[2, 2, 2000, 7, 0, 1, 0, 1, 0]])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.3 64-bit",
   "language": "python",
   "name": "python37364bit5e0b7703ae47466699b32afa3e25363f"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}