02.Naive Methods.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"AirQualityUCI.csv\", sep = \";\", decimal = \",\")\n",
    "df = df.iloc[ : , 0:14]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "132594"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.size(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['Date'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "130998"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.size(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date             0\n",
       "Time             0\n",
       "CO(GT)           0\n",
       "PT08.S1(CO)      0\n",
       "NMHC(GT)         0\n",
       "C6H6(GT)         0\n",
       "PT08.S2(NMHC)    0\n",
       "NOx(GT)          0\n",
       "PT08.S3(NOx)     0\n",
       "NO2(GT)          0\n",
       "PT08.S4(NO2)     0\n",
       "PT08.S5(O3)      0\n",
       "T                0\n",
       "RH               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       13.6\n",
       "1       13.3\n",
       "2       11.9\n",
       "3       11.0\n",
       "4       11.2\n",
       "5       11.2\n",
       "6       11.3\n",
       "7       10.7\n",
       "8       10.7\n",
       "9       10.3\n",
       "10      10.1\n",
       "11      11.0\n",
       "12      10.5\n",
       "13      10.2\n",
       "14      10.8\n",
       "15      10.5\n",
       "16      10.8\n",
       "17      10.5\n",
       "18       9.5\n",
       "19       8.3\n",
       "20       8.0\n",
       "21       8.3\n",
       "22       9.7\n",
       "23       9.8\n",
       "24      10.3\n",
       "25       9.7\n",
       "26       9.6\n",
       "27       9.1\n",
       "28       8.2\n",
       "29       8.2\n",
       "        ... \n",
       "9327    17.8\n",
       "9328    21.1\n",
       "9329    24.0\n",
       "9330    26.5\n",
       "9331    28.7\n",
       "9332    28.5\n",
       "9333    30.0\n",
       "9334    29.4\n",
       "9335    28.9\n",
       "9336    22.8\n",
       "9337    19.9\n",
       "9338    17.5\n",
       "9339    16.4\n",
       "9340    15.5\n",
       "9341    14.3\n",
       "9342    14.2\n",
       "9343    13.8\n",
       "9344    12.1\n",
       "9345    11.3\n",
       "9346    11.8\n",
       "9347    10.4\n",
       "9348     9.5\n",
       "9349     9.7\n",
       "9350    13.5\n",
       "9351    18.2\n",
       "9352    21.9\n",
       "9353    24.3\n",
       "9354    26.9\n",
       "9355    28.3\n",
       "9356    28.5\n",
       "Name: T, Length: 9357, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['T']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['T_t-1'] = df['T'].shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        NaN\n",
       "1       13.6\n",
       "2       13.3\n",
       "3       11.9\n",
       "4       11.0\n",
       "5       11.2\n",
       "6       11.2\n",
       "7       11.3\n",
       "8       10.7\n",
       "9       10.7\n",
       "10      10.3\n",
       "11      10.1\n",
       "12      11.0\n",
       "13      10.5\n",
       "14      10.2\n",
       "15      10.8\n",
       "16      10.5\n",
       "17      10.8\n",
       "18      10.5\n",
       "19       9.5\n",
       "20       8.3\n",
       "21       8.0\n",
       "22       8.3\n",
       "23       9.7\n",
       "24       9.8\n",
       "25      10.3\n",
       "26       9.7\n",
       "27       9.6\n",
       "28       9.1\n",
       "29       8.2\n",
       "        ... \n",
       "9327    13.5\n",
       "9328    17.8\n",
       "9329    21.1\n",
       "9330    24.0\n",
       "9331    26.5\n",
       "9332    28.7\n",
       "9333    28.5\n",
       "9334    30.0\n",
       "9335    29.4\n",
       "9336    28.9\n",
       "9337    22.8\n",
       "9338    19.9\n",
       "9339    17.5\n",
       "9340    16.4\n",
       "9341    15.5\n",
       "9342    14.3\n",
       "9343    14.2\n",
       "9344    13.8\n",
       "9345    12.1\n",
       "9346    11.3\n",
       "9347    11.8\n",
       "9348    10.4\n",
       "9349     9.5\n",
       "9350     9.7\n",
       "9351    13.5\n",
       "9352    18.2\n",
       "9353    21.9\n",
       "9354    24.3\n",
       "9355    26.9\n",
       "9356    28.3\n",
       "Name: T_t-1, Length: 9357, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['T_t-1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_naive = df[['T','T_t-1']][1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>T</th>\n",
       "      <th>T_t-1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13.3</td>\n",
       "      <td>13.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11.9</td>\n",
       "      <td>13.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.0</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11.2</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11.2</td>\n",
       "      <td>11.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11.3</td>\n",
       "      <td>11.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10.7</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.7</td>\n",
       "      <td>10.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.3</td>\n",
       "      <td>10.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10.1</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11.0</td>\n",
       "      <td>10.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10.5</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10.2</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10.8</td>\n",
       "      <td>10.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10.5</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10.8</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10.5</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>9.5</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>8.3</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>8.0</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>8.3</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>9.7</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>9.8</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10.3</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>9.7</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>9.6</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>9.1</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>8.2</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>8.2</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>8.3</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>9327</th>\n",
       "      <td>17.8</td>\n",
       "      <td>13.5</td>\n",
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       "    <tr>\n",
       "      <th>9328</th>\n",
       "      <td>21.1</td>\n",
       "      <td>17.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9329</th>\n",
       "      <td>24.0</td>\n",
       "      <td>21.1</td>\n",
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       "    <tr>\n",
       "      <th>9330</th>\n",
       "      <td>26.5</td>\n",
       "      <td>24.0</td>\n",
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       "    <tr>\n",
       "      <th>9331</th>\n",
       "      <td>28.7</td>\n",
       "      <td>26.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9332</th>\n",
       "      <td>28.5</td>\n",
       "      <td>28.7</td>\n",
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       "    <tr>\n",
       "      <th>9333</th>\n",
       "      <td>30.0</td>\n",
       "      <td>28.5</td>\n",
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       "    <tr>\n",
       "      <th>9334</th>\n",
       "      <td>29.4</td>\n",
       "      <td>30.0</td>\n",
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       "    <tr>\n",
       "      <th>9335</th>\n",
       "      <td>28.9</td>\n",
       "      <td>29.4</td>\n",
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       "    <tr>\n",
       "      <th>9336</th>\n",
       "      <td>22.8</td>\n",
       "      <td>28.9</td>\n",
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       "    <tr>\n",
       "      <th>9337</th>\n",
       "      <td>19.9</td>\n",
       "      <td>22.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9338</th>\n",
       "      <td>17.5</td>\n",
       "      <td>19.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9339</th>\n",
       "      <td>16.4</td>\n",
       "      <td>17.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9340</th>\n",
       "      <td>15.5</td>\n",
       "      <td>16.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9341</th>\n",
       "      <td>14.3</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9342</th>\n",
       "      <td>14.2</td>\n",
       "      <td>14.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9343</th>\n",
       "      <td>13.8</td>\n",
       "      <td>14.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9344</th>\n",
       "      <td>12.1</td>\n",
       "      <td>13.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9345</th>\n",
       "      <td>11.3</td>\n",
       "      <td>12.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9346</th>\n",
       "      <td>11.8</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9347</th>\n",
       "      <td>10.4</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9348</th>\n",
       "      <td>9.5</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9349</th>\n",
       "      <td>9.7</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9350</th>\n",
       "      <td>13.5</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9351</th>\n",
       "      <td>18.2</td>\n",
       "      <td>13.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9352</th>\n",
       "      <td>21.9</td>\n",
       "      <td>18.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9353</th>\n",
       "      <td>24.3</td>\n",
       "      <td>21.9</td>\n",
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       "    <tr>\n",
       "      <th>9354</th>\n",
       "      <td>26.9</td>\n",
       "      <td>24.3</td>\n",
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       "    <tr>\n",
       "      <th>9355</th>\n",
       "      <td>28.3</td>\n",
       "      <td>26.9</td>\n",
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       "    <tr>\n",
       "      <th>9356</th>\n",
       "      <td>28.5</td>\n",
       "      <td>28.3</td>\n",
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      ],
      "text/plain": [
       "         T  T_t-1\n",
       "1     13.3   13.6\n",
       "2     11.9   13.3\n",
       "3     11.0   11.9\n",
       "4     11.2   11.0\n",
       "5     11.2   11.2\n",
       "6     11.3   11.2\n",
       "7     10.7   11.3\n",
       "8     10.7   10.7\n",
       "9     10.3   10.7\n",
       "10    10.1   10.3\n",
       "11    11.0   10.1\n",
       "12    10.5   11.0\n",
       "13    10.2   10.5\n",
       "14    10.8   10.2\n",
       "15    10.5   10.8\n",
       "16    10.8   10.5\n",
       "17    10.5   10.8\n",
       "18     9.5   10.5\n",
       "19     8.3    9.5\n",
       "20     8.0    8.3\n",
       "21     8.3    8.0\n",
       "22     9.7    8.3\n",
       "23     9.8    9.7\n",
       "24    10.3    9.8\n",
       "25     9.7   10.3\n",
       "26     9.6    9.7\n",
       "27     9.1    9.6\n",
       "28     8.2    9.1\n",
       "29     8.2    8.2\n",
       "30     8.3    8.2\n",
       "...    ...    ...\n",
       "9327  17.8   13.5\n",
       "9328  21.1   17.8\n",
       "9329  24.0   21.1\n",
       "9330  26.5   24.0\n",
       "9331  28.7   26.5\n",
       "9332  28.5   28.7\n",
       "9333  30.0   28.5\n",
       "9334  29.4   30.0\n",
       "9335  28.9   29.4\n",
       "9336  22.8   28.9\n",
       "9337  19.9   22.8\n",
       "9338  17.5   19.9\n",
       "9339  16.4   17.5\n",
       "9340  15.5   16.4\n",
       "9341  14.3   15.5\n",
       "9342  14.2   14.3\n",
       "9343  13.8   14.2\n",
       "9344  12.1   13.8\n",
       "9345  11.3   12.1\n",
       "9346  11.8   11.3\n",
       "9347  10.4   11.8\n",
       "9348   9.5   10.4\n",
       "9349   9.7    9.5\n",
       "9350  13.5    9.7\n",
       "9351  18.2   13.5\n",
       "9352  21.9   18.2\n",
       "9353  24.3   21.9\n",
       "9354  26.9   24.3\n",
       "9355  28.3   26.9\n",
       "9356  28.5   28.3\n",
       "\n",
       "[9356 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_naive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import metrics\n",
    "from math import sqrt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "true = df_naive['T']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction = df_naive['T_t-1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "error = sqrt(metrics.mean_squared_error(true,prediction))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.901140576492974"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE for Naive Method 2:  12.901140576492974\n"
     ]
    }
   ],
   "source": [
    "print ('RMSE for Naive Method 2: ', error)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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