diff --git a/Tech Challenge.ipynb b/Tech Challenge.ipynb
new file mode 100644
index 0000000..dea1609
--- /dev/null
+++ b/Tech Challenge.ipynb	
@@ -0,0 +1,1349 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "id": "760d6a49-60cf-42bc-a13f-6c8926f3d62c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "2afe2e2c-512f-4062-91c2-65e244ab610d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv('measurements.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "f9d99dc2-bd2f-4168-9a5b-cb515873401f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>distance</th>\n",
+       "      <th>consume</th>\n",
+       "      <th>speed</th>\n",
+       "      <th>temp_inside</th>\n",
+       "      <th>temp_outside</th>\n",
+       "      <th>specials</th>\n",
+       "      <th>gas_type</th>\n",
+       "      <th>AC</th>\n",
+       "      <th>rain</th>\n",
+       "      <th>sun</th>\n",
+       "      <th>refill liters</th>\n",
+       "      <th>refill gas</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>28</td>\n",
+       "      <td>5</td>\n",
+       "      <td>26</td>\n",
+       "      <td>21,5</td>\n",
+       "      <td>12</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>45</td>\n",
+       "      <td>E10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12</td>\n",
+       "      <td>4,2</td>\n",
+       "      <td>30</td>\n",
+       "      <td>21,5</td>\n",
+       "      <td>13</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11,2</td>\n",
+       "      <td>5,5</td>\n",
+       "      <td>38</td>\n",
+       "      <td>21,5</td>\n",
+       "      <td>15</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>12,9</td>\n",
+       "      <td>3,9</td>\n",
+       "      <td>36</td>\n",
+       "      <td>21,5</td>\n",
+       "      <td>14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>18,5</td>\n",
+       "      <td>4,5</td>\n",
+       "      <td>46</td>\n",
+       "      <td>21,5</td>\n",
+       "      <td>15</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>383</th>\n",
+       "      <td>16</td>\n",
+       "      <td>3,7</td>\n",
+       "      <td>39</td>\n",
+       "      <td>24,5</td>\n",
+       "      <td>18</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>384</th>\n",
+       "      <td>16,1</td>\n",
+       "      <td>4,3</td>\n",
+       "      <td>38</td>\n",
+       "      <td>25</td>\n",
+       "      <td>31</td>\n",
+       "      <td>AC</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>385</th>\n",
+       "      <td>16</td>\n",
+       "      <td>3,8</td>\n",
+       "      <td>45</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>386</th>\n",
+       "      <td>15,4</td>\n",
+       "      <td>4,6</td>\n",
+       "      <td>42</td>\n",
+       "      <td>25</td>\n",
+       "      <td>31</td>\n",
+       "      <td>AC</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>387</th>\n",
+       "      <td>14,7</td>\n",
+       "      <td>5</td>\n",
+       "      <td>25</td>\n",
+       "      <td>25</td>\n",
+       "      <td>30</td>\n",
+       "      <td>AC</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>388 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    distance consume  speed temp_inside  temp_outside specials gas_type  AC  \\\n",
+       "0         28       5     26        21,5            12      NaN      E10   0   \n",
+       "1         12     4,2     30        21,5            13      NaN      E10   0   \n",
+       "2       11,2     5,5     38        21,5            15      NaN      E10   0   \n",
+       "3       12,9     3,9     36        21,5            14      NaN      E10   0   \n",
+       "4       18,5     4,5     46        21,5            15      NaN      E10   0   \n",
+       "..       ...     ...    ...         ...           ...      ...      ...  ..   \n",
+       "383       16     3,7     39        24,5            18      NaN     SP98   0   \n",
+       "384     16,1     4,3     38          25            31       AC     SP98   1   \n",
+       "385       16     3,8     45          25            19      NaN     SP98   0   \n",
+       "386     15,4     4,6     42          25            31       AC     SP98   1   \n",
+       "387     14,7       5     25          25            30       AC     SP98   1   \n",
+       "\n",
+       "     rain  sun refill liters refill gas  \n",
+       "0       0    0            45        E10  \n",
+       "1       0    0           NaN        NaN  \n",
+       "2       0    0           NaN        NaN  \n",
+       "3       0    0           NaN        NaN  \n",
+       "4       0    0           NaN        NaN  \n",
+       "..    ...  ...           ...        ...  \n",
+       "383     0    0           NaN        NaN  \n",
+       "384     0    0           NaN        NaN  \n",
+       "385     0    0           NaN        NaN  \n",
+       "386     0    0           NaN        NaN  \n",
+       "387     0    0           NaN        NaN  \n",
+       "\n",
+       "[388 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# OVERVIEW \n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "id": "241e164b-4ace-4c07-9235-d3051239a4cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>speed</th>\n",
+       "      <th>temp_outside</th>\n",
+       "      <th>AC</th>\n",
+       "      <th>rain</th>\n",
+       "      <th>sun</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>388.000000</td>\n",
+       "      <td>388.000000</td>\n",
+       "      <td>388.000000</td>\n",
+       "      <td>388.000000</td>\n",
+       "      <td>388.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>41.927835</td>\n",
+       "      <td>11.358247</td>\n",
+       "      <td>0.077320</td>\n",
+       "      <td>0.123711</td>\n",
+       "      <td>0.082474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>13.598524</td>\n",
+       "      <td>6.991542</td>\n",
+       "      <td>0.267443</td>\n",
+       "      <td>0.329677</td>\n",
+       "      <td>0.275441</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>14.000000</td>\n",
+       "      <td>-5.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>32.750000</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>40.500000</td>\n",
+       "      <td>10.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>50.000000</td>\n",
+       "      <td>16.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>90.000000</td>\n",
+       "      <td>31.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            speed  temp_outside          AC        rain         sun\n",
+       "count  388.000000    388.000000  388.000000  388.000000  388.000000\n",
+       "mean    41.927835     11.358247    0.077320    0.123711    0.082474\n",
+       "std     13.598524      6.991542    0.267443    0.329677    0.275441\n",
+       "min     14.000000     -5.000000    0.000000    0.000000    0.000000\n",
+       "25%     32.750000      7.000000    0.000000    0.000000    0.000000\n",
+       "50%     40.500000     10.000000    0.000000    0.000000    0.000000\n",
+       "75%     50.000000     16.000000    0.000000    0.000000    0.000000\n",
+       "max     90.000000     31.000000    1.000000    1.000000    1.000000"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "id": "576fcf43-00c1-446d-afd2-f7d0e9b768fe",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 388 entries, 0 to 387\n",
+      "Data columns (total 12 columns):\n",
+      " #   Column         Non-Null Count  Dtype \n",
+      "---  ------         --------------  ----- \n",
+      " 0   distance       388 non-null    object\n",
+      " 1   consume        388 non-null    object\n",
+      " 2   speed          388 non-null    int64 \n",
+      " 3   temp_inside    376 non-null    object\n",
+      " 4   temp_outside   388 non-null    int64 \n",
+      " 5   specials       93 non-null     object\n",
+      " 6   gas_type       388 non-null    object\n",
+      " 7   AC             388 non-null    int64 \n",
+      " 8   rain           388 non-null    int64 \n",
+      " 9   sun            388 non-null    int64 \n",
+      " 10  refill liters  13 non-null     object\n",
+      " 11  refill gas     13 non-null     object\n",
+      "dtypes: int64(5), object(7)\n",
+      "memory usage: 36.5+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "830a9e9f-aeb5-4535-8e62-2069ad32d175",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# df2 = pd.read_excel('measurements2.xlsx')  the same "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "1120981e-2081-4fee-9dc7-92b9e366242e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['distance', 'consume', 'speed', 'temp_inside', 'temp_outside',\n",
+       "       'specials', 'gas_type', 'AC', 'rain', 'sun', 'refill liters',\n",
+       "       'refill gas'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "id": "b3ae3473-0b1f-4fef-9ae3-f8b9c2a7246e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "distance         0\n",
+       "consume          0\n",
+       "speed            0\n",
+       "temp_inside      0\n",
+       "temp_outside     0\n",
+       "specials         0\n",
+       "gas_type         0\n",
+       "AC               0\n",
+       "rain             0\n",
+       "sun              0\n",
+       "refill liters    0\n",
+       "refill gas       0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 103,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# CLEANING\n",
+    "\n",
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "923bf12b-dccd-4865-a3e6-518d7d98dc41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df['temp_inside'] = df['temp_inside'].str.replace(',', '.')\n",
+    "df['temp_inside'] = pd.to_numeric(df['temp_inside'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "id": "47e4e25d-1e4b-4867-87a4-a21318658f3a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/jr/tzjk1k550jnfd3ck0z2tl_nr0000gn/T/ipykernel_3443/1485448771.py:1: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
+      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
+      "\n",
+      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
+      "\n",
+      "\n",
+      "  df['temp_inside'].fillna(df['temp_inside'].mean(), inplace=True)\n"
+     ]
+    }
+   ],
+   "source": [
+    "df['temp_inside'].fillna(df['temp_inside'].mean(), inplace=True)\n",
+    "df['specials'] = df['specials'].fillna('No Specials')\n",
+    "df['refill liters'] = df['refill liters'].fillna(0)\n",
+    "df['refill gas'] = df['refill gas'].fillna(0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "id": "65f8bc71-d43c-4930-ba77-896dcec21512",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>distance</th>\n",
+       "      <th>consume</th>\n",
+       "      <th>speed</th>\n",
+       "      <th>temp_inside</th>\n",
+       "      <th>temp_outside</th>\n",
+       "      <th>specials</th>\n",
+       "      <th>gas_type</th>\n",
+       "      <th>AC</th>\n",
+       "      <th>rain</th>\n",
+       "      <th>sun</th>\n",
+       "      <th>refill liters</th>\n",
+       "      <th>refill gas</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>28</td>\n",
+       "      <td>5</td>\n",
+       "      <td>26</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>12</td>\n",
+       "      <td>No Specials</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>45</td>\n",
+       "      <td>E10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12</td>\n",
+       "      <td>4,2</td>\n",
+       "      <td>30</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>13</td>\n",
+       "      <td>No Specials</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11,2</td>\n",
+       "      <td>5,5</td>\n",
+       "      <td>38</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>15</td>\n",
+       "      <td>No Specials</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>12,9</td>\n",
+       "      <td>3,9</td>\n",
+       "      <td>36</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>14</td>\n",
+       "      <td>No Specials</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>18,5</td>\n",
+       "      <td>4,5</td>\n",
+       "      <td>46</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>15</td>\n",
+       "      <td>No Specials</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>383</th>\n",
+       "      <td>16</td>\n",
+       "      <td>3,7</td>\n",
+       "      <td>39</td>\n",
+       "      <td>24.5</td>\n",
+       "      <td>18</td>\n",
+       "      <td>No Specials</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>384</th>\n",
+       "      <td>16,1</td>\n",
+       "      <td>4,3</td>\n",
+       "      <td>38</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>AC</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>385</th>\n",
+       "      <td>16</td>\n",
+       "      <td>3,8</td>\n",
+       "      <td>45</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>19</td>\n",
+       "      <td>No Specials</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>386</th>\n",
+       "      <td>15,4</td>\n",
+       "      <td>4,6</td>\n",
+       "      <td>42</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>AC</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>387</th>\n",
+       "      <td>14,7</td>\n",
+       "      <td>5</td>\n",
+       "      <td>25</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>AC</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>388 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    distance consume  speed  temp_inside  temp_outside     specials gas_type  \\\n",
+       "0         28       5     26         21.5            12  No Specials      E10   \n",
+       "1         12     4,2     30         21.5            13  No Specials      E10   \n",
+       "2       11,2     5,5     38         21.5            15  No Specials      E10   \n",
+       "3       12,9     3,9     36         21.5            14  No Specials      E10   \n",
+       "4       18,5     4,5     46         21.5            15  No Specials      E10   \n",
+       "..       ...     ...    ...          ...           ...          ...      ...   \n",
+       "383       16     3,7     39         24.5            18  No Specials     SP98   \n",
+       "384     16,1     4,3     38         25.0            31           AC     SP98   \n",
+       "385       16     3,8     45         25.0            19  No Specials     SP98   \n",
+       "386     15,4     4,6     42         25.0            31           AC     SP98   \n",
+       "387     14,7       5     25         25.0            30           AC     SP98   \n",
+       "\n",
+       "     AC  rain  sun refill liters refill gas  \n",
+       "0     0     0    0            45        E10  \n",
+       "1     0     0    0             0          0  \n",
+       "2     0     0    0             0          0  \n",
+       "3     0     0    0             0          0  \n",
+       "4     0     0    0             0          0  \n",
+       "..   ..   ...  ...           ...        ...  \n",
+       "383   0     0    0             0          0  \n",
+       "384   1     0    0             0          0  \n",
+       "385   0     0    0             0          0  \n",
+       "386   1     0    0             0          0  \n",
+       "387   1     0    0             0          0  \n",
+       "\n",
+       "[388 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "id": "67ccd53a-c493-49a7-a6d2-4ebd28f8943c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 388 entries, 0 to 387\n",
+      "Data columns (total 2 columns):\n",
+      " #   Column    Non-Null Count  Dtype  \n",
+      "---  ------    --------------  -----  \n",
+      " 0   consume   388 non-null    float64\n",
+      " 1   distance  388 non-null    float64\n",
+      "dtypes: float64(2)\n",
+      "memory usage: 6.2 KB\n",
+      "None\n"
+     ]
+    }
+   ],
+   "source": [
+    "df['distance'] = df['distance'].str.replace(',', '.')\n",
+    "df['consume'] = df['consume'].str.replace(',', '.')\n",
+    "df['distance'] = pd.to_numeric(df['distance'])\n",
+    "df['consume'] = pd.to_numeric(df['consume'])\n",
+    "print(df[['consume', 'distance']].info())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "id": "dec481f5-542e-428c-a100-9e86e3d1f747",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.to_csv('cleaned.csv', index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "id": "f4158215-6a8f-4244-b42f-b2f6bb425fda",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "gas_type\n",
+      "E10     0.436056\n",
+      "SP98    0.506136\n",
+      "Name: efficiency, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 1. DISTANCE \n",
+    "\n",
+    "df['efficiency'] = df['consume']/ df['distance']\n",
+    "print(df.groupby('gas_type')['efficiency'].mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "id": "8b4f0341-6fe0-4c7d-a9c3-d317c3de9f1a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "efficiency_by_gas = df.groupby('gas_type')['efficiency'].mean().reset_index()\n",
+    "plt.figure(figsize=(8, 5))\n",
+    "sns.barplot(data=efficiency_by_gas, x='gas_type', y='efficiency')\n",
+    "plt.title('Mean efficiency per gas type')\n",
+    "plt.xlabel('gas_type')\n",
+    "plt.ylabel('efficiency per distance')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "id": "f0887a9c-85af-4ce8-836e-bbf3e43a0b4a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x1306b8260>"
+      ]
+     },
+     "execution_count": 139,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(df['distance'], df['consume'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bc95c355-188f-4347-962f-931a5dd39e53",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# decreasing consumption with higher distance/ high fuekl consumption for short distance "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "8081da5e-a440-47ee-8578-5fe7e51f867b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gas_type</th>\n",
+       "      <th>consume</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>E10</td>\n",
+       "      <td>4.931250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>SP98</td>\n",
+       "      <td>4.899123</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  gas_type   consume\n",
+       "0      E10  4.931250\n",
+       "1     SP98  4.899123"
+      ]
+     },
+     "execution_count": 123,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 2. CONSUME\n",
+    "\n",
+    "consume_by_gas = df.groupby('gas_type')['consume'].mean().reset_index()\n",
+    "consume_by_gas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4502bc7b-8701-4cb2-8174-1be26c0b421f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# the mean consumption of SP98 is a little bit lower than for E 10, but as we see earlier the efficiency (consumption per distance) is  lower for E 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "id": "a8bfecb2-c3fc-4e08-9828-5573aaf33c49",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gas_type</th>\n",
+       "      <th>speed</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>E10</td>\n",
+       "      <td>43.506250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>SP98</td>\n",
+       "      <td>40.820175</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  gas_type      speed\n",
+       "0      E10  43.506250\n",
+       "1     SP98  40.820175"
+      ]
+     },
+     "execution_count": 131,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 3. SPEED\n",
+    "\n",
+    "speed = df.groupby('gas_type')['speed'].mean().reset_index()\n",
+    "speed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 143,
+   "id": "ecaaa606-c3d7-4170-868f-c948691bfb75",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gas_type</th>\n",
+       "      <th>temp_inside</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>E10</td>\n",
+       "      <td>21.917429</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>SP98</td>\n",
+       "      <td>21.938007</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  gas_type  temp_inside\n",
+       "0      E10    21.917429\n",
+       "1     SP98    21.938007"
+      ]
+     },
+     "execution_count": 143,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 4. TEMP_INSIDE  (almost the same: no insights here)\n",
+    "\n",
+    "temp_inside = df.groupby('gas_type')['temp_inside'].mean().reset_index()\n",
+    "temp_inside"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "id": "6580d6ed-530a-4bd6-9673-875054f83d8d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gas_type</th>\n",
+       "      <th>temp_outside</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>E10</td>\n",
+       "      <td>10.11875</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>SP98</td>\n",
+       "      <td>12.22807</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  gas_type  temp_outside\n",
+       "0      E10      10.11875\n",
+       "1     SP98      12.22807"
+      ]
+     },
+     "execution_count": 145,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 5. TEMP_OUTSIDE\n",
+    "\n",
+    "temp_outside = df.groupby('gas_type')['temp_outside'].mean().reset_index()\n",
+    "temp_outside"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5b865e7b-43dd-4ecd-8c19-673d70d59c36",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# lower temperatures sometimes increase consumption, so that could explain why the average consumption of E10 is slightly higher "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 155,
+   "id": "20b7abad-388b-4752-b3eb-2a3adf6fa5de",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['No Specials', 'AC rain', 'AC', 'rain', 'snow', 'AC snow',\n",
+       "       'half rain half sun', 'sun', 'AC sun', 'sun ac', 'ac', 'AC Sun',\n",
+       "       'ac rain'], dtype=object)"
+      ]
+     },
+     "execution_count": 155,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 6. SPECIALS\n",
+    "\n",
+    "df['specials'].unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 157,
+   "id": "704970e3-0cf8-443f-b7d0-3ffe8bd9e949",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "specials            gas_type\n",
+      "AC                  E10         5.000000\n",
+      "                    SP98        4.620000\n",
+      "AC Sun              E10         4.800000\n",
+      "AC rain             E10         4.500000\n",
+      "                    SP98        5.771429\n",
+      "AC snow             E10         7.100000\n",
+      "AC sun              E10         4.800000\n",
+      "No Specials         E10         4.897692\n",
+      "                    SP98        4.903030\n",
+      "ac                  E10         4.600000\n",
+      "                    SP98        4.700000\n",
+      "ac rain             E10         5.100000\n",
+      "half rain half sun  SP98        4.700000\n",
+      "rain                E10         5.700000\n",
+      "                    SP98        5.305000\n",
+      "snow                SP98        5.166667\n",
+      "sun                 E10         4.350000\n",
+      "                    SP98        4.235294\n",
+      "sun ac              SP98        4.433333\n",
+      "Name: consume, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "mean_consume = df.groupby(['specials', 'gas_type'])['consume'].mean()\n",
+    "print(mean_consume)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 159,
+   "id": "5bea6bf4-34f4-428d-8d20-a731c1cf2592",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "gas_type                 E10      SP98\n",
+      "specials                              \n",
+      "AC                  5.000000  4.620000\n",
+      "AC Sun              4.800000       NaN\n",
+      "AC rain             4.500000  5.771429\n",
+      "AC snow             7.100000       NaN\n",
+      "AC sun              4.800000       NaN\n",
+      "No Specials         4.897692  4.903030\n",
+      "ac                  4.600000  4.700000\n",
+      "ac rain             5.100000       NaN\n",
+      "half rain half sun       NaN  4.700000\n",
+      "rain                5.700000  5.305000\n",
+      "snow                     NaN  5.166667\n",
+      "sun                 4.350000  4.235294\n",
+      "sun ac                   NaN  4.433333\n"
+     ]
+    }
+   ],
+   "source": [
+    "pivot_table = df.pivot_table(\n",
+    "    values='consume',\n",
+    "    index='specials',\n",
+    "    columns='gas_type',\n",
+    "    aggfunc='mean'\n",
+    ")\n",
+    "\n",
+    "print(pivot_table)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2b05b3de-8b27-4415-982b-2407c4720531",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# no big differences here"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5829e6a4-9fe4-4dc4-b930-9f2de209722e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# All in all I would recommand to go with the E10 combustible: most efficient"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/cleaned.csv b/cleaned.csv
new file mode 100644
index 0000000..2786b73
--- /dev/null
+++ b/cleaned.csv
@@ -0,0 +1,389 @@
+distance,consume,speed,temp_inside,temp_outside,specials,gas_type,AC,rain,sun,refill liters,refill gas,efficiency
+28.0,5.0,26,21.5,12,No Specials,E10,0,0,0,45,E10,0.17857142857142858
+12.0,4.2,30,21.5,13,No Specials,E10,0,0,0,0,0,0.35000000000000003
+11.2,5.5,38,21.5,15,No Specials,E10,0,0,0,0,0,0.4910714285714286
+12.9,3.9,36,21.5,14,No Specials,E10,0,0,0,0,0,0.3023255813953488
+18.5,4.5,46,21.5,15,No Specials,E10,0,0,0,0,0,0.24324324324324326
+8.3,6.4,50,21.5,10,No Specials,E10,0,0,0,0,0,0.7710843373493975
+7.8,4.4,43,21.5,11,No Specials,E10,0,0,0,0,0,0.5641025641025642
+12.3,5.0,40,21.5,6,No Specials,E10,0,0,0,0,0,0.4065040650406504
+4.9,6.4,26,21.5,4,No Specials,E10,0,0,0,0,0,1.3061224489795917
+11.9,5.3,30,21.5,9,No Specials,E10,0,0,0,0,0,0.4453781512605042
+12.4,5.6,42,21.5,4,No Specials,E10,0,0,0,0,0,0.4516129032258064
+11.8,4.6,38,21.5,0,No Specials,E10,0,0,0,0,0,0.38983050847457623
+12.3,5.9,59,21.5,10,No Specials,E10,0,0,0,0,0,0.4796747967479675
+24.7,5.1,58,21.5,12,No Specials,E10,0,0,0,0,0,0.20647773279352225
+12.4,4.7,46,21.5,11,No Specials,E10,0,0,0,0,0,0.3790322580645161
+17.3,5.1,24,21.5,5,No Specials,E10,0,0,0,0,0,0.29479768786127164
+33.4,5.6,36,21.5,3,No Specials,E10,0,0,0,0,0,0.16766467065868262
+11.8,5.1,32,21.5,3,No Specials,E10,0,0,0,0,0,0.43220338983050843
+25.9,4.9,39,21.5,8,No Specials,E10,0,0,0,0,0,0.1891891891891892
+11.8,4.7,40,21.5,4,No Specials,E10,0,0,0,0,0,0.3983050847457627
+25.3,5.5,32,21.5,3,No Specials,E10,0,0,0,0,0,0.21739130434782608
+14.2,5.9,38,21.5,1,No Specials,E10,0,0,0,0,0,0.41549295774647893
+17.9,5.7,37,21.5,1,No Specials,E10,0,0,0,0,0,0.3184357541899442
+11.8,4.7,36,21.5,1,No Specials,E10,0,0,0,0,0,0.3983050847457627
+12.3,5.9,62,21.5,6,No Specials,E10,0,0,0,0,0,0.4796747967479675
+12.4,4.1,57,21.5,9,No Specials,E10,0,0,0,0,0,0.33064516129032256
+18.4,5.7,21,22.5,2,No Specials,E10,0,0,0,0,0,0.3097826086956522
+18.4,5.8,28,21.5,3,No Specials,E10,0,0,0,0,0,0.31521739130434784
+18.3,5.5,29,21.5,1,No Specials,E10,0,0,0,0,0,0.3005464480874317
+18.4,5.7,35,21.5,4,No Specials,E10,0,0,0,0,0,0.3097826086956522
+12.3,5.3,51,21.5,11,No Specials,E10,0,0,0,0,0,0.4308943089430894
+11.8,5.0,29,21.5,10,No Specials,E10,0,0,0,0,0,0.423728813559322
+12.3,5.6,58,21.5,8,No Specials,E10,0,0,0,0,0,0.4552845528455284
+32.6,4.8,40,21.5,7,No Specials,E10,0,0,0,0,0,0.14723926380368096
+19.0,4.3,36,21.5,7,No Specials,E10,0,0,0,0,0,0.2263157894736842
+12.1,5.7,36,21.5,8,No Specials,E10,0,0,0,0,0,0.4710743801652893
+20.0,5.2,37,21.5,4,No Specials,E10,0,0,0,0,0,0.26
+4.9,7.4,26,21.5,6,No Specials,E10,0,0,0,0,0,1.510204081632653
+11.8,4.8,23,21.5,9,No Specials,E10,0,0,0,0,0,0.4067796610169491
+12.3,6.5,58,21.5,7,No Specials,E10,0,0,0,0,0,0.5284552845528455
+12.4,4.0,55,21.5,7,AC rain,E10,1,1,0,0,0,0.3225806451612903
+4.5,5.0,29,21.5,7,AC,E10,1,0,0,0,0,1.1111111111111112
+11.7,4.6,37,21.5,6,No Specials,E10,0,0,0,0,0,0.39316239316239315
+10.2,4.3,44,21.5,7,No Specials,E10,0,0,0,0,0,0.4215686274509804
+5.4,3.3,32,21.5,7,No Specials,SP98,0,0,0,"37,6",SP98,0.611111111111111
+2.0,9.9,21,21.5,4,No Specials,SP98,0,0,0,0,0,4.95
+14.2,5.1,32,21.5,7,No Specials,SP98,0,0,0,0,0,0.35915492957746475
+16.0,4.9,25,21.5,8,No Specials,SP98,0,0,0,0,0,0.30625
+11.8,4.9,25,21.5,11,No Specials,SP98,0,0,0,0,0,0.4152542372881356
+27.3,4.7,36,21.5,10,No Specials,SP98,0,0,0,0,0,0.17216117216117216
+11.8,5.1,29,21.5,5,rain,SP98,0,1,0,0,0,0.43220338983050843
+10.6,4.9,63,21.5,6,No Specials,SP98,0,0,0,0,0,0.4622641509433963
+11.6,4.2,61,21.5,7,No Specials,SP98,0,0,0,0,0,0.3620689655172414
+13.1,6.1,46,21.5,6,rain,SP98,0,1,0,0,0,0.46564885496183206
+6.1,6.4,28,21.5,8,No Specials,SP98,0,0,0,0,0,1.0491803278688525
+153.5,4.9,82,21.5,3,rain,SP98,0,1,0,0,0,0.03192182410423453
+11.8,4.9,24,21.5,7,No Specials,SP98,0,0,0,0,0,0.4152542372881356
+12.3,6.2,61,21.5,8,No Specials,SP98,0,0,0,0,0,0.5040650406504065
+12.4,4.2,57,21.5,8,No Specials,SP98,0,0,0,0,0,0.33870967741935487
+12.3,5.7,52,21.5,8,rain,SP98,0,1,0,0,0,0.46341463414634143
+2.9,7.9,18,21.5,9,AC rain,SP98,1,1,0,0,0,2.724137931034483
+2.1,12.2,23,21.5,9,No Specials,SP98,1,1,0,0,0,5.809523809523809
+9.8,5.8,24,21.5,6,No Specials,SP98,0,0,0,0,0,0.5918367346938775
+6.8,5.3,26,21.5,6,No Specials,SP98,0,0,0,0,0,0.7794117647058824
+12.4,5.4,24,21.5,7,No Specials,SP98,0,0,0,0,0,0.43548387096774194
+12.4,4.7,57,21.5,8,No Specials,SP98,0,0,0,0,0,0.3790322580645161
+11.8,4.6,41,21.5,6,No Specials,SP98,0,0,0,0,0,0.38983050847457623
+12.3,5.4,55,21.5,8,No Specials,SP98,0,0,0,0,0,0.43902439024390244
+14.0,4.3,40,21.5,8,No Specials,SP98,0,0,0,0,0,0.3071428571428571
+11.8,4.5,37,21.5,4,AC,SP98,1,0,0,0,0,0.3813559322033898
+12.3,5.2,55,21.5,12,No Specials,SP98,0,0,0,0,0,0.4227642276422764
+2.0,6.2,20,21.5,10,No Specials,SP98,0,0,0,0,0,3.1
+13.9,5.1,29,21.5,6,No Specials,SP98,0,0,0,0,0,0.3669064748201438
+9.7,3.9,42,21.5,8,No Specials,SP98,0,0,0,0,0,0.4020618556701031
+11.6,5.0,25,21.5,6,No Specials,SP98,0,0,0,0,0,0.4310344827586207
+14.2,5.4,38,21.5,7,No Specials,SP98,0,0,0,0,0,0.3802816901408451
+11.8,4.5,39,21.5,6,No Specials,SP98,0,0,0,0,0,0.3813559322033898
+24.8,5.1,50,21.5,9,No Specials,SP98,0,0,0,0,0,0.20564516129032256
+12.4,4.7,56,21.5,7,No Specials,SP98,0,0,0,0,0,0.3790322580645161
+34.8,4.0,28,20.0,4,No Specials,SP98,0,0,0,0,0,0.1149425287356322
+14.2,5.4,36,20.0,6,No Specials,SP98,0,0,0,0,0,0.3802816901408451
+5.2,4.5,39,20.0,10,No Specials,SP98,0,0,0,0,0,0.8653846153846153
+10.5,3.6,42,20.0,10,No Specials,SP98,0,0,0,"37,7",SP98,0.34285714285714286
+12.3,5.2,57,20.0,10,No Specials,SP98,0,0,0,0,0,0.4227642276422764
+11.8,4.9,25,20.0,11,No Specials,SP98,0,0,0,0,0,0.4152542372881356
+12.3,6.2,58,20.0,11,rain,SP98,0,1,0,0,0,0.5040650406504065
+13.2,4.3,51,20.0,11,rain,SP98,0,1,0,0,0,0.32575757575757575
+13.0,5.0,45,20.0,11,rain,SP98,0,1,0,0,0,0.38461538461538464
+12.9,5.1,32,20.0,11,No Specials,SP98,0,0,0,0,0,0.3953488372093023
+13.9,5.6,22,20.0,8,No Specials,SP98,0,0,0,0,0,0.40287769784172656
+11.8,4.3,37,20.0,6,No Specials,SP98,0,0,0,0,0,0.3644067796610169
+12.2,5.8,60,20.0,11,No Specials,SP98,0,0,0,0,0,0.4754098360655738
+12.5,4.0,51,20.0,13,No Specials,SP98,0,0,0,0,0,0.32
+12.4,4.7,43,21.929521276595743,10,No Specials,SP98,0,0,0,0,0,0.3790322580645161
+11.8,5.9,21,20.0,9,AC rain,SP98,1,1,0,0,0,0.5
+11.8,5.3,52,21.929521276595743,11,No Specials,SP98,0,0,0,0,0,0.4491525423728813
+12.5,4.2,57,20.0,11,No Specials,SP98,0,0,0,0,0,0.336
+15.7,5.3,33,21.929521276595743,9,No Specials,SP98,0,0,0,0,0,0.3375796178343949
+12.9,5.7,35,21.929521276595743,9,No Specials,SP98,0,0,0,0,0,0.4418604651162791
+6.4,4.4,37,21.929521276595743,10,No Specials,SP98,0,0,0,0,0,0.6875
+5.3,4.1,34,21.929521276595743,9,No Specials,SP98,0,0,0,0,0,0.7735849056603773
+26.2,5.8,71,21.0,8,AC rain,SP98,1,1,0,0,0,0.22137404580152673
+18.8,5.0,62,21.929521276595743,9,rain,SP98,0,1,0,0,0,0.26595744680851063
+4.9,6.9,25,21.0,12,rain,SP98,0,1,0,0,0,1.4081632653061225
+12.4,5.4,18,21.0,11,AC rain,SP98,1,1,0,0,0,0.43548387096774194
+22.9,5.3,45,20.5,7,No Specials,SP98,0,0,0,0,0,0.2314410480349345
+162.7,5.5,75,23.0,1,No Specials,SP98,0,0,0,45,SP98,0.03380454824830977
+4.9,6.5,26,21.0,1,No Specials,SP98,0,0,0,0,0,1.3265306122448979
+11.8,4.7,36,21.0,4,No Specials,SP98,0,0,0,0,0,0.3983050847457627
+16.6,5.1,56,21.0,7,No Specials,SP98,0,0,0,0,0,0.30722891566265054
+12.4,5.7,37,21.0,7,No Specials,SP98,0,0,0,0,0,0.4596774193548387
+15.9,5.4,25,21.0,7,No Specials,SP98,0,0,0,0,0,0.339622641509434
+5.1,8.7,21,23.5,5,No Specials,SP98,0,0,0,0,0,1.7058823529411764
+22.4,4.9,66,20.5,7,No Specials,SP98,0,0,0,0,0,0.21875000000000003
+31.1,4.7,42,20.5,7,No Specials,SP98,0,0,0,0,0,0.15112540192926044
+4.9,6.3,27,20.5,3,No Specials,SP98,0,0,0,0,0,1.2857142857142856
+11.8,5.1,26,23.0,4,rain,SP98,0,1,0,0,0,0.43220338983050843
+22.9,6.0,42,23.0,4,rain,SP98,0,1,0,0,0,0.26200873362445415
+12.4,4.6,38,23.0,1,snow,SP98,0,1,0,0,0,0.3709677419354838
+12.9,5.8,40,23.0,4,No Specials,SP98,0,0,0,0,0,0.44961240310077516
+11.8,5.1,43,23.0,0,No Specials,SP98,0,0,0,0,0,0.43220338983050843
+12.2,5.8,58,23.0,2,No Specials,SP98,0,0,0,0,0,0.4754098360655738
+24.8,4.6,55,23.0,3,No Specials,SP98,0,0,0,0,0,0.1854838709677419
+14.2,5.6,24,23.0,8,No Specials,SP98,0,0,0,0,0,0.39436619718309857
+11.8,4.6,38,23.0,0,snow,SP98,0,1,0,0,0,0.38983050847457623
+12.2,6.3,57,23.0,0,snow,SP98,0,1,0,0,0,0.5163934426229508
+24.7,5.5,56,25.0,1,No Specials,SP98,0,0,0,0,0,0.22267206477732795
+6.8,4.3,46,24.0,2,No Specials,SP98,0,0,0,0,0,0.6323529411764706
+17.3,5.6,37,21.5,1,No Specials,SP98,0,0,0,0,0,0.32369942196531787
+11.8,4.3,44,21.5,-3,No Specials,SP98,0,0,0,0,0,0.3644067796610169
+15.9,5.7,46,21.5,5,No Specials,SP98,0,0,0,0,0,0.3584905660377358
+5.1,6.4,39,21.5,4,No Specials,SP98,0,0,0,0,0,1.254901960784314
+16.1,4.5,33,21.5,6,No Specials,SP98,0,0,0,0,0,0.2795031055900621
+11.8,4.5,43,21.5,3,No Specials,SP98,0,0,0,0,0,0.3813559322033898
+4.2,6.0,26,21.5,5,No Specials,SP98,0,0,0,0,0,1.4285714285714286
+17.4,5.1,30,21.5,5,No Specials,SP98,0,0,0,0,0,0.2931034482758621
+23.5,6.0,25,21.5,5,rain,SP98,0,1,0,0,0,0.2553191489361702
+11.8,4.5,38,21.5,5,rain,SP98,0,1,0,0,0,0.3813559322033898
+12.3,6.1,61,21.5,10,rain,SP98,0,1,0,0,0,0.4959349593495934
+16.1,5.4,24,21.5,7,rain,E10,0,1,0,38,E10,0.3354037267080745
+11.8,4.3,40,21.5,10,rain,E10,0,1,0,0,0,0.3644067796610169
+12.3,5.4,58,21.5,13,No Specials,E10,0,0,0,0,0,0.43902439024390244
+12.4,4.3,49,21.5,17,No Specials,E10,0,0,0,0,0,0.34677419354838707
+7.0,5.2,25,21.5,17,No Specials,E10,0,0,0,0,0,0.7428571428571429
+11.8,4.1,37,21.5,10,No Specials,E10,0,0,0,0,0,0.34745762711864403
+20.1,4.4,41,21.5,18,No Specials,E10,0,0,0,0,0,0.21890547263681592
+20.8,4.5,45,21.5,10,No Specials,E10,0,0,0,0,0,0.21634615384615383
+1.7,10.8,14,21.5,10,rain,E10,0,1,0,0,0,6.352941176470589
+35.9,4.7,45,21.5,12,No Specials,E10,0,0,0,0,0,0.13091922005571033
+36.9,4.8,52,21.5,5,No Specials,E10,0,0,0,0,0,0.13008130081300814
+16.8,4.0,46,21.5,8,No Specials,E10,0,0,0,0,0,0.23809523809523808
+9.9,5.0,28,21.5,9,No Specials,E10,0,0,0,0,0,0.5050505050505051
+22.9,4.6,61,21.5,7,rain,E10,0,1,0,0,0,0.20087336244541484
+17.3,5.0,61,21.5,6,AC rain,E10,1,1,0,0,0,0.2890173410404624
+11.8,4.3,37,21.5,7,No Specials,E10,0,0,0,0,0,0.3644067796610169
+36.6,5.2,80,21.5,7,rain,E10,0,1,0,0,0,0.14207650273224043
+44.9,4.7,62,21.5,8,No Specials,E10,0,0,0,0,0,0.1046770601336303
+11.8,4.2,34,21.5,9,rain,E10,0,1,0,0,0,0.3559322033898305
+21.6,5.3,44,21.5,9,rain,E10,0,1,0,0,0,0.24537037037037035
+39.4,5.3,60,21.5,9,rain,E10,0,1,0,0,0,0.13451776649746192
+5.1,8.1,39,21.5,4,No Specials,E10,0,0,0,0,0,1.5882352941176472
+26.6,4.8,38,21.5,7,No Specials,E10,0,0,0,0,0,0.18045112781954886
+53.2,5.1,71,21.5,2,No Specials,E10,0,0,0,0,0,0.09586466165413533
+18.9,4.4,53,21.5,2,No Specials,E10,0,0,0,0,0,0.23280423280423285
+43.5,5.0,80,21.5,3,No Specials,E10,0,0,0,0,0,0.11494252873563218
+6.1,6.3,26,21.5,5,No Specials,E10,0,0,0,0,0,1.0327868852459017
+16.4,4.8,49,21.5,5,No Specials,E10,0,0,0,0,0,0.29268292682926833
+12.3,6.1,40,21.5,6,No Specials,E10,0,0,0,0,0,0.4959349593495934
+21.1,4.6,36,21.5,8,No Specials,E10,0,0,0,0,0,0.21800947867298576
+21.1,4.8,43,21.5,7,No Specials,E10,0,0,0,0,0,0.22748815165876776
+22.7,4.7,55,21.5,6,No Specials,E10,0,0,0,0,0,0.20704845814977976
+44.4,4.8,38,21.5,8,No Specials,E10,0,0,0,"38,3",E10,0.10810810810810811
+35.8,4.4,51,21.5,6,No Specials,E10,0,0,0,0,0,0.12290502793296092
+11.8,4.9,44,21.5,0,No Specials,E10,0,0,0,0,0,0.4152542372881356
+26.2,4.9,42,21.5,6,No Specials,E10,0,0,0,0,0,0.18702290076335878
+40.6,4.4,44,21.0,3,No Specials,E10,0,0,0,0,0,0.10837438423645321
+12.4,5.3,38,21.0,-5,No Specials,E10,0,0,0,0,0,0.42741935483870963
+14.1,5.3,47,21.0,-3,No Specials,E10,0,0,0,0,0,0.375886524822695
+58.7,4.8,75,21.0,0,No Specials,E10,0,0,0,0,0,0.0817717206132879
+16.2,5.2,29,21.0,0,No Specials,E10,0,0,0,0,0,0.3209876543209877
+12.3,4.9,50,22.5,0,No Specials,E10,0,0,0,0,0,0.3983739837398374
+12.3,7.1,52,22.5,0,AC snow,E10,1,1,0,0,0,0.5772357723577235
+12.4,5.2,51,22.5,1,No Specials,E10,0,0,0,0,0,0.41935483870967744
+31.8,4.7,59,22.5,3,No Specials,E10,0,0,0,0,0,0.14779874213836477
+12.3,5.1,55,22.5,8,No Specials,E10,0,0,0,0,0,0.41463414634146334
+51.6,5.0,73,22.5,12,No Specials,E10,0,0,0,0,0,0.09689922480620154
+38.6,4.6,44,22.5,10,No Specials,E10,0,0,0,0,0,0.11917098445595854
+12.3,4.8,41,22.5,7,No Specials,E10,0,0,0,0,0,0.39024390243902435
+81.2,4.4,69,22.0,13,No Specials,E10,0,0,0,0,0,0.054187192118226604
+130.3,4.6,85,22.0,12,No Specials,E10,0,0,0,0,0,0.03530314658480429
+67.2,4.3,67,22.0,18,No Specials,E10,0,0,0,0,0,0.06398809523809523
+43.7,4.7,44,22.0,9,half rain half sun,SP98,0,1,0,10,SP98,0.10755148741418764
+12.1,4.2,43,22.0,4,No Specials,SP98,0,0,0,39,SP98,0.34710743801652894
+56.1,4.8,82,22.0,13,No Specials,SP98,0,0,0,0,0,0.0855614973262032
+39.0,4.1,61,22.0,16,No Specials,SP98,0,0,0,0,0,0.10512820512820512
+11.8,4.5,41,21.5,13,No Specials,SP98,0,0,0,0,0,0.3813559322033898
+38.5,4.8,63,21.5,14,No Specials,SP98,0,0,0,0,0,0.12467532467532468
+28.2,4.6,54,21.5,14,No Specials,SP98,0,0,0,0,0,0.1631205673758865
+2.9,7.4,24,21.5,14,No Specials,SP98,0,0,0,0,0,2.5517241379310347
+6.1,5.6,24,21.5,13,No Specials,SP98,0,0,0,0,0,0.9180327868852459
+19.6,4.9,43,21.5,13,No Specials,SP98,0,0,0,0,0,0.25
+22.2,3.8,42,21.929521276595743,15,No Specials,SP98,0,0,0,0,0,0.17117117117117117
+13.6,4.5,44,19.0,18,No Specials,SP98,0,0,0,0,0,0.33088235294117646
+12.6,4.1,33,21.929521276595743,17,No Specials,SP98,0,0,0,0,0,0.32539682539682535
+8.7,5.3,28,22.5,12,AC rain,SP98,1,1,0,0,0,0.6091954022988506
+7.9,4.7,31,22.5,12,AC,SP98,1,0,0,0,0,0.5949367088607594
+2.4,9.0,26,20.0,10,No Specials,SP98,0,0,0,0,0,3.75
+4.9,6.3,26,20.0,10,No Specials,SP98,0,0,0,0,0,1.2857142857142856
+18.1,3.6,36,20.0,19,No Specials,SP98,0,0,0,0,0,0.19889502762430938
+25.9,3.7,39,20.0,21,No Specials,SP98,0,0,0,0,0,0.14285714285714288
+1.3,11.5,21,20.0,10,No Specials,SP98,0,0,0,0,0,8.846153846153847
+14.1,5.0,22,20.0,12,No Specials,SP98,0,0,0,0,0,0.3546099290780142
+13.4,5.5,31,20.0,9,No Specials,SP98,0,0,0,0,0,0.4104477611940298
+6.4,4.7,33,20.0,8,No Specials,SP98,0,0,0,0,0,0.734375
+12.9,4.5,42,20.0,13,No Specials,SP98,0,0,0,0,0,0.3488372093023256
+12.1,4.4,33,22.5,5,No Specials,SP98,0,0,0,0,0,0.3636363636363637
+15.7,4.1,32,22.5,13,No Specials,SP98,0,0,0,0,0,0.2611464968152866
+16.2,4.4,26,22.5,11,No Specials,SP98,0,0,0,0,0,0.271604938271605
+12.8,4.6,22,22.5,12,No Specials,SP98,0,0,0,0,0,0.35937499999999994
+19.0,4.4,58,22.5,17,sun,SP98,0,0,1,0,0,0.23157894736842108
+29.0,4.0,27,22.5,12,No Specials,SP98,0,0,0,0,0,0.13793103448275862
+12.1,5.0,32,22.5,9,No Specials,SP98,0,0,0,0,0,0.4132231404958678
+12.3,5.2,55,22.5,10,No Specials,SP98,0,0,0,0,0,0.4227642276422764
+24.8,4.0,56,22.5,11,No Specials,SP98,0,0,0,0,0,0.16129032258064516
+12.9,5.1,34,22.5,8,rain,SP98,0,1,0,0,0,0.3953488372093023
+11.8,4.5,39,22.5,3,No Specials,SP98,0,0,0,0,0,0.3813559322033898
+31.4,4.6,62,22.5,11,No Specials,SP98,0,0,0,0,0,0.1464968152866242
+19.0,5.1,53,22.5,4,rain,SP98,0,1,0,0,0,0.26842105263157895
+13.0,5.7,38,22.5,3,AC rain,SP98,1,1,0,0,0,0.43846153846153846
+11.8,4.8,42,22.5,2,No Specials,SP98,0,0,0,0,0,0.4067796610169491
+13.0,6.2,32,22.5,4,No Specials,SP98,0,0,0,0,0,0.47692307692307695
+11.8,5.0,43,22.5,1,No Specials,SP98,0,0,0,0,0,0.423728813559322
+27.1,5.0,69,22.5,8,No Specials,SP98,0,0,0,0,0,0.18450184501845018
+5.2,4.6,38,22.5,8,No Specials,SP98,0,0,0,0,0,0.8846153846153845
+19.0,4.5,29,22.5,10,No Specials,E10,0,0,0,39,E10,0.23684210526315788
+12.4,4.8,38,22.5,1,No Specials,E10,0,0,0,0,0,0.3870967741935484
+25.2,5.0,55,22.5,9,No Specials,E10,0,0,0,0,0,0.19841269841269843
+14.3,4.8,36,22.5,10,No Specials,E10,0,0,0,0,0,0.3356643356643356
+11.8,4.6,40,22.5,2,No Specials,E10,0,0,0,0,0,0.38983050847457623
+16.9,4.5,48,22.5,9,sun,E10,0,0,1,0,0,0.26627218934911245
+12.4,4.6,55,22.5,11,sun,E10,0,0,1,0,0,0.3709677419354838
+17.4,4.4,36,22.5,12,sun,E10,0,0,1,0,0,0.25287356321839083
+9.2,5.7,33,22.5,8,rain,E10,0,1,0,0,0,0.6195652173913044
+12.3,5.8,54,22.5,10,rain,E10,0,1,0,0,0,0.47154471544715443
+13.0,5.9,32,22.5,10,No Specials,E10,0,0,0,0,0,0.4538461538461539
+11.8,6.1,16,22.5,6,rain,E10,0,1,0,0,0,0.5169491525423728
+13.0,5.7,37,22.5,11,rain,E10,0,1,0,0,0,0.43846153846153846
+12.3,5.0,42,22.5,10,No Specials,E10,0,0,0,0,0,0.4065040650406504
+12.3,5.2,57,22.5,15,sun,E10,0,0,1,0,0,0.4227642276422764
+12.5,4.3,57,22.5,16,sun,E10,0,0,1,0,0,0.344
+31.5,4.1,30,22.5,16,sun,E10,0,0,1,0,0,0.13015873015873014
+11.8,4.4,42,22.5,8,No Specials,E10,0,0,0,0,0,0.3728813559322034
+24.9,4.5,53,22.5,14,No Specials,E10,0,0,0,0,0,0.18072289156626506
+17.0,3.9,46,22.5,14,sun,E10,0,0,1,0,0,0.22941176470588234
+2.0,8.1,20,22.5,14,No Specials,E10,0,0,0,0,0,4.05
+11.8,4.4,33,22.5,8,No Specials,E10,0,0,0,0,0,0.3728813559322034
+7.4,5.0,31,22.5,12,No Specials,E10,0,0,0,0,0,0.6756756756756757
+12.4,4.7,55,22.5,14,sun,E10,0,0,1,0,0,0.3790322580645161
+2.0,6.0,22,22.5,14,No Specials,E10,0,0,0,0,0,3.0
+14.0,5.0,41,22.5,8,No Specials,E10,0,0,0,0,0,0.35714285714285715
+25.7,5.0,45,22.5,7,No Specials,E10,0,0,0,0,0,0.19455252918287938
+24.5,3.9,50,21.929521276595743,15,sun,E10,0,0,1,0,0,0.15918367346938775
+11.8,4.5,28,22.5,12,No Specials,E10,0,0,0,0,0,0.3813559322033898
+4.1,5.4,24,22.5,13,No Specials,E10,0,0,0,0,0,1.3170731707317076
+4.2,5.6,29,22.0,17,No Specials,E10,0,0,0,0,0,1.3333333333333333
+4.2,3.9,29,22.0,18,sun,E10,0,0,1,0,0,0.9285714285714285
+16.0,4.0,40,22.0,10,No Specials,E10,0,0,0,0,0,0.25
+22.9,4.0,29,21.929521276595743,21,No Specials,E10,0,0,0,0,0,0.17467248908296945
+16.0,3.8,42,21.929521276595743,8,No Specials,E10,0,0,0,0,0,0.2375
+15.4,4.5,50,22.0,14,No Specials,E10,0,0,0,0,0,0.2922077922077922
+16.0,3.8,41,22.0,12,No Specials,E10,0,0,0,0,0,0.2375
+4.2,5.6,32,22.0,18,No Specials,E10,0,0,0,0,0,1.3333333333333333
+101.9,5.2,75,22.0,18,No Specials,E10,0,0,0,0,0,0.05103042198233562
+93.9,4.8,88,23.0,18,AC sun,E10,1,0,1,0,0,0.051118210862619806
+25.7,4.9,50,22.0,10,rain,SP98,0,1,0,41,SP98,0.1906614785992218
+16.0,4.1,40,22.0,10,No Specials,SP98,0,0,0,0,0,0.25625
+16.1,4.5,32,22.0,19,No Specials,SP98,0,0,0,0,0,0.2795031055900621
+16.0,4.4,40,22.0,7,AC rain,SP98,1,1,0,0,0,0.275
+16.0,4.5,41,22.0,11,No Specials,SP98,0,0,0,0,0,0.28125
+24.7,4.5,26,22.0,10,No Specials,SP98,0,0,0,0,0,0.18218623481781376
+16.0,3.9,42,22.0,8,No Specials,SP98,0,0,0,0,0,0.24375
+15.4,4.6,43,22.0,16,No Specials,SP98,0,0,0,0,0,0.2987012987012987
+16.0,3.8,40,22.0,8,No Specials,SP98,0,0,0,0,0,0.2375
+32.1,4.5,50,22.0,16,No Specials,SP98,0,0,0,0,0,0.14018691588785046
+25.9,4.4,40,22.0,14,No Specials,SP98,0,0,0,0,0,0.1698841698841699
+48.6,4.3,44,22.0,12,No Specials,SP98,0,0,0,0,0,0.08847736625514403
+37.2,4.0,45,22.0,20,sun,SP98,0,0,1,0,0,0.1075268817204301
+28.8,3.9,35,22.0,15,sun,SP98,0,0,1,0,0,0.13541666666666666
+6.7,5.0,30,22.0,17,No Specials,SP98,0,0,0,0,0,0.7462686567164178
+7.4,4.1,25,22.0,18,sun,SP98,0,0,1,0,0,0.554054054054054
+17.3,4.1,22,22.0,25,sun,SP98,0,0,1,0,0,0.23699421965317916
+6.6,5.6,43,22.0,16,No Specials,SP98,0,0,0,0,0,0.8484848484848485
+14.3,4.1,26,22.0,20,No Specials,SP98,0,0,0,0,0,0.28671328671328666
+13.3,4.6,33,22.0,18,No Specials,SP98,0,0,0,0,0,0.3458646616541353
+8.3,4.9,26,22.0,23,No Specials,SP98,0,0,0,0,0,0.5903614457831325
+12.7,4.5,39,22.0,27,sun,SP98,0,0,1,0,0,0.35433070866141736
+16.5,4.1,47,22.0,14,No Specials,SP98,0,0,0,0,0,0.24848484848484848
+20.6,4.1,38,22.0,21,No Specials,SP98,0,0,0,0,0,0.1990291262135922
+16.3,4.5,58,22.0,16,No Specials,SP98,0,0,0,0,0,0.2760736196319018
+18.7,4.2,65,25.0,18,sun ac,SP98,1,0,1,0,0,0.22459893048128343
+36.5,3.9,54,23.0,18,sun,SP98,0,0,1,0,0,0.10684931506849314
+19.0,5.0,35,22.0,15,sun ac,SP98,1,0,1,0,0,0.2631578947368421
+16.6,4.4,46,22.0,5,ac,SP98,1,0,0,0,0,0.26506024096385544
+29.9,4.5,32,22.0,18,ac,SP98,1,0,0,0,0,0.1505016722408027
+16.0,3.8,42,22.0,11,No Specials,SP98,0,0,0,0,0,0.2375
+21.1,5.1,33,22.0,10,rain,SP98,0,1,0,0,0,0.24170616113744073
+16.0,3.9,40,22.0,10,No Specials,SP98,0,0,0,0,0,0.24375
+11.9,5.3,34,22.0,13,No Specials,SP98,0,0,0,0,0,0.4453781512605042
+10.1,4.2,35,22.0,16,No Specials,SP98,0,0,0,0,0,0.4158415841584159
+31.9,4.3,33,22.0,16,No Specials,SP98,0,0,0,0,0,0.13479623824451412
+18.7,4.0,60,22.0,13,No Specials,SP98,0,0,0,0,0,0.21390374331550802
+10.8,4.7,48,22.0,17,sun,SP98,0,0,1,0,0,0.4351851851851852
+19.8,4.0,56,22.0,17,sun,SP98,0,0,1,0,0,0.20202020202020202
+11.3,4.3,38,22.0,17,No Specials,SP98,0,0,0,37,SP98,0.3805309734513274
+11.5,5.3,53,22.0,15,No Specials,SP98,0,0,0,0,0,0.4608695652173913
+21.4,5.2,51,22.0,13,No Specials,SP98,0,0,0,0,0,0.2429906542056075
+32.0,4.9,53,22.0,15,No Specials,SP98,0,0,0,0,0,0.153125
+41.9,4.7,53,22.0,14,No Specials,SP98,0,0,0,0,0,0.11217183770883056
+211.0,4.6,80,22.0,20,No Specials,SP98,0,0,0,0,0,0.021800947867298578
+216.1,5.3,90,22.0,21,sun,SP98,0,0,1,0,0,0.024525682554372975
+25.5,3.6,27,22.0,27,sun,SP98,0,0,1,0,0,0.1411764705882353
+16.6,4.2,52,22.0,15,rain,SP98,0,1,0,0,0,0.25301204819277107
+25.9,4.1,43,22.0,24,No Specials,SP98,0,0,0,0,0,0.1583011583011583
+16.5,4.0,48,22.0,15,No Specials,SP98,0,0,0,0,0,0.24242424242424243
+22.1,3.9,29,22.0,26,No Specials,SP98,0,0,0,0,0,0.1764705882352941
+16.6,3.7,49,22.0,17,No Specials,E10,0,0,0,"37,7",E10,0.22289156626506024
+15.4,4.5,43,22.0,24,No Specials,E10,0,0,0,0,0,0.2922077922077922
+16.5,3.9,43,22.0,17,No Specials,E10,0,0,0,0,0,0.23636363636363636
+15.4,5.1,21,22.0,24,No Specials,E10,0,0,0,0,0,0.3311688311688311
+18.4,4.2,59,22.0,24,No Specials,E10,0,0,0,0,0,0.2282608695652174
+39.5,4.2,58,22.0,25,No Specials,E10,0,0,0,0,0,0.10632911392405063
+21.5,4.8,47,25.0,27,AC Sun,E10,1,0,1,0,0,0.22325581395348837
+4.8,4.7,26,25.0,18,No Specials,E10,0,0,0,0,0,0.9791666666666667
+100.9,4.7,87,23.5,22,No Specials,E10,0,0,0,0,0,0.04658077304261645
+129.7,4.6,58,24.0,21,ac,E10,0,0,0,0,0,0.035466461063993836
+16.6,3.8,43,21.5,16,No Specials,E10,0,0,0,0,0,0.22891566265060237
+15.4,4.2,50,21.5,21,No Specials,E10,0,0,0,0,0,0.2727272727272727
+16.0,3.7,45,22.0,17,No Specials,E10,0,0,0,0,0,0.23125
+16.0,4.2,41,22.0,15,No Specials,E10,0,0,0,0,0,0.2625
+15.4,4.1,45,22.0,24,No Specials,E10,0,0,0,0,0,0.2662337662337662
+16.0,4.0,43,22.0,16,No Specials,E10,0,0,0,0,0,0.25
+21.0,3.8,37,22.0,21,No Specials,E10,0,0,0,0,0,0.18095238095238095
+15.4,3.8,47,22.0,24,No Specials,E10,0,0,0,0,0,0.24675324675324672
+16.0,3.8,42,22.0,17,No Specials,E10,0,0,0,0,0,0.2375
+16.1,5.1,30,25.0,16,ac rain,E10,1,1,0,0,0,0.31677018633540366
+16.0,4.0,42,22.0,15,No Specials,E10,0,0,0,0,0,0.25
+15.4,4.8,40,22.0,18,No Specials,E10,0,0,0,0,0,0.3116883116883117
+17.2,3.9,35,22.0,16,No Specials,E10,0,0,0,0,0,0.22674418604651164
+16.6,4.6,50,22.0,25,No Specials,E10,0,0,0,0,0,0.2771084337349397
+18.3,4.3,46,22.0,16,No Specials,SP98,0,0,0,"37,2",SP98,0.2349726775956284
+16.1,4.8,36,22.0,18,rain,SP98,0,1,0,0,0,0.29813664596273287
+16.0,4.1,46,22.0,17,No Specials,SP98,0,0,0,0,0,0.25625
+16.3,4.0,35,22.0,23,No Specials,SP98,0,0,0,0,0,0.24539877300613497
+16.0,3.7,44,22.0,16,No Specials,SP98,0,0,0,0,0,0.23125
+18.3,4.3,46,22.0,23,No Specials,SP98,0,0,0,0,0,0.2349726775956284
+4.5,5.2,23,22.0,23,sun,SP98,0,0,1,0,0,1.1555555555555557
+17.0,4.2,48,22.0,16,No Specials,SP98,0,0,0,0,0,0.24705882352941178
+6.1,5.0,35,24.5,18,No Specials,SP98,0,0,0,0,0,0.819672131147541
+6.1,5.0,33,22.0,24,sun,SP98,0,0,1,0,0,0.819672131147541
+17.3,4.2,36,22.0,22,No Specials,SP98,0,0,0,0,0,0.24277456647398843
+6.0,4.8,27,22.0,17,No Specials,SP98,0,0,0,0,0,0.7999999999999999
+16.0,4.1,45,22.0,15,No Specials,SP98,0,0,0,0,0,0.25625
+15.4,4.9,55,22.0,18,No Specials,SP98,0,0,0,0,0,0.3181818181818182
+15.4,4.3,39,22.0,23,No Specials,SP98,0,0,0,0,0,0.2792207792207792
+16.0,3.9,35,22.0,18,No Specials,SP98,0,0,0,0,0,0.24375
+15.4,4.5,52,22.0,26,No Specials,SP98,0,0,0,0,0,0.2922077922077922
+16.6,4.1,48,25.5,30,sun ac,SP98,1,0,1,0,0,0.24698795180722888
+15.4,5.0,48,25.5,31,ac,SP98,1,0,0,0,0,0.3246753246753247
+16.0,4.0,43,22.0,21,ac,SP98,1,0,0,0,0,0.25
+15.4,4.5,42,22.0,30,No Specials,SP98,0,0,0,0,0,0.2922077922077922
+16.0,3.6,43,22.0,19,No Specials,SP98,0,0,0,0,0,0.225
+20.9,4.1,33,22.0,21,No Specials,SP98,0,0,0,0,0,0.19617224880382775
+32.1,3.9,47,22.0,26,No Specials,SP98,0,0,0,0,0,0.12149532710280372
+15.3,6.6,16,24.0,27,ac,SP98,1,0,0,0,0,0.4313725490196078
+28.5,4.0,44,25.0,23,ac,SP98,1,0,0,0,0,0.14035087719298245
+11.9,3.7,33,25.0,19,No Specials,SP98,0,0,0,0,0,0.31092436974789917
+14.5,4.3,36,25.0,22,No Specials,SP98,0,0,0,0,0,0.296551724137931
+16.6,4.1,49,22.0,26,sun,SP98,0,0,1,0,0,0.24698795180722888
+16.2,4.4,39,24.5,17,ac,SP98,1,0,0,0,0,0.271604938271605
+16.7,3.8,44,24.5,23,sun,SP98,0,0,1,0,0,0.2275449101796407
+8.3,5.0,52,24.5,27,No Specials,SP98,0,0,0,0,0,0.6024096385542168
+5.5,3.7,33,24.5,28,sun,SP98,0,0,1,0,0,0.6727272727272727
+13.6,3.7,33,24.5,28,sun,SP98,0,0,1,0,0,0.2720588235294118
+16.0,3.7,39,24.5,18,No Specials,SP98,0,0,0,0,0,0.23125
+16.1,4.3,38,25.0,31,AC,SP98,1,0,0,0,0,0.26708074534161486
+16.0,3.8,45,25.0,19,No Specials,SP98,0,0,0,0,0,0.2375
+15.4,4.6,42,25.0,31,AC,SP98,1,0,0,0,0,0.2987012987012987
+14.7,5.0,25,25.0,30,AC,SP98,1,0,0,0,0,0.3401360544217687
diff --git a/data/cleaned.csv b/data/cleaned.csv
new file mode 100644
index 0000000..2786b73
--- /dev/null
+++ b/data/cleaned.csv
@@ -0,0 +1,389 @@
+distance,consume,speed,temp_inside,temp_outside,specials,gas_type,AC,rain,sun,refill liters,refill gas,efficiency
+28.0,5.0,26,21.5,12,No Specials,E10,0,0,0,45,E10,0.17857142857142858
+12.0,4.2,30,21.5,13,No Specials,E10,0,0,0,0,0,0.35000000000000003
+11.2,5.5,38,21.5,15,No Specials,E10,0,0,0,0,0,0.4910714285714286
+12.9,3.9,36,21.5,14,No Specials,E10,0,0,0,0,0,0.3023255813953488
+18.5,4.5,46,21.5,15,No Specials,E10,0,0,0,0,0,0.24324324324324326
+8.3,6.4,50,21.5,10,No Specials,E10,0,0,0,0,0,0.7710843373493975
+7.8,4.4,43,21.5,11,No Specials,E10,0,0,0,0,0,0.5641025641025642
+12.3,5.0,40,21.5,6,No Specials,E10,0,0,0,0,0,0.4065040650406504
+4.9,6.4,26,21.5,4,No Specials,E10,0,0,0,0,0,1.3061224489795917
+11.9,5.3,30,21.5,9,No Specials,E10,0,0,0,0,0,0.4453781512605042
+12.4,5.6,42,21.5,4,No Specials,E10,0,0,0,0,0,0.4516129032258064
+11.8,4.6,38,21.5,0,No Specials,E10,0,0,0,0,0,0.38983050847457623
+12.3,5.9,59,21.5,10,No Specials,E10,0,0,0,0,0,0.4796747967479675
+24.7,5.1,58,21.5,12,No Specials,E10,0,0,0,0,0,0.20647773279352225
+12.4,4.7,46,21.5,11,No Specials,E10,0,0,0,0,0,0.3790322580645161
+17.3,5.1,24,21.5,5,No Specials,E10,0,0,0,0,0,0.29479768786127164
+33.4,5.6,36,21.5,3,No Specials,E10,0,0,0,0,0,0.16766467065868262
+11.8,5.1,32,21.5,3,No Specials,E10,0,0,0,0,0,0.43220338983050843
+25.9,4.9,39,21.5,8,No Specials,E10,0,0,0,0,0,0.1891891891891892
+11.8,4.7,40,21.5,4,No Specials,E10,0,0,0,0,0,0.3983050847457627
+25.3,5.5,32,21.5,3,No Specials,E10,0,0,0,0,0,0.21739130434782608
+14.2,5.9,38,21.5,1,No Specials,E10,0,0,0,0,0,0.41549295774647893
+17.9,5.7,37,21.5,1,No Specials,E10,0,0,0,0,0,0.3184357541899442
+11.8,4.7,36,21.5,1,No Specials,E10,0,0,0,0,0,0.3983050847457627
+12.3,5.9,62,21.5,6,No Specials,E10,0,0,0,0,0,0.4796747967479675
+12.4,4.1,57,21.5,9,No Specials,E10,0,0,0,0,0,0.33064516129032256
+18.4,5.7,21,22.5,2,No Specials,E10,0,0,0,0,0,0.3097826086956522
+18.4,5.8,28,21.5,3,No Specials,E10,0,0,0,0,0,0.31521739130434784
+18.3,5.5,29,21.5,1,No Specials,E10,0,0,0,0,0,0.3005464480874317
+18.4,5.7,35,21.5,4,No Specials,E10,0,0,0,0,0,0.3097826086956522
+12.3,5.3,51,21.5,11,No Specials,E10,0,0,0,0,0,0.4308943089430894
+11.8,5.0,29,21.5,10,No Specials,E10,0,0,0,0,0,0.423728813559322
+12.3,5.6,58,21.5,8,No Specials,E10,0,0,0,0,0,0.4552845528455284
+32.6,4.8,40,21.5,7,No Specials,E10,0,0,0,0,0,0.14723926380368096
+19.0,4.3,36,21.5,7,No Specials,E10,0,0,0,0,0,0.2263157894736842
+12.1,5.7,36,21.5,8,No Specials,E10,0,0,0,0,0,0.4710743801652893
+20.0,5.2,37,21.5,4,No Specials,E10,0,0,0,0,0,0.26
+4.9,7.4,26,21.5,6,No Specials,E10,0,0,0,0,0,1.510204081632653
+11.8,4.8,23,21.5,9,No Specials,E10,0,0,0,0,0,0.4067796610169491
+12.3,6.5,58,21.5,7,No Specials,E10,0,0,0,0,0,0.5284552845528455
+12.4,4.0,55,21.5,7,AC rain,E10,1,1,0,0,0,0.3225806451612903
+4.5,5.0,29,21.5,7,AC,E10,1,0,0,0,0,1.1111111111111112
+11.7,4.6,37,21.5,6,No Specials,E10,0,0,0,0,0,0.39316239316239315
+10.2,4.3,44,21.5,7,No Specials,E10,0,0,0,0,0,0.4215686274509804
+5.4,3.3,32,21.5,7,No Specials,SP98,0,0,0,"37,6",SP98,0.611111111111111
+2.0,9.9,21,21.5,4,No Specials,SP98,0,0,0,0,0,4.95
+14.2,5.1,32,21.5,7,No Specials,SP98,0,0,0,0,0,0.35915492957746475
+16.0,4.9,25,21.5,8,No Specials,SP98,0,0,0,0,0,0.30625
+11.8,4.9,25,21.5,11,No Specials,SP98,0,0,0,0,0,0.4152542372881356
+27.3,4.7,36,21.5,10,No Specials,SP98,0,0,0,0,0,0.17216117216117216
+11.8,5.1,29,21.5,5,rain,SP98,0,1,0,0,0,0.43220338983050843
+10.6,4.9,63,21.5,6,No Specials,SP98,0,0,0,0,0,0.4622641509433963
+11.6,4.2,61,21.5,7,No Specials,SP98,0,0,0,0,0,0.3620689655172414
+13.1,6.1,46,21.5,6,rain,SP98,0,1,0,0,0,0.46564885496183206
+6.1,6.4,28,21.5,8,No Specials,SP98,0,0,0,0,0,1.0491803278688525
+153.5,4.9,82,21.5,3,rain,SP98,0,1,0,0,0,0.03192182410423453
+11.8,4.9,24,21.5,7,No Specials,SP98,0,0,0,0,0,0.4152542372881356
+12.3,6.2,61,21.5,8,No Specials,SP98,0,0,0,0,0,0.5040650406504065
+12.4,4.2,57,21.5,8,No Specials,SP98,0,0,0,0,0,0.33870967741935487
+12.3,5.7,52,21.5,8,rain,SP98,0,1,0,0,0,0.46341463414634143
+2.9,7.9,18,21.5,9,AC rain,SP98,1,1,0,0,0,2.724137931034483
+2.1,12.2,23,21.5,9,No Specials,SP98,1,1,0,0,0,5.809523809523809
+9.8,5.8,24,21.5,6,No Specials,SP98,0,0,0,0,0,0.5918367346938775
+6.8,5.3,26,21.5,6,No Specials,SP98,0,0,0,0,0,0.7794117647058824
+12.4,5.4,24,21.5,7,No Specials,SP98,0,0,0,0,0,0.43548387096774194
+12.4,4.7,57,21.5,8,No Specials,SP98,0,0,0,0,0,0.3790322580645161
+11.8,4.6,41,21.5,6,No Specials,SP98,0,0,0,0,0,0.38983050847457623
+12.3,5.4,55,21.5,8,No Specials,SP98,0,0,0,0,0,0.43902439024390244
+14.0,4.3,40,21.5,8,No Specials,SP98,0,0,0,0,0,0.3071428571428571
+11.8,4.5,37,21.5,4,AC,SP98,1,0,0,0,0,0.3813559322033898
+12.3,5.2,55,21.5,12,No Specials,SP98,0,0,0,0,0,0.4227642276422764
+2.0,6.2,20,21.5,10,No Specials,SP98,0,0,0,0,0,3.1
+13.9,5.1,29,21.5,6,No Specials,SP98,0,0,0,0,0,0.3669064748201438
+9.7,3.9,42,21.5,8,No Specials,SP98,0,0,0,0,0,0.4020618556701031
+11.6,5.0,25,21.5,6,No Specials,SP98,0,0,0,0,0,0.4310344827586207
+14.2,5.4,38,21.5,7,No Specials,SP98,0,0,0,0,0,0.3802816901408451
+11.8,4.5,39,21.5,6,No Specials,SP98,0,0,0,0,0,0.3813559322033898
+24.8,5.1,50,21.5,9,No Specials,SP98,0,0,0,0,0,0.20564516129032256
+12.4,4.7,56,21.5,7,No Specials,SP98,0,0,0,0,0,0.3790322580645161
+34.8,4.0,28,20.0,4,No Specials,SP98,0,0,0,0,0,0.1149425287356322
+14.2,5.4,36,20.0,6,No Specials,SP98,0,0,0,0,0,0.3802816901408451
+5.2,4.5,39,20.0,10,No Specials,SP98,0,0,0,0,0,0.8653846153846153
+10.5,3.6,42,20.0,10,No Specials,SP98,0,0,0,"37,7",SP98,0.34285714285714286
+12.3,5.2,57,20.0,10,No Specials,SP98,0,0,0,0,0,0.4227642276422764
+11.8,4.9,25,20.0,11,No Specials,SP98,0,0,0,0,0,0.4152542372881356
+12.3,6.2,58,20.0,11,rain,SP98,0,1,0,0,0,0.5040650406504065
+13.2,4.3,51,20.0,11,rain,SP98,0,1,0,0,0,0.32575757575757575
+13.0,5.0,45,20.0,11,rain,SP98,0,1,0,0,0,0.38461538461538464
+12.9,5.1,32,20.0,11,No Specials,SP98,0,0,0,0,0,0.3953488372093023
+13.9,5.6,22,20.0,8,No Specials,SP98,0,0,0,0,0,0.40287769784172656
+11.8,4.3,37,20.0,6,No Specials,SP98,0,0,0,0,0,0.3644067796610169
+12.2,5.8,60,20.0,11,No Specials,SP98,0,0,0,0,0,0.4754098360655738
+12.5,4.0,51,20.0,13,No Specials,SP98,0,0,0,0,0,0.32
+12.4,4.7,43,21.929521276595743,10,No Specials,SP98,0,0,0,0,0,0.3790322580645161
+11.8,5.9,21,20.0,9,AC rain,SP98,1,1,0,0,0,0.5
+11.8,5.3,52,21.929521276595743,11,No Specials,SP98,0,0,0,0,0,0.4491525423728813
+12.5,4.2,57,20.0,11,No Specials,SP98,0,0,0,0,0,0.336
+15.7,5.3,33,21.929521276595743,9,No Specials,SP98,0,0,0,0,0,0.3375796178343949
+12.9,5.7,35,21.929521276595743,9,No Specials,SP98,0,0,0,0,0,0.4418604651162791
+6.4,4.4,37,21.929521276595743,10,No Specials,SP98,0,0,0,0,0,0.6875
+5.3,4.1,34,21.929521276595743,9,No Specials,SP98,0,0,0,0,0,0.7735849056603773
+26.2,5.8,71,21.0,8,AC rain,SP98,1,1,0,0,0,0.22137404580152673
+18.8,5.0,62,21.929521276595743,9,rain,SP98,0,1,0,0,0,0.26595744680851063
+4.9,6.9,25,21.0,12,rain,SP98,0,1,0,0,0,1.4081632653061225
+12.4,5.4,18,21.0,11,AC rain,SP98,1,1,0,0,0,0.43548387096774194
+22.9,5.3,45,20.5,7,No Specials,SP98,0,0,0,0,0,0.2314410480349345
+162.7,5.5,75,23.0,1,No Specials,SP98,0,0,0,45,SP98,0.03380454824830977
+4.9,6.5,26,21.0,1,No Specials,SP98,0,0,0,0,0,1.3265306122448979
+11.8,4.7,36,21.0,4,No Specials,SP98,0,0,0,0,0,0.3983050847457627
+16.6,5.1,56,21.0,7,No Specials,SP98,0,0,0,0,0,0.30722891566265054
+12.4,5.7,37,21.0,7,No Specials,SP98,0,0,0,0,0,0.4596774193548387
+15.9,5.4,25,21.0,7,No Specials,SP98,0,0,0,0,0,0.339622641509434
+5.1,8.7,21,23.5,5,No Specials,SP98,0,0,0,0,0,1.7058823529411764
+22.4,4.9,66,20.5,7,No Specials,SP98,0,0,0,0,0,0.21875000000000003
+31.1,4.7,42,20.5,7,No Specials,SP98,0,0,0,0,0,0.15112540192926044
+4.9,6.3,27,20.5,3,No Specials,SP98,0,0,0,0,0,1.2857142857142856
+11.8,5.1,26,23.0,4,rain,SP98,0,1,0,0,0,0.43220338983050843
+22.9,6.0,42,23.0,4,rain,SP98,0,1,0,0,0,0.26200873362445415
+12.4,4.6,38,23.0,1,snow,SP98,0,1,0,0,0,0.3709677419354838
+12.9,5.8,40,23.0,4,No Specials,SP98,0,0,0,0,0,0.44961240310077516
+11.8,5.1,43,23.0,0,No Specials,SP98,0,0,0,0,0,0.43220338983050843
+12.2,5.8,58,23.0,2,No Specials,SP98,0,0,0,0,0,0.4754098360655738
+24.8,4.6,55,23.0,3,No Specials,SP98,0,0,0,0,0,0.1854838709677419
+14.2,5.6,24,23.0,8,No Specials,SP98,0,0,0,0,0,0.39436619718309857
+11.8,4.6,38,23.0,0,snow,SP98,0,1,0,0,0,0.38983050847457623
+12.2,6.3,57,23.0,0,snow,SP98,0,1,0,0,0,0.5163934426229508
+24.7,5.5,56,25.0,1,No Specials,SP98,0,0,0,0,0,0.22267206477732795
+6.8,4.3,46,24.0,2,No Specials,SP98,0,0,0,0,0,0.6323529411764706
+17.3,5.6,37,21.5,1,No Specials,SP98,0,0,0,0,0,0.32369942196531787
+11.8,4.3,44,21.5,-3,No Specials,SP98,0,0,0,0,0,0.3644067796610169
+15.9,5.7,46,21.5,5,No Specials,SP98,0,0,0,0,0,0.3584905660377358
+5.1,6.4,39,21.5,4,No Specials,SP98,0,0,0,0,0,1.254901960784314
+16.1,4.5,33,21.5,6,No Specials,SP98,0,0,0,0,0,0.2795031055900621
+11.8,4.5,43,21.5,3,No Specials,SP98,0,0,0,0,0,0.3813559322033898
+4.2,6.0,26,21.5,5,No Specials,SP98,0,0,0,0,0,1.4285714285714286
+17.4,5.1,30,21.5,5,No Specials,SP98,0,0,0,0,0,0.2931034482758621
+23.5,6.0,25,21.5,5,rain,SP98,0,1,0,0,0,0.2553191489361702
+11.8,4.5,38,21.5,5,rain,SP98,0,1,0,0,0,0.3813559322033898
+12.3,6.1,61,21.5,10,rain,SP98,0,1,0,0,0,0.4959349593495934
+16.1,5.4,24,21.5,7,rain,E10,0,1,0,38,E10,0.3354037267080745
+11.8,4.3,40,21.5,10,rain,E10,0,1,0,0,0,0.3644067796610169
+12.3,5.4,58,21.5,13,No Specials,E10,0,0,0,0,0,0.43902439024390244
+12.4,4.3,49,21.5,17,No Specials,E10,0,0,0,0,0,0.34677419354838707
+7.0,5.2,25,21.5,17,No Specials,E10,0,0,0,0,0,0.7428571428571429
+11.8,4.1,37,21.5,10,No Specials,E10,0,0,0,0,0,0.34745762711864403
+20.1,4.4,41,21.5,18,No Specials,E10,0,0,0,0,0,0.21890547263681592
+20.8,4.5,45,21.5,10,No Specials,E10,0,0,0,0,0,0.21634615384615383
+1.7,10.8,14,21.5,10,rain,E10,0,1,0,0,0,6.352941176470589
+35.9,4.7,45,21.5,12,No Specials,E10,0,0,0,0,0,0.13091922005571033
+36.9,4.8,52,21.5,5,No Specials,E10,0,0,0,0,0,0.13008130081300814
+16.8,4.0,46,21.5,8,No Specials,E10,0,0,0,0,0,0.23809523809523808
+9.9,5.0,28,21.5,9,No Specials,E10,0,0,0,0,0,0.5050505050505051
+22.9,4.6,61,21.5,7,rain,E10,0,1,0,0,0,0.20087336244541484
+17.3,5.0,61,21.5,6,AC rain,E10,1,1,0,0,0,0.2890173410404624
+11.8,4.3,37,21.5,7,No Specials,E10,0,0,0,0,0,0.3644067796610169
+36.6,5.2,80,21.5,7,rain,E10,0,1,0,0,0,0.14207650273224043
+44.9,4.7,62,21.5,8,No Specials,E10,0,0,0,0,0,0.1046770601336303
+11.8,4.2,34,21.5,9,rain,E10,0,1,0,0,0,0.3559322033898305
+21.6,5.3,44,21.5,9,rain,E10,0,1,0,0,0,0.24537037037037035
+39.4,5.3,60,21.5,9,rain,E10,0,1,0,0,0,0.13451776649746192
+5.1,8.1,39,21.5,4,No Specials,E10,0,0,0,0,0,1.5882352941176472
+26.6,4.8,38,21.5,7,No Specials,E10,0,0,0,0,0,0.18045112781954886
+53.2,5.1,71,21.5,2,No Specials,E10,0,0,0,0,0,0.09586466165413533
+18.9,4.4,53,21.5,2,No Specials,E10,0,0,0,0,0,0.23280423280423285
+43.5,5.0,80,21.5,3,No Specials,E10,0,0,0,0,0,0.11494252873563218
+6.1,6.3,26,21.5,5,No Specials,E10,0,0,0,0,0,1.0327868852459017
+16.4,4.8,49,21.5,5,No Specials,E10,0,0,0,0,0,0.29268292682926833
+12.3,6.1,40,21.5,6,No Specials,E10,0,0,0,0,0,0.4959349593495934
+21.1,4.6,36,21.5,8,No Specials,E10,0,0,0,0,0,0.21800947867298576
+21.1,4.8,43,21.5,7,No Specials,E10,0,0,0,0,0,0.22748815165876776
+22.7,4.7,55,21.5,6,No Specials,E10,0,0,0,0,0,0.20704845814977976
+44.4,4.8,38,21.5,8,No Specials,E10,0,0,0,"38,3",E10,0.10810810810810811
+35.8,4.4,51,21.5,6,No Specials,E10,0,0,0,0,0,0.12290502793296092
+11.8,4.9,44,21.5,0,No Specials,E10,0,0,0,0,0,0.4152542372881356
+26.2,4.9,42,21.5,6,No Specials,E10,0,0,0,0,0,0.18702290076335878
+40.6,4.4,44,21.0,3,No Specials,E10,0,0,0,0,0,0.10837438423645321
+12.4,5.3,38,21.0,-5,No Specials,E10,0,0,0,0,0,0.42741935483870963
+14.1,5.3,47,21.0,-3,No Specials,E10,0,0,0,0,0,0.375886524822695
+58.7,4.8,75,21.0,0,No Specials,E10,0,0,0,0,0,0.0817717206132879
+16.2,5.2,29,21.0,0,No Specials,E10,0,0,0,0,0,0.3209876543209877
+12.3,4.9,50,22.5,0,No Specials,E10,0,0,0,0,0,0.3983739837398374
+12.3,7.1,52,22.5,0,AC snow,E10,1,1,0,0,0,0.5772357723577235
+12.4,5.2,51,22.5,1,No Specials,E10,0,0,0,0,0,0.41935483870967744
+31.8,4.7,59,22.5,3,No Specials,E10,0,0,0,0,0,0.14779874213836477
+12.3,5.1,55,22.5,8,No Specials,E10,0,0,0,0,0,0.41463414634146334
+51.6,5.0,73,22.5,12,No Specials,E10,0,0,0,0,0,0.09689922480620154
+38.6,4.6,44,22.5,10,No Specials,E10,0,0,0,0,0,0.11917098445595854
+12.3,4.8,41,22.5,7,No Specials,E10,0,0,0,0,0,0.39024390243902435
+81.2,4.4,69,22.0,13,No Specials,E10,0,0,0,0,0,0.054187192118226604
+130.3,4.6,85,22.0,12,No Specials,E10,0,0,0,0,0,0.03530314658480429
+67.2,4.3,67,22.0,18,No Specials,E10,0,0,0,0,0,0.06398809523809523
+43.7,4.7,44,22.0,9,half rain half sun,SP98,0,1,0,10,SP98,0.10755148741418764
+12.1,4.2,43,22.0,4,No Specials,SP98,0,0,0,39,SP98,0.34710743801652894
+56.1,4.8,82,22.0,13,No Specials,SP98,0,0,0,0,0,0.0855614973262032
+39.0,4.1,61,22.0,16,No Specials,SP98,0,0,0,0,0,0.10512820512820512
+11.8,4.5,41,21.5,13,No Specials,SP98,0,0,0,0,0,0.3813559322033898
+38.5,4.8,63,21.5,14,No Specials,SP98,0,0,0,0,0,0.12467532467532468
+28.2,4.6,54,21.5,14,No Specials,SP98,0,0,0,0,0,0.1631205673758865
+2.9,7.4,24,21.5,14,No Specials,SP98,0,0,0,0,0,2.5517241379310347
+6.1,5.6,24,21.5,13,No Specials,SP98,0,0,0,0,0,0.9180327868852459
+19.6,4.9,43,21.5,13,No Specials,SP98,0,0,0,0,0,0.25
+22.2,3.8,42,21.929521276595743,15,No Specials,SP98,0,0,0,0,0,0.17117117117117117
+13.6,4.5,44,19.0,18,No Specials,SP98,0,0,0,0,0,0.33088235294117646
+12.6,4.1,33,21.929521276595743,17,No Specials,SP98,0,0,0,0,0,0.32539682539682535
+8.7,5.3,28,22.5,12,AC rain,SP98,1,1,0,0,0,0.6091954022988506
+7.9,4.7,31,22.5,12,AC,SP98,1,0,0,0,0,0.5949367088607594
+2.4,9.0,26,20.0,10,No Specials,SP98,0,0,0,0,0,3.75
+4.9,6.3,26,20.0,10,No Specials,SP98,0,0,0,0,0,1.2857142857142856
+18.1,3.6,36,20.0,19,No Specials,SP98,0,0,0,0,0,0.19889502762430938
+25.9,3.7,39,20.0,21,No Specials,SP98,0,0,0,0,0,0.14285714285714288
+1.3,11.5,21,20.0,10,No Specials,SP98,0,0,0,0,0,8.846153846153847
+14.1,5.0,22,20.0,12,No Specials,SP98,0,0,0,0,0,0.3546099290780142
+13.4,5.5,31,20.0,9,No Specials,SP98,0,0,0,0,0,0.4104477611940298
+6.4,4.7,33,20.0,8,No Specials,SP98,0,0,0,0,0,0.734375
+12.9,4.5,42,20.0,13,No Specials,SP98,0,0,0,0,0,0.3488372093023256
+12.1,4.4,33,22.5,5,No Specials,SP98,0,0,0,0,0,0.3636363636363637
+15.7,4.1,32,22.5,13,No Specials,SP98,0,0,0,0,0,0.2611464968152866
+16.2,4.4,26,22.5,11,No Specials,SP98,0,0,0,0,0,0.271604938271605
+12.8,4.6,22,22.5,12,No Specials,SP98,0,0,0,0,0,0.35937499999999994
+19.0,4.4,58,22.5,17,sun,SP98,0,0,1,0,0,0.23157894736842108
+29.0,4.0,27,22.5,12,No Specials,SP98,0,0,0,0,0,0.13793103448275862
+12.1,5.0,32,22.5,9,No Specials,SP98,0,0,0,0,0,0.4132231404958678
+12.3,5.2,55,22.5,10,No Specials,SP98,0,0,0,0,0,0.4227642276422764
+24.8,4.0,56,22.5,11,No Specials,SP98,0,0,0,0,0,0.16129032258064516
+12.9,5.1,34,22.5,8,rain,SP98,0,1,0,0,0,0.3953488372093023
+11.8,4.5,39,22.5,3,No Specials,SP98,0,0,0,0,0,0.3813559322033898
+31.4,4.6,62,22.5,11,No Specials,SP98,0,0,0,0,0,0.1464968152866242
+19.0,5.1,53,22.5,4,rain,SP98,0,1,0,0,0,0.26842105263157895
+13.0,5.7,38,22.5,3,AC rain,SP98,1,1,0,0,0,0.43846153846153846
+11.8,4.8,42,22.5,2,No Specials,SP98,0,0,0,0,0,0.4067796610169491
+13.0,6.2,32,22.5,4,No Specials,SP98,0,0,0,0,0,0.47692307692307695
+11.8,5.0,43,22.5,1,No Specials,SP98,0,0,0,0,0,0.423728813559322
+27.1,5.0,69,22.5,8,No Specials,SP98,0,0,0,0,0,0.18450184501845018
+5.2,4.6,38,22.5,8,No Specials,SP98,0,0,0,0,0,0.8846153846153845
+19.0,4.5,29,22.5,10,No Specials,E10,0,0,0,39,E10,0.23684210526315788
+12.4,4.8,38,22.5,1,No Specials,E10,0,0,0,0,0,0.3870967741935484
+25.2,5.0,55,22.5,9,No Specials,E10,0,0,0,0,0,0.19841269841269843
+14.3,4.8,36,22.5,10,No Specials,E10,0,0,0,0,0,0.3356643356643356
+11.8,4.6,40,22.5,2,No Specials,E10,0,0,0,0,0,0.38983050847457623
+16.9,4.5,48,22.5,9,sun,E10,0,0,1,0,0,0.26627218934911245
+12.4,4.6,55,22.5,11,sun,E10,0,0,1,0,0,0.3709677419354838
+17.4,4.4,36,22.5,12,sun,E10,0,0,1,0,0,0.25287356321839083
+9.2,5.7,33,22.5,8,rain,E10,0,1,0,0,0,0.6195652173913044
+12.3,5.8,54,22.5,10,rain,E10,0,1,0,0,0,0.47154471544715443
+13.0,5.9,32,22.5,10,No Specials,E10,0,0,0,0,0,0.4538461538461539
+11.8,6.1,16,22.5,6,rain,E10,0,1,0,0,0,0.5169491525423728
+13.0,5.7,37,22.5,11,rain,E10,0,1,0,0,0,0.43846153846153846
+12.3,5.0,42,22.5,10,No Specials,E10,0,0,0,0,0,0.4065040650406504
+12.3,5.2,57,22.5,15,sun,E10,0,0,1,0,0,0.4227642276422764
+12.5,4.3,57,22.5,16,sun,E10,0,0,1,0,0,0.344
+31.5,4.1,30,22.5,16,sun,E10,0,0,1,0,0,0.13015873015873014
+11.8,4.4,42,22.5,8,No Specials,E10,0,0,0,0,0,0.3728813559322034
+24.9,4.5,53,22.5,14,No Specials,E10,0,0,0,0,0,0.18072289156626506
+17.0,3.9,46,22.5,14,sun,E10,0,0,1,0,0,0.22941176470588234
+2.0,8.1,20,22.5,14,No Specials,E10,0,0,0,0,0,4.05
+11.8,4.4,33,22.5,8,No Specials,E10,0,0,0,0,0,0.3728813559322034
+7.4,5.0,31,22.5,12,No Specials,E10,0,0,0,0,0,0.6756756756756757
+12.4,4.7,55,22.5,14,sun,E10,0,0,1,0,0,0.3790322580645161
+2.0,6.0,22,22.5,14,No Specials,E10,0,0,0,0,0,3.0
+14.0,5.0,41,22.5,8,No Specials,E10,0,0,0,0,0,0.35714285714285715
+25.7,5.0,45,22.5,7,No Specials,E10,0,0,0,0,0,0.19455252918287938
+24.5,3.9,50,21.929521276595743,15,sun,E10,0,0,1,0,0,0.15918367346938775
+11.8,4.5,28,22.5,12,No Specials,E10,0,0,0,0,0,0.3813559322033898
+4.1,5.4,24,22.5,13,No Specials,E10,0,0,0,0,0,1.3170731707317076
+4.2,5.6,29,22.0,17,No Specials,E10,0,0,0,0,0,1.3333333333333333
+4.2,3.9,29,22.0,18,sun,E10,0,0,1,0,0,0.9285714285714285
+16.0,4.0,40,22.0,10,No Specials,E10,0,0,0,0,0,0.25
+22.9,4.0,29,21.929521276595743,21,No Specials,E10,0,0,0,0,0,0.17467248908296945
+16.0,3.8,42,21.929521276595743,8,No Specials,E10,0,0,0,0,0,0.2375
+15.4,4.5,50,22.0,14,No Specials,E10,0,0,0,0,0,0.2922077922077922
+16.0,3.8,41,22.0,12,No Specials,E10,0,0,0,0,0,0.2375
+4.2,5.6,32,22.0,18,No Specials,E10,0,0,0,0,0,1.3333333333333333
+101.9,5.2,75,22.0,18,No Specials,E10,0,0,0,0,0,0.05103042198233562
+93.9,4.8,88,23.0,18,AC sun,E10,1,0,1,0,0,0.051118210862619806
+25.7,4.9,50,22.0,10,rain,SP98,0,1,0,41,SP98,0.1906614785992218
+16.0,4.1,40,22.0,10,No Specials,SP98,0,0,0,0,0,0.25625
+16.1,4.5,32,22.0,19,No Specials,SP98,0,0,0,0,0,0.2795031055900621
+16.0,4.4,40,22.0,7,AC rain,SP98,1,1,0,0,0,0.275
+16.0,4.5,41,22.0,11,No Specials,SP98,0,0,0,0,0,0.28125
+24.7,4.5,26,22.0,10,No Specials,SP98,0,0,0,0,0,0.18218623481781376
+16.0,3.9,42,22.0,8,No Specials,SP98,0,0,0,0,0,0.24375
+15.4,4.6,43,22.0,16,No Specials,SP98,0,0,0,0,0,0.2987012987012987
+16.0,3.8,40,22.0,8,No Specials,SP98,0,0,0,0,0,0.2375
+32.1,4.5,50,22.0,16,No Specials,SP98,0,0,0,0,0,0.14018691588785046
+25.9,4.4,40,22.0,14,No Specials,SP98,0,0,0,0,0,0.1698841698841699
+48.6,4.3,44,22.0,12,No Specials,SP98,0,0,0,0,0,0.08847736625514403
+37.2,4.0,45,22.0,20,sun,SP98,0,0,1,0,0,0.1075268817204301
+28.8,3.9,35,22.0,15,sun,SP98,0,0,1,0,0,0.13541666666666666
+6.7,5.0,30,22.0,17,No Specials,SP98,0,0,0,0,0,0.7462686567164178
+7.4,4.1,25,22.0,18,sun,SP98,0,0,1,0,0,0.554054054054054
+17.3,4.1,22,22.0,25,sun,SP98,0,0,1,0,0,0.23699421965317916
+6.6,5.6,43,22.0,16,No Specials,SP98,0,0,0,0,0,0.8484848484848485
+14.3,4.1,26,22.0,20,No Specials,SP98,0,0,0,0,0,0.28671328671328666
+13.3,4.6,33,22.0,18,No Specials,SP98,0,0,0,0,0,0.3458646616541353
+8.3,4.9,26,22.0,23,No Specials,SP98,0,0,0,0,0,0.5903614457831325
+12.7,4.5,39,22.0,27,sun,SP98,0,0,1,0,0,0.35433070866141736
+16.5,4.1,47,22.0,14,No Specials,SP98,0,0,0,0,0,0.24848484848484848
+20.6,4.1,38,22.0,21,No Specials,SP98,0,0,0,0,0,0.1990291262135922
+16.3,4.5,58,22.0,16,No Specials,SP98,0,0,0,0,0,0.2760736196319018
+18.7,4.2,65,25.0,18,sun ac,SP98,1,0,1,0,0,0.22459893048128343
+36.5,3.9,54,23.0,18,sun,SP98,0,0,1,0,0,0.10684931506849314
+19.0,5.0,35,22.0,15,sun ac,SP98,1,0,1,0,0,0.2631578947368421
+16.6,4.4,46,22.0,5,ac,SP98,1,0,0,0,0,0.26506024096385544
+29.9,4.5,32,22.0,18,ac,SP98,1,0,0,0,0,0.1505016722408027
+16.0,3.8,42,22.0,11,No Specials,SP98,0,0,0,0,0,0.2375
+21.1,5.1,33,22.0,10,rain,SP98,0,1,0,0,0,0.24170616113744073
+16.0,3.9,40,22.0,10,No Specials,SP98,0,0,0,0,0,0.24375
+11.9,5.3,34,22.0,13,No Specials,SP98,0,0,0,0,0,0.4453781512605042
+10.1,4.2,35,22.0,16,No Specials,SP98,0,0,0,0,0,0.4158415841584159
+31.9,4.3,33,22.0,16,No Specials,SP98,0,0,0,0,0,0.13479623824451412
+18.7,4.0,60,22.0,13,No Specials,SP98,0,0,0,0,0,0.21390374331550802
+10.8,4.7,48,22.0,17,sun,SP98,0,0,1,0,0,0.4351851851851852
+19.8,4.0,56,22.0,17,sun,SP98,0,0,1,0,0,0.20202020202020202
+11.3,4.3,38,22.0,17,No Specials,SP98,0,0,0,37,SP98,0.3805309734513274
+11.5,5.3,53,22.0,15,No Specials,SP98,0,0,0,0,0,0.4608695652173913
+21.4,5.2,51,22.0,13,No Specials,SP98,0,0,0,0,0,0.2429906542056075
+32.0,4.9,53,22.0,15,No Specials,SP98,0,0,0,0,0,0.153125
+41.9,4.7,53,22.0,14,No Specials,SP98,0,0,0,0,0,0.11217183770883056
+211.0,4.6,80,22.0,20,No Specials,SP98,0,0,0,0,0,0.021800947867298578
+216.1,5.3,90,22.0,21,sun,SP98,0,0,1,0,0,0.024525682554372975
+25.5,3.6,27,22.0,27,sun,SP98,0,0,1,0,0,0.1411764705882353
+16.6,4.2,52,22.0,15,rain,SP98,0,1,0,0,0,0.25301204819277107
+25.9,4.1,43,22.0,24,No Specials,SP98,0,0,0,0,0,0.1583011583011583
+16.5,4.0,48,22.0,15,No Specials,SP98,0,0,0,0,0,0.24242424242424243
+22.1,3.9,29,22.0,26,No Specials,SP98,0,0,0,0,0,0.1764705882352941
+16.6,3.7,49,22.0,17,No Specials,E10,0,0,0,"37,7",E10,0.22289156626506024
+15.4,4.5,43,22.0,24,No Specials,E10,0,0,0,0,0,0.2922077922077922
+16.5,3.9,43,22.0,17,No Specials,E10,0,0,0,0,0,0.23636363636363636
+15.4,5.1,21,22.0,24,No Specials,E10,0,0,0,0,0,0.3311688311688311
+18.4,4.2,59,22.0,24,No Specials,E10,0,0,0,0,0,0.2282608695652174
+39.5,4.2,58,22.0,25,No Specials,E10,0,0,0,0,0,0.10632911392405063
+21.5,4.8,47,25.0,27,AC Sun,E10,1,0,1,0,0,0.22325581395348837
+4.8,4.7,26,25.0,18,No Specials,E10,0,0,0,0,0,0.9791666666666667
+100.9,4.7,87,23.5,22,No Specials,E10,0,0,0,0,0,0.04658077304261645
+129.7,4.6,58,24.0,21,ac,E10,0,0,0,0,0,0.035466461063993836
+16.6,3.8,43,21.5,16,No Specials,E10,0,0,0,0,0,0.22891566265060237
+15.4,4.2,50,21.5,21,No Specials,E10,0,0,0,0,0,0.2727272727272727
+16.0,3.7,45,22.0,17,No Specials,E10,0,0,0,0,0,0.23125
+16.0,4.2,41,22.0,15,No Specials,E10,0,0,0,0,0,0.2625
+15.4,4.1,45,22.0,24,No Specials,E10,0,0,0,0,0,0.2662337662337662
+16.0,4.0,43,22.0,16,No Specials,E10,0,0,0,0,0,0.25
+21.0,3.8,37,22.0,21,No Specials,E10,0,0,0,0,0,0.18095238095238095
+15.4,3.8,47,22.0,24,No Specials,E10,0,0,0,0,0,0.24675324675324672
+16.0,3.8,42,22.0,17,No Specials,E10,0,0,0,0,0,0.2375
+16.1,5.1,30,25.0,16,ac rain,E10,1,1,0,0,0,0.31677018633540366
+16.0,4.0,42,22.0,15,No Specials,E10,0,0,0,0,0,0.25
+15.4,4.8,40,22.0,18,No Specials,E10,0,0,0,0,0,0.3116883116883117
+17.2,3.9,35,22.0,16,No Specials,E10,0,0,0,0,0,0.22674418604651164
+16.6,4.6,50,22.0,25,No Specials,E10,0,0,0,0,0,0.2771084337349397
+18.3,4.3,46,22.0,16,No Specials,SP98,0,0,0,"37,2",SP98,0.2349726775956284
+16.1,4.8,36,22.0,18,rain,SP98,0,1,0,0,0,0.29813664596273287
+16.0,4.1,46,22.0,17,No Specials,SP98,0,0,0,0,0,0.25625
+16.3,4.0,35,22.0,23,No Specials,SP98,0,0,0,0,0,0.24539877300613497
+16.0,3.7,44,22.0,16,No Specials,SP98,0,0,0,0,0,0.23125
+18.3,4.3,46,22.0,23,No Specials,SP98,0,0,0,0,0,0.2349726775956284
+4.5,5.2,23,22.0,23,sun,SP98,0,0,1,0,0,1.1555555555555557
+17.0,4.2,48,22.0,16,No Specials,SP98,0,0,0,0,0,0.24705882352941178
+6.1,5.0,35,24.5,18,No Specials,SP98,0,0,0,0,0,0.819672131147541
+6.1,5.0,33,22.0,24,sun,SP98,0,0,1,0,0,0.819672131147541
+17.3,4.2,36,22.0,22,No Specials,SP98,0,0,0,0,0,0.24277456647398843
+6.0,4.8,27,22.0,17,No Specials,SP98,0,0,0,0,0,0.7999999999999999
+16.0,4.1,45,22.0,15,No Specials,SP98,0,0,0,0,0,0.25625
+15.4,4.9,55,22.0,18,No Specials,SP98,0,0,0,0,0,0.3181818181818182
+15.4,4.3,39,22.0,23,No Specials,SP98,0,0,0,0,0,0.2792207792207792
+16.0,3.9,35,22.0,18,No Specials,SP98,0,0,0,0,0,0.24375
+15.4,4.5,52,22.0,26,No Specials,SP98,0,0,0,0,0,0.2922077922077922
+16.6,4.1,48,25.5,30,sun ac,SP98,1,0,1,0,0,0.24698795180722888
+15.4,5.0,48,25.5,31,ac,SP98,1,0,0,0,0,0.3246753246753247
+16.0,4.0,43,22.0,21,ac,SP98,1,0,0,0,0,0.25
+15.4,4.5,42,22.0,30,No Specials,SP98,0,0,0,0,0,0.2922077922077922
+16.0,3.6,43,22.0,19,No Specials,SP98,0,0,0,0,0,0.225
+20.9,4.1,33,22.0,21,No Specials,SP98,0,0,0,0,0,0.19617224880382775
+32.1,3.9,47,22.0,26,No Specials,SP98,0,0,0,0,0,0.12149532710280372
+15.3,6.6,16,24.0,27,ac,SP98,1,0,0,0,0,0.4313725490196078
+28.5,4.0,44,25.0,23,ac,SP98,1,0,0,0,0,0.14035087719298245
+11.9,3.7,33,25.0,19,No Specials,SP98,0,0,0,0,0,0.31092436974789917
+14.5,4.3,36,25.0,22,No Specials,SP98,0,0,0,0,0,0.296551724137931
+16.6,4.1,49,22.0,26,sun,SP98,0,0,1,0,0,0.24698795180722888
+16.2,4.4,39,24.5,17,ac,SP98,1,0,0,0,0,0.271604938271605
+16.7,3.8,44,24.5,23,sun,SP98,0,0,1,0,0,0.2275449101796407
+8.3,5.0,52,24.5,27,No Specials,SP98,0,0,0,0,0,0.6024096385542168
+5.5,3.7,33,24.5,28,sun,SP98,0,0,1,0,0,0.6727272727272727
+13.6,3.7,33,24.5,28,sun,SP98,0,0,1,0,0,0.2720588235294118
+16.0,3.7,39,24.5,18,No Specials,SP98,0,0,0,0,0,0.23125
+16.1,4.3,38,25.0,31,AC,SP98,1,0,0,0,0,0.26708074534161486
+16.0,3.8,45,25.0,19,No Specials,SP98,0,0,0,0,0,0.2375
+15.4,4.6,42,25.0,31,AC,SP98,1,0,0,0,0,0.2987012987012987
+14.7,5.0,25,25.0,30,AC,SP98,1,0,0,0,0,0.3401360544217687