diff --git a/notebooks/Challenge.ipynb b/notebooks/Challenge.ipynb
new file mode 100644
index 0000000..5db6724
--- /dev/null
+++ b/notebooks/Challenge.ipynb
@@ -0,0 +1,1625 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Show all columns in pandas\n",
+    "pd.set_option('display.max_columns', None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "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": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = pd.read_csv('../data/measurements.csv')\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "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>28.0</td>\n",
+       "      <td>5.0</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>45.0</td>\n",
+       "      <td>E10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12.0</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>16.0</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>25.0</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>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>385</th>\n",
+       "      <td>16.0</td>\n",
+       "      <td>3.8</td>\n",
+       "      <td>45</td>\n",
+       "      <td>25.0</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>25.0</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>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>387</th>\n",
+       "      <td>14.7</td>\n",
+       "      <td>5.0</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>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  \\\n",
+       "0        28.0      5.0     26         21.5            12      NaN      E10   \n",
+       "1        12.0      4.2     30         21.5            13      NaN      E10   \n",
+       "2        11.2      5.5     38         21.5            15      NaN      E10   \n",
+       "3        12.9      3.9     36         21.5            14      NaN      E10   \n",
+       "4        18.5      4.5     46         21.5            15      NaN      E10   \n",
+       "..        ...      ...    ...          ...           ...      ...      ...   \n",
+       "383      16.0      3.7     39         24.5            18      NaN     SP98   \n",
+       "384      16.1      4.3     38         25.0            31       AC     SP98   \n",
+       "385      16.0      3.8     45         25.0            19      NaN     SP98   \n",
+       "386      15.4      4.6     42         25.0            31       AC     SP98   \n",
+       "387      14.7      5.0     25         25.0            30       AC     SP98   \n",
+       "\n",
+       "     AC  rain  sun  refill liters refill gas  \n",
+       "0     0     0    0           45.0        E10  \n",
+       "1     0     0    0            NaN        NaN  \n",
+       "2     0     0    0            NaN        NaN  \n",
+       "3     0     0    0            NaN        NaN  \n",
+       "4     0     0    0            NaN        NaN  \n",
+       "..   ..   ...  ...            ...        ...  \n",
+       "383   0     0    0            NaN        NaN  \n",
+       "384   1     0    0            NaN        NaN  \n",
+       "385   0     0    0            NaN        NaN  \n",
+       "386   1     0    0            NaN        NaN  \n",
+       "387   1     0    0            NaN        NaN  \n",
+       "\n",
+       "[388 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data2 = pd.read_excel('../data/measurements2.xlsx')\n",
+    "data2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Both files look the same."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "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": [
+    "data.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The columns 'distance', 'consume', 'temp_inside' have values with data type object and need to be converted to floats: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The error we're encountering seems to stem from the format. We'll replace ',' with '.'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data['distance'] = data['distance'].str.replace(',', '.')\n",
+    "data['consume'] = data['consume'].str.replace(',', '.')\n",
+    "data['temp_inside'] = data['temp_inside'].str.replace(',', '.')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data['distance'] = pd.to_numeric(data['distance'], errors='coerce')\n",
+    "data['consume'] = pd.to_numeric(data['consume'], errors='coerce')\n",
+    "data['temp_inside'] = pd.to_numeric(data['temp_inside'], errors='coerce')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "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    float64\n",
+      " 1   consume        388 non-null    float64\n",
+      " 2   speed          388 non-null    int64  \n",
+      " 3   temp_inside    376 non-null    float64\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: float64(3), int64(5), object(4)\n",
+      "memory usage: 36.5+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "data.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "numeric_data = data.select_dtypes(include=['float64', 'int64'])\n",
+    "categoric_data = data.select_dtypes(include=['object'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "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>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>376.000000</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>19.652835</td>\n",
+       "      <td>4.912371</td>\n",
+       "      <td>41.927835</td>\n",
+       "      <td>21.929521</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>22.667837</td>\n",
+       "      <td>1.033172</td>\n",
+       "      <td>13.598524</td>\n",
+       "      <td>1.010455</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>1.300000</td>\n",
+       "      <td>3.300000</td>\n",
+       "      <td>14.000000</td>\n",
+       "      <td>19.000000</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>11.800000</td>\n",
+       "      <td>4.300000</td>\n",
+       "      <td>32.750000</td>\n",
+       "      <td>21.500000</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>14.600000</td>\n",
+       "      <td>4.700000</td>\n",
+       "      <td>40.500000</td>\n",
+       "      <td>22.000000</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>19.000000</td>\n",
+       "      <td>5.300000</td>\n",
+       "      <td>50.000000</td>\n",
+       "      <td>22.500000</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>216.100000</td>\n",
+       "      <td>12.200000</td>\n",
+       "      <td>90.000000</td>\n",
+       "      <td>25.500000</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": [
+       "         distance     consume       speed  temp_inside  temp_outside  \\\n",
+       "count  388.000000  388.000000  388.000000   376.000000    388.000000   \n",
+       "mean    19.652835    4.912371   41.927835    21.929521     11.358247   \n",
+       "std     22.667837    1.033172   13.598524     1.010455      6.991542   \n",
+       "min      1.300000    3.300000   14.000000    19.000000     -5.000000   \n",
+       "25%     11.800000    4.300000   32.750000    21.500000      7.000000   \n",
+       "50%     14.600000    4.700000   40.500000    22.000000     10.000000   \n",
+       "75%     19.000000    5.300000   50.000000    22.500000     16.000000   \n",
+       "max    216.100000   12.200000   90.000000    25.500000     31.000000   \n",
+       "\n",
+       "               AC        rain         sun  \n",
+       "count  388.000000  388.000000  388.000000  \n",
+       "mean     0.077320    0.123711    0.082474  \n",
+       "std      0.267443    0.329677    0.275441  \n",
+       "min      0.000000    0.000000    0.000000  \n",
+       "25%      0.000000    0.000000    0.000000  \n",
+       "50%      0.000000    0.000000    0.000000  \n",
+       "75%      0.000000    0.000000    0.000000  \n",
+       "max      1.000000    1.000000    1.000000  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "numeric_data.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can see the data is differently distributed in the different columns and also the ranges are different. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next we check the unique values of the categorical columns: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['specials', 'gas_type', 'refill liters', 'refill gas'], dtype='object')"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "categoric_data.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "rain                  32\n",
+       "sun                   27\n",
+       "AC rain                9\n",
+       "ac                     8\n",
+       "AC                     6\n",
+       "snow                   3\n",
+       "sun ac                 3\n",
+       "AC snow                1\n",
+       "half rain half sun     1\n",
+       "AC sun                 1\n",
+       "AC Sun                 1\n",
+       "ac rain                1\n",
+       "Name: specials, dtype: int64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "categoric_data['specials'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can see there are values, which are the same, but are spelled differently, we correct that: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "value_mapping = {\n",
+    "    'ac': 'AC',\n",
+    "    'AC Sun': 'AC sun',\n",
+    "    'sun ac': 'AC sun',\n",
+    "    'ac rain': 'AC rain',\n",
+    "}\n",
+    "\n",
+    "data['specials'] = categoric_data['specials'].replace(value_mapping)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SP98    228\n",
+       "E10     160\n",
+       "Name: gas_type, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "categoric_data['gas_type'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Checking for missing values: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "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>column_name</th>\n",
+       "      <th>percentage_of_missing_values</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>distance</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>consume</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speed</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>temp_inside</td>\n",
+       "      <td>3.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>temp_outside</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>specials</td>\n",
+       "      <td>76.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>gas_type</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>AC</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>rain</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>sun</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>refill liters</td>\n",
+       "      <td>96.65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>refill gas</td>\n",
+       "      <td>96.65</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      column_name  percentage_of_missing_values\n",
+       "0        distance                          0.00\n",
+       "1         consume                          0.00\n",
+       "2           speed                          0.00\n",
+       "3     temp_inside                          3.09\n",
+       "4    temp_outside                          0.00\n",
+       "5        specials                         76.03\n",
+       "6        gas_type                          0.00\n",
+       "7              AC                          0.00\n",
+       "8            rain                          0.00\n",
+       "9             sun                          0.00\n",
+       "10  refill liters                         96.65\n",
+       "11     refill gas                         96.65"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "missing_values_df = pd.DataFrame(round(data.isna().sum()/len(data),4)*100)\n",
+    "missing_values_df = missing_values_df.reset_index()\n",
+    "missing_values_df.columns = ['column_name', 'percentage_of_missing_values']\n",
+    "display(missing_values_df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Columns 10 and 11 contain too many missing values and we`re going to drop them."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data.drop(columns=['refill liters', 'refill gas'], inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "rain                  32\n",
+       "sun                   27\n",
+       "AC                    14\n",
+       "AC rain               10\n",
+       "AC sun                 5\n",
+       "snow                   3\n",
+       "AC snow                1\n",
+       "half rain half sun     1\n",
+       "Name: specials, dtype: int64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data['specials'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Most of the data from this column has already been coded in the columns 'AC' 'rain' 'sun' therefor we can drop it. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data.drop(columns='specials', inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I am not sure if we are going to need this column since we already have the most important info in other columns. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.histplot(data['temp_inside'], kde=True, color='blue')\n",
+    "plt.title('Distribution of Temperature Data (temp_inside)')\n",
+    "plt.xlabel('Temperature')\n",
+    "plt.ylabel('Frequency')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We'll fill the missing values in the column temp_inside with the mean 21.92, rounded 22.00 because:\n",
+    "- we have continious data\n",
+    "- we have ordinal data (temperature)\n",
+    "- the range of the data is not very big\n",
+    "- std of 1 indicates a tight distribution\n",
+    "- we can see that we don`t have any major outliers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data['temp_inside'].fillna(22.00, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we check for duplicates:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "No duplicate rows found.\n"
+     ]
+    }
+   ],
+   "source": [
+    "duplicate_rows = data[data.duplicated()]\n",
+    "\n",
+    "if not duplicate_rows.empty:\n",
+    "    print(\"Duplicate rows found:\")\n",
+    "    print(duplicate_rows)\n",
+    "else:\n",
+    "    print(\"No duplicate rows found.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "numeric_data = data.select_dtypes(include=['float64', 'int64'])\n",
+    "categoric_data = data.select_dtypes(include=['object', 'int64'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "categoric_data.drop(columns=['temp_outside', 'speed'], inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We check the distribution of the categoric data:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for column in categoric_data.columns:\n",
+    "    sns.countplot(x=column, data=categoric_data)\n",
+    "    plt.title(f'Distribution of {column}')\n",
+    "    plt.xlabel(column)\n",
+    "    plt.ylabel('Count')\n",
+    "    plt.xticks(rotation=45)  # Rotate x-axis labels for better visibility if needed\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can see that there is a significant data imbalance in the columns 'AC', 'rain', 'sun', in the 'fuel' column the imbalance is low. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "exclude_columns = ['AC', 'sun', 'rain']\n",
+    "\n",
+    "for column in numeric_data.columns:\n",
+    "    if column not in exclude_columns:\n",
+    "        sns.histplot(numeric_data[column], kde=True)\n",
+    "        plt.title(f'Histogram of {column}')\n",
+    "        plt.xlabel(column)\n",
+    "        plt.ylabel('Frequency')\n",
+    "        plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We see that columns 'distance' and 'consume' are right skewed, which means we`re going to have to scale before modelling. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "But first we check the correlation matrix for colinearity between features: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before we do this, we encode the gas_type column:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_encoded = pd.get_dummies(data, columns=['gas_type'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "correlation_matrix = data_encoded.corr()\n",
+    "\n",
+    "plt.figure(figsize=(8, 6)) \n",
+    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
+    "plt.title(\"Correlation Matrix of Data\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We don't see any colinearity except between distance and speed. As long as it`s lower than 0.8 we do nothing and proceed. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "from sklearn.metrics import mean_squared_error"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = data_encoded.drop(columns='consume')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y = data_encoded['consume']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+    "scaler = StandardScaler()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train_scaled = scaler.fit_transform(X_train)\n",
+    "X_test_scaled = scaler.transform(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.linear_model import LinearRegression"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = LinearRegression()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LinearRegression</label><div class=\"sk-toggleable__content\"><pre>LinearRegression()</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "LinearRegression()"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y_pred = model.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mean Squared Error: 0.8219075821875492\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Evaluate the model\n",
+    "mse = mean_squared_error(y_test, y_pred)\n",
+    "print(\"Mean Squared Error:\", mse)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.6598027559858758 0.9065911880156068 0.09412310938686286\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
+    "\n",
+    "# Calculate MAE\n",
+    "mae = mean_absolute_error(y_test, y_pred)\n",
+    "\n",
+    "# Calculate RMSE\n",
+    "rmse = mean_squared_error(y_test, y_pred, squared=False)\n",
+    "\n",
+    "# Calculate R-squared\n",
+    "r_squared = r2_score(y_test, y_pred)\n",
+    "\n",
+    "print(mae, rmse, r_squared)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Overall, these metrics suggest that the model's predictive performance is not very strong. The MAE and RMSE indicate that the model's predictions have a considerable amount of error compared to the actual values, and the low R-squared value suggests that the model explains only a small portion of the variance in the target variable.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot actual vs. predicted values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.regplot(x=y_test, y=y_pred, scatter_kws={'s': 20}) \n",
+    "plt.title('Actual vs. Predicted Values with Regression Line')\n",
+    "plt.xlabel('Actual Values')\n",
+    "plt.ylabel('Predicted Values')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "With more time and more data we can check other models to predict the consumption. "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}