EDA with Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "4039a31d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "import seaborn as sns\n",
    "\n",
    "plt.style.use('ggplot')\n",
    "pd.set_option('display.max_columns', 200) #to visualize all columns in dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "097c1142",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('coaster_db.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9254902f",
   "metadata": {},
   "source": [
    "### STEP 1: DATA UNDERSTANDING ###\n",
    "- _shape_\n",
    "- _head_ and _tail_\n",
    "- _dtypes_\n",
    "- _describe_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "06e1e51d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1087, 56)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape  #rows,columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9a03e096",
   "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>coaster_name</th>\n",
       "      <th>Length</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Location</th>\n",
       "      <th>Status</th>\n",
       "      <th>Opening date</th>\n",
       "      <th>Type</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Height restriction</th>\n",
       "      <th>Model</th>\n",
       "      <th>Height</th>\n",
       "      <th>Inversions</th>\n",
       "      <th>Lift/launch system</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Trains</th>\n",
       "      <th>Park section</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Capacity</th>\n",
       "      <th>G-force</th>\n",
       "      <th>Designer</th>\n",
       "      <th>Max vertical angle</th>\n",
       "      <th>Drop</th>\n",
       "      <th>Soft opening date</th>\n",
       "      <th>Fast Lane available</th>\n",
       "      <th>Replaced</th>\n",
       "      <th>Track layout</th>\n",
       "      <th>Fastrack available</th>\n",
       "      <th>Soft opening date.1</th>\n",
       "      <th>Closing date</th>\n",
       "      <th>Opened</th>\n",
       "      <th>Replaced by</th>\n",
       "      <th>Website</th>\n",
       "      <th>Flash Pass Available</th>\n",
       "      <th>Must transfer from wheelchair</th>\n",
       "      <th>Theme</th>\n",
       "      <th>Single rider line available</th>\n",
       "      <th>Restraint Style</th>\n",
       "      <th>Flash Pass available</th>\n",
       "      <th>Acceleration</th>\n",
       "      <th>Restraints</th>\n",
       "      <th>Name</th>\n",
       "      <th>year_introduced</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Type_Main</th>\n",
       "      <th>opening_date_clean</th>\n",
       "      <th>speed1</th>\n",
       "      <th>speed2</th>\n",
       "      <th>speed1_value</th>\n",
       "      <th>speed1_unit</th>\n",
       "      <th>speed_mph</th>\n",
       "      <th>height_value</th>\n",
       "      <th>height_unit</th>\n",
       "      <th>height_ft</th>\n",
       "      <th>Inversions_clean</th>\n",
       "      <th>Gforce_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switchback Railway</td>\n",
       "      <td>600 ft (180 m)</td>\n",
       "      <td>6 mph (9.7 km/h)</td>\n",
       "      <td>Coney Island</td>\n",
       "      <td>Removed</td>\n",
       "      <td>June 16, 1884</td>\n",
       "      <td>Wood</td>\n",
       "      <td>LaMarcus Adna Thompson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lift Packed</td>\n",
       "      <td>50 ft (15 m)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gravity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Coney Island Cyclone Site</td>\n",
       "      <td>1:00</td>\n",
       "      <td>1600 riders per hour</td>\n",
       "      <td>2.9</td>\n",
       "      <td>LaMarcus Adna Thompson</td>\n",
       "      <td>30°</td>\n",
       "      <td>43 ft (13 m)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gravity pulled coaster</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1884</td>\n",
       "      <td>40.5740</td>\n",
       "      <td>-73.9780</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1884-06-16</td>\n",
       "      <td>6 mph</td>\n",
       "      <td>9.7 km/h</td>\n",
       "      <td>6.0</td>\n",
       "      <td>mph</td>\n",
       "      <td>6.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>ft</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Flip Flap Railway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sea Lion Park</td>\n",
       "      <td>Removed</td>\n",
       "      <td>1895</td>\n",
       "      <td>Wood</td>\n",
       "      <td>Lina Beecher</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a single car. Riders are arranged 1 across in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>Lina Beecher</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1902</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>40.5780</td>\n",
       "      <td>-73.9790</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1895-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Switchback Railway (Euclid Beach Park)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cleveland, Ohio, United States</td>\n",
       "      <td>Closed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1896</td>\n",
       "      <td>41.5800</td>\n",
       "      <td>-81.5700</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Loop the Loop (Coney Island)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>Removed</td>\n",
       "      <td>1901</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Edwin Prescott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a single car. Riders are arranged 2 across in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Edward A. Green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Switchback Railway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1910</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Giant Racer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1901</td>\n",
       "      <td>40.5745</td>\n",
       "      <td>-73.9780</td>\n",
       "      <td>Steel</td>\n",
       "      <td>1901-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Loop the Loop (Young's Pier)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>Removed</td>\n",
       "      <td>1901</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Edwin Prescott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Edward A. Green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1912</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1901</td>\n",
       "      <td>39.3538</td>\n",
       "      <td>-74.4342</td>\n",
       "      <td>Steel</td>\n",
       "      <td>1901-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             coaster_name          Length             Speed  \\\n",
       "0                      Switchback Railway  600 ft (180 m)  6 mph (9.7 km/h)   \n",
       "1                       Flip Flap Railway             NaN               NaN   \n",
       "2  Switchback Railway (Euclid Beach Park)             NaN               NaN   \n",
       "3            Loop the Loop (Coney Island)             NaN               NaN   \n",
       "4            Loop the Loop (Young's Pier)             NaN               NaN   \n",
       "\n",
       "                         Location   Status   Opening date   Type  \\\n",
       "0                    Coney Island  Removed  June 16, 1884   Wood   \n",
       "1                   Sea Lion Park  Removed           1895   Wood   \n",
       "2  Cleveland, Ohio, United States   Closed            NaN  Other   \n",
       "3                           Other  Removed           1901  Steel   \n",
       "4                           Other  Removed           1901  Steel   \n",
       "\n",
       "             Manufacturer Height restriction        Model        Height  \\\n",
       "0  LaMarcus Adna Thompson                NaN  Lift Packed  50 ft (15 m)   \n",
       "1            Lina Beecher                NaN          NaN           NaN   \n",
       "2                     NaN                NaN          NaN           NaN   \n",
       "3          Edwin Prescott                NaN          NaN           NaN   \n",
       "4          Edwin Prescott                NaN          NaN           NaN   \n",
       "\n",
       "   Inversions Lift/launch system Cost  \\\n",
       "0         NaN            gravity  NaN   \n",
       "1         1.0                NaN  NaN   \n",
       "2         NaN                NaN  NaN   \n",
       "3         1.0                NaN  NaN   \n",
       "4         1.0                NaN  NaN   \n",
       "\n",
       "                                              Trains  \\\n",
       "0                                                NaN   \n",
       "1  a single car. Riders are arranged 1 across in ...   \n",
       "2                                                NaN   \n",
       "3  a single car. Riders are arranged 2 across in ...   \n",
       "4                                                NaN   \n",
       "\n",
       "                Park section Duration              Capacity G-force  \\\n",
       "0  Coney Island Cyclone Site     1:00  1600 riders per hour     2.9   \n",
       "1                        NaN      NaN                   NaN      12   \n",
       "2                        NaN      NaN                   NaN     NaN   \n",
       "3                        NaN      NaN                   NaN     NaN   \n",
       "4                        NaN      NaN                   NaN     NaN   \n",
       "\n",
       "                 Designer Max vertical angle          Drop Soft opening date  \\\n",
       "0  LaMarcus Adna Thompson                30°  43 ft (13 m)               NaN   \n",
       "1            Lina Beecher                NaN           NaN               NaN   \n",
       "2                     NaN                NaN           NaN               NaN   \n",
       "3         Edward A. Green                NaN           NaN               NaN   \n",
       "4         Edward A. Green                NaN           NaN               NaN   \n",
       "\n",
       "  Fast Lane available            Replaced            Track layout  \\\n",
       "0                 NaN                 NaN  Gravity pulled coaster   \n",
       "1                 NaN                 NaN                     NaN   \n",
       "2                 NaN                 NaN                     NaN   \n",
       "3                 NaN  Switchback Railway                     NaN   \n",
       "4                 NaN                 NaN                     NaN   \n",
       "\n",
       "  Fastrack available Soft opening date.1 Closing date Opened  Replaced by  \\\n",
       "0                NaN                 NaN          NaN    NaN          NaN   \n",
       "1                NaN                 NaN         1902    NaN          NaN   \n",
       "2                NaN                 NaN          NaN   1895          NaN   \n",
       "3                NaN                 NaN         1910    NaN  Giant Racer   \n",
       "4                NaN                 NaN         1912    NaN          NaN   \n",
       "\n",
       "  Website Flash Pass Available Must transfer from wheelchair Theme  \\\n",
       "0     NaN                  NaN                           NaN   NaN   \n",
       "1     NaN                  NaN                           NaN   NaN   \n",
       "2     NaN                  NaN                           NaN   NaN   \n",
       "3     NaN                  NaN                           NaN   NaN   \n",
       "4     NaN                  NaN                           NaN   NaN   \n",
       "\n",
       "  Single rider line available Restraint Style Flash Pass available  \\\n",
       "0                         NaN             NaN                  NaN   \n",
       "1                         NaN             NaN                  NaN   \n",
       "2                         NaN             NaN                  NaN   \n",
       "3                         NaN             NaN                  NaN   \n",
       "4                         NaN             NaN                  NaN   \n",
       "\n",
       "  Acceleration Restraints Name  year_introduced  latitude  longitude  \\\n",
       "0          NaN        NaN  NaN             1884   40.5740   -73.9780   \n",
       "1          NaN        NaN  NaN             1895   40.5780   -73.9790   \n",
       "2          NaN        NaN  NaN             1896   41.5800   -81.5700   \n",
       "3          NaN        NaN  NaN             1901   40.5745   -73.9780   \n",
       "4          NaN        NaN  NaN             1901   39.3538   -74.4342   \n",
       "\n",
       "  Type_Main opening_date_clean  speed1    speed2  speed1_value speed1_unit  \\\n",
       "0      Wood         1884-06-16  6 mph   9.7 km/h           6.0         mph   \n",
       "1      Wood         1895-01-01     NaN       NaN           NaN         NaN   \n",
       "2     Other                NaN     NaN       NaN           NaN         NaN   \n",
       "3     Steel         1901-01-01     NaN       NaN           NaN         NaN   \n",
       "4     Steel         1901-01-01     NaN       NaN           NaN         NaN   \n",
       "\n",
       "   speed_mph  height_value height_unit  height_ft  Inversions_clean  \\\n",
       "0        6.0          50.0          ft        NaN                 0   \n",
       "1        NaN           NaN         NaN        NaN                 1   \n",
       "2        NaN           NaN         NaN        NaN                 0   \n",
       "3        NaN           NaN         NaN        NaN                 1   \n",
       "4        NaN           NaN         NaN        NaN                 1   \n",
       "\n",
       "   Gforce_clean  \n",
       "0           2.9  \n",
       "1          12.0  \n",
       "2           NaN  \n",
       "3           NaN  \n",
       "4           NaN  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1bd80f92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['coaster_name', 'Length', 'Speed', 'Location', 'Status', 'Opening date',\n",
       "       'Type', 'Manufacturer', 'Height restriction', 'Model', 'Height',\n",
       "       'Inversions', 'Lift/launch system', 'Cost', 'Trains', 'Park section',\n",
       "       'Duration', 'Capacity', 'G-force', 'Designer', 'Max vertical angle',\n",
       "       'Drop', 'Soft opening date', 'Fast Lane available', 'Replaced',\n",
       "       'Track layout', 'Fastrack available', 'Soft opening date.1',\n",
       "       'Closing date', 'Opened', 'Replaced by', 'Website',\n",
       "       'Flash Pass Available', 'Must transfer from wheelchair', 'Theme',\n",
       "       'Single rider line available', 'Restraint Style',\n",
       "       'Flash Pass available', 'Acceleration', 'Restraints', 'Name',\n",
       "       'year_introduced', 'latitude', 'longitude', 'Type_Main',\n",
       "       'opening_date_clean', 'speed1', 'speed2', 'speed1_value', 'speed1_unit',\n",
       "       'speed_mph', 'height_value', 'height_unit', 'height_ft',\n",
       "       'Inversions_clean', 'Gforce_clean'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "42212fcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "coaster_name                      object\n",
       "Length                            object\n",
       "Speed                             object\n",
       "Location                          object\n",
       "Status                            object\n",
       "Opening date                      object\n",
       "Type                              object\n",
       "Manufacturer                      object\n",
       "Height restriction                object\n",
       "Model                             object\n",
       "Height                            object\n",
       "Inversions                       float64\n",
       "Lift/launch system                object\n",
       "Cost                              object\n",
       "Trains                            object\n",
       "Park section                      object\n",
       "Duration                          object\n",
       "Capacity                          object\n",
       "G-force                           object\n",
       "Designer                          object\n",
       "Max vertical angle                object\n",
       "Drop                              object\n",
       "Soft opening date                 object\n",
       "Fast Lane available               object\n",
       "Replaced                          object\n",
       "Track layout                      object\n",
       "Fastrack available                object\n",
       "Soft opening date.1               object\n",
       "Closing date                      object\n",
       "Opened                            object\n",
       "Replaced by                       object\n",
       "Website                           object\n",
       "Flash Pass Available              object\n",
       "Must transfer from wheelchair     object\n",
       "Theme                             object\n",
       "Single rider line available       object\n",
       "Restraint Style                   object\n",
       "Flash Pass available              object\n",
       "Acceleration                      object\n",
       "Restraints                        object\n",
       "Name                              object\n",
       "year_introduced                    int64\n",
       "latitude                         float64\n",
       "longitude                        float64\n",
       "Type_Main                         object\n",
       "opening_date_clean                object\n",
       "speed1                            object\n",
       "speed2                            object\n",
       "speed1_value                     float64\n",
       "speed1_unit                       object\n",
       "speed_mph                        float64\n",
       "height_value                     float64\n",
       "height_unit                       object\n",
       "height_ft                        float64\n",
       "Inversions_clean                   int64\n",
       "Gforce_clean                     float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes     #each column is a series, which type of data it is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "2c20b654",
   "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>Inversions</th>\n",
       "      <th>year_introduced</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>speed1_value</th>\n",
       "      <th>speed_mph</th>\n",
       "      <th>height_value</th>\n",
       "      <th>height_ft</th>\n",
       "      <th>Inversions_clean</th>\n",
       "      <th>Gforce_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>932.000000</td>\n",
       "      <td>1087.000000</td>\n",
       "      <td>812.000000</td>\n",
       "      <td>812.000000</td>\n",
       "      <td>937.000000</td>\n",
       "      <td>937.000000</td>\n",
       "      <td>965.000000</td>\n",
       "      <td>171.000000</td>\n",
       "      <td>1087.000000</td>\n",
       "      <td>362.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.547210</td>\n",
       "      <td>1994.986201</td>\n",
       "      <td>38.373484</td>\n",
       "      <td>-41.595373</td>\n",
       "      <td>53.850374</td>\n",
       "      <td>48.617289</td>\n",
       "      <td>89.575171</td>\n",
       "      <td>101.996491</td>\n",
       "      <td>1.326587</td>\n",
       "      <td>3.824006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.114073</td>\n",
       "      <td>23.475248</td>\n",
       "      <td>15.516596</td>\n",
       "      <td>72.285227</td>\n",
       "      <td>23.385518</td>\n",
       "      <td>16.678031</td>\n",
       "      <td>136.246444</td>\n",
       "      <td>67.329092</td>\n",
       "      <td>2.030854</td>\n",
       "      <td>0.989998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1884.000000</td>\n",
       "      <td>-48.261700</td>\n",
       "      <td>-123.035700</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>13.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1989.000000</td>\n",
       "      <td>35.031050</td>\n",
       "      <td>-84.552200</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>37.300000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>51.800000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>40.289800</td>\n",
       "      <td>-76.653600</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>49.700000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>91.200000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>44.799600</td>\n",
       "      <td>2.778100</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>131.200000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>14.000000</td>\n",
       "      <td>2022.000000</td>\n",
       "      <td>63.230900</td>\n",
       "      <td>153.426500</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>149.100000</td>\n",
       "      <td>3937.000000</td>\n",
       "      <td>377.300000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Inversions  year_introduced    latitude   longitude  speed1_value  \\\n",
       "count  932.000000      1087.000000  812.000000  812.000000    937.000000   \n",
       "mean     1.547210      1994.986201   38.373484  -41.595373     53.850374   \n",
       "std      2.114073        23.475248   15.516596   72.285227     23.385518   \n",
       "min      0.000000      1884.000000  -48.261700 -123.035700      5.000000   \n",
       "25%      0.000000      1989.000000   35.031050  -84.552200     40.000000   \n",
       "50%      0.000000      2000.000000   40.289800  -76.653600     50.000000   \n",
       "75%      3.000000      2010.000000   44.799600    2.778100     63.000000   \n",
       "max     14.000000      2022.000000   63.230900  153.426500    240.000000   \n",
       "\n",
       "        speed_mph  height_value   height_ft  Inversions_clean  Gforce_clean  \n",
       "count  937.000000    965.000000  171.000000       1087.000000    362.000000  \n",
       "mean    48.617289     89.575171  101.996491          1.326587      3.824006  \n",
       "std     16.678031    136.246444   67.329092          2.030854      0.989998  \n",
       "min      5.000000      4.000000   13.100000          0.000000      0.800000  \n",
       "25%     37.300000     44.000000   51.800000          0.000000      3.400000  \n",
       "50%     49.700000     79.000000   91.200000          0.000000      4.000000  \n",
       "75%     58.000000    113.000000  131.200000          2.000000      4.500000  \n",
       "max    149.100000   3937.000000  377.300000         14.000000     12.000000  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1144e08c",
   "metadata": {},
   "source": [
    "### STEP 2: DATA PREPARATION ###\n",
    "\n",
    "- Dropping irrelevant columns and rows\n",
    "- Idetifying duplicated columns\n",
    "- Renaming columns\n",
    "- Feature creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4ec95999",
   "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>coaster_name</th>\n",
       "      <th>Length</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Location</th>\n",
       "      <th>Status</th>\n",
       "      <th>Opening date</th>\n",
       "      <th>Type</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Height restriction</th>\n",
       "      <th>Model</th>\n",
       "      <th>Height</th>\n",
       "      <th>Inversions</th>\n",
       "      <th>Lift/launch system</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Trains</th>\n",
       "      <th>Park section</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Capacity</th>\n",
       "      <th>G-force</th>\n",
       "      <th>Designer</th>\n",
       "      <th>Max vertical angle</th>\n",
       "      <th>Drop</th>\n",
       "      <th>Soft opening date</th>\n",
       "      <th>Fast Lane available</th>\n",
       "      <th>Replaced</th>\n",
       "      <th>Track layout</th>\n",
       "      <th>Fastrack available</th>\n",
       "      <th>Soft opening date.1</th>\n",
       "      <th>Closing date</th>\n",
       "      <th>Opened</th>\n",
       "      <th>Replaced by</th>\n",
       "      <th>Website</th>\n",
       "      <th>Flash Pass Available</th>\n",
       "      <th>Must transfer from wheelchair</th>\n",
       "      <th>Theme</th>\n",
       "      <th>Single rider line available</th>\n",
       "      <th>Restraint Style</th>\n",
       "      <th>Flash Pass available</th>\n",
       "      <th>Acceleration</th>\n",
       "      <th>Restraints</th>\n",
       "      <th>Name</th>\n",
       "      <th>year_introduced</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Type_Main</th>\n",
       "      <th>opening_date_clean</th>\n",
       "      <th>speed1</th>\n",
       "      <th>speed2</th>\n",
       "      <th>speed1_value</th>\n",
       "      <th>speed1_unit</th>\n",
       "      <th>speed_mph</th>\n",
       "      <th>height_value</th>\n",
       "      <th>height_unit</th>\n",
       "      <th>height_ft</th>\n",
       "      <th>Inversions_clean</th>\n",
       "      <th>Gforce_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switchback Railway</td>\n",
       "      <td>600 ft (180 m)</td>\n",
       "      <td>6 mph (9.7 km/h)</td>\n",
       "      <td>Coney Island</td>\n",
       "      <td>Removed</td>\n",
       "      <td>June 16, 1884</td>\n",
       "      <td>Wood</td>\n",
       "      <td>LaMarcus Adna Thompson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lift Packed</td>\n",
       "      <td>50 ft (15 m)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gravity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Coney Island Cyclone Site</td>\n",
       "      <td>1:00</td>\n",
       "      <td>1600 riders per hour</td>\n",
       "      <td>2.9</td>\n",
       "      <td>LaMarcus Adna Thompson</td>\n",
       "      <td>30°</td>\n",
       "      <td>43 ft (13 m)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gravity pulled coaster</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1884</td>\n",
       "      <td>40.5740</td>\n",
       "      <td>-73.9780</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1884-06-16</td>\n",
       "      <td>6 mph</td>\n",
       "      <td>9.7 km/h</td>\n",
       "      <td>6.0</td>\n",
       "      <td>mph</td>\n",
       "      <td>6.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>ft</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Flip Flap Railway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sea Lion Park</td>\n",
       "      <td>Removed</td>\n",
       "      <td>1895</td>\n",
       "      <td>Wood</td>\n",
       "      <td>Lina Beecher</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a single car. Riders are arranged 1 across in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>Lina Beecher</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1902</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>40.5780</td>\n",
       "      <td>-73.9790</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1895-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Switchback Railway (Euclid Beach Park)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cleveland, Ohio, United States</td>\n",
       "      <td>Closed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1896</td>\n",
       "      <td>41.5800</td>\n",
       "      <td>-81.5700</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Loop the Loop (Coney Island)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>Removed</td>\n",
       "      <td>1901</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Edwin Prescott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a single car. Riders are arranged 2 across in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Edward A. Green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Switchback Railway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1910</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Giant Racer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1901</td>\n",
       "      <td>40.5745</td>\n",
       "      <td>-73.9780</td>\n",
       "      <td>Steel</td>\n",
       "      <td>1901-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Loop the Loop (Young's Pier)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>Removed</td>\n",
       "      <td>1901</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Edwin Prescott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Edward A. Green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1912</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1901</td>\n",
       "      <td>39.3538</td>\n",
       "      <td>-74.4342</td>\n",
       "      <td>Steel</td>\n",
       "      <td>1901-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             coaster_name          Length             Speed  \\\n",
       "0                      Switchback Railway  600 ft (180 m)  6 mph (9.7 km/h)   \n",
       "1                       Flip Flap Railway             NaN               NaN   \n",
       "2  Switchback Railway (Euclid Beach Park)             NaN               NaN   \n",
       "3            Loop the Loop (Coney Island)             NaN               NaN   \n",
       "4            Loop the Loop (Young's Pier)             NaN               NaN   \n",
       "\n",
       "                         Location   Status   Opening date   Type  \\\n",
       "0                    Coney Island  Removed  June 16, 1884   Wood   \n",
       "1                   Sea Lion Park  Removed           1895   Wood   \n",
       "2  Cleveland, Ohio, United States   Closed            NaN  Other   \n",
       "3                           Other  Removed           1901  Steel   \n",
       "4                           Other  Removed           1901  Steel   \n",
       "\n",
       "             Manufacturer Height restriction        Model        Height  \\\n",
       "0  LaMarcus Adna Thompson                NaN  Lift Packed  50 ft (15 m)   \n",
       "1            Lina Beecher                NaN          NaN           NaN   \n",
       "2                     NaN                NaN          NaN           NaN   \n",
       "3          Edwin Prescott                NaN          NaN           NaN   \n",
       "4          Edwin Prescott                NaN          NaN           NaN   \n",
       "\n",
       "   Inversions Lift/launch system Cost  \\\n",
       "0         NaN            gravity  NaN   \n",
       "1         1.0                NaN  NaN   \n",
       "2         NaN                NaN  NaN   \n",
       "3         1.0                NaN  NaN   \n",
       "4         1.0                NaN  NaN   \n",
       "\n",
       "                                              Trains  \\\n",
       "0                                                NaN   \n",
       "1  a single car. Riders are arranged 1 across in ...   \n",
       "2                                                NaN   \n",
       "3  a single car. Riders are arranged 2 across in ...   \n",
       "4                                                NaN   \n",
       "\n",
       "                Park section Duration              Capacity G-force  \\\n",
       "0  Coney Island Cyclone Site     1:00  1600 riders per hour     2.9   \n",
       "1                        NaN      NaN                   NaN      12   \n",
       "2                        NaN      NaN                   NaN     NaN   \n",
       "3                        NaN      NaN                   NaN     NaN   \n",
       "4                        NaN      NaN                   NaN     NaN   \n",
       "\n",
       "                 Designer Max vertical angle          Drop Soft opening date  \\\n",
       "0  LaMarcus Adna Thompson                30°  43 ft (13 m)               NaN   \n",
       "1            Lina Beecher                NaN           NaN               NaN   \n",
       "2                     NaN                NaN           NaN               NaN   \n",
       "3         Edward A. Green                NaN           NaN               NaN   \n",
       "4         Edward A. Green                NaN           NaN               NaN   \n",
       "\n",
       "  Fast Lane available            Replaced            Track layout  \\\n",
       "0                 NaN                 NaN  Gravity pulled coaster   \n",
       "1                 NaN                 NaN                     NaN   \n",
       "2                 NaN                 NaN                     NaN   \n",
       "3                 NaN  Switchback Railway                     NaN   \n",
       "4                 NaN                 NaN                     NaN   \n",
       "\n",
       "  Fastrack available Soft opening date.1 Closing date Opened  Replaced by  \\\n",
       "0                NaN                 NaN          NaN    NaN          NaN   \n",
       "1                NaN                 NaN         1902    NaN          NaN   \n",
       "2                NaN                 NaN          NaN   1895          NaN   \n",
       "3                NaN                 NaN         1910    NaN  Giant Racer   \n",
       "4                NaN                 NaN         1912    NaN          NaN   \n",
       "\n",
       "  Website Flash Pass Available Must transfer from wheelchair Theme  \\\n",
       "0     NaN                  NaN                           NaN   NaN   \n",
       "1     NaN                  NaN                           NaN   NaN   \n",
       "2     NaN                  NaN                           NaN   NaN   \n",
       "3     NaN                  NaN                           NaN   NaN   \n",
       "4     NaN                  NaN                           NaN   NaN   \n",
       "\n",
       "  Single rider line available Restraint Style Flash Pass available  \\\n",
       "0                         NaN             NaN                  NaN   \n",
       "1                         NaN             NaN                  NaN   \n",
       "2                         NaN             NaN                  NaN   \n",
       "3                         NaN             NaN                  NaN   \n",
       "4                         NaN             NaN                  NaN   \n",
       "\n",
       "  Acceleration Restraints Name  year_introduced  latitude  longitude  \\\n",
       "0          NaN        NaN  NaN             1884   40.5740   -73.9780   \n",
       "1          NaN        NaN  NaN             1895   40.5780   -73.9790   \n",
       "2          NaN        NaN  NaN             1896   41.5800   -81.5700   \n",
       "3          NaN        NaN  NaN             1901   40.5745   -73.9780   \n",
       "4          NaN        NaN  NaN             1901   39.3538   -74.4342   \n",
       "\n",
       "  Type_Main opening_date_clean  speed1    speed2  speed1_value speed1_unit  \\\n",
       "0      Wood         1884-06-16  6 mph   9.7 km/h           6.0         mph   \n",
       "1      Wood         1895-01-01     NaN       NaN           NaN         NaN   \n",
       "2     Other                NaN     NaN       NaN           NaN         NaN   \n",
       "3     Steel         1901-01-01     NaN       NaN           NaN         NaN   \n",
       "4     Steel         1901-01-01     NaN       NaN           NaN         NaN   \n",
       "\n",
       "   speed_mph  height_value height_unit  height_ft  Inversions_clean  \\\n",
       "0        6.0          50.0          ft        NaN                 0   \n",
       "1        NaN           NaN         NaN        NaN                 1   \n",
       "2        NaN           NaN         NaN        NaN                 0   \n",
       "3        NaN           NaN         NaN        NaN                 1   \n",
       "4        NaN           NaN         NaN        NaN                 1   \n",
       "\n",
       "   Gforce_clean  \n",
       "0           2.9  \n",
       "1          12.0  \n",
       "2           NaN  \n",
       "3           NaN  \n",
       "4           NaN  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "39c62ed2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['coaster_name', 'Length', 'Speed', 'Location', 'Status', 'Opening date',\n",
       "       'Type', 'Manufacturer', 'Height restriction', 'Model', 'Height',\n",
       "       'Inversions', 'Lift/launch system', 'Cost', 'Trains', 'Park section',\n",
       "       'Duration', 'Capacity', 'G-force', 'Designer', 'Max vertical angle',\n",
       "       'Drop', 'Soft opening date', 'Fast Lane available', 'Replaced',\n",
       "       'Track layout', 'Fastrack available', 'Soft opening date.1',\n",
       "       'Closing date', 'Opened', 'Replaced by', 'Website',\n",
       "       'Flash Pass Available', 'Must transfer from wheelchair', 'Theme',\n",
       "       'Single rider line available', 'Restraint Style',\n",
       "       'Flash Pass available', 'Acceleration', 'Restraints', 'Name',\n",
       "       'year_introduced', 'latitude', 'longitude', 'Type_Main',\n",
       "       'opening_date_clean', 'speed1', 'speed2', 'speed1_value', 'speed1_unit',\n",
       "       'speed_mph', 'height_value', 'height_unit', 'height_ft',\n",
       "       'Inversions_clean', 'Gforce_clean'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e83ebcc",
   "metadata": {},
   "source": [
    "Copy data into df to visualize all column again, goal is to extract a subset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "801e2422",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[['coaster_name', \n",
    "    #'Length', 'Speed', 'Location', 'Status', 'Opening date',\n",
    "    #'Type',\n",
    "    'Manufacturer', \n",
    "    #'Height restriction', 'Model', 'Height',\n",
    "      # 'Inversions', 'Lift/launch system', 'Cost', 'Trains', 'Park section',\n",
    "      # 'Duration', 'Capacity', 'G-force', 'Designer', 'Max vertical angle',\n",
    "      # 'Drop', 'Soft opening date', 'Fast Lane available', 'Replaced',\n",
    "     #  'Track layout', 'Fastrack available', 'Soft opening date.1',\n",
    "      # 'Closing date', \n",
    "    'Opened', \n",
    "    #'Replaced by', 'Website',\n",
    "     #  'Flash Pass Available', 'Must transfer from wheelchair', 'Theme',\n",
    "      # 'Single rider line available', 'Restraint Style',\n",
    "      # 'Flash Pass available', 'Acceleration', 'Restraints', 'Name',\n",
    "       'year_introduced', 'latitude', 'longitude', 'Type_Main',\n",
    "       'opening_date_clean', \n",
    "    #'speed1', 'speed2', 'speed1_value', 'speed1_unit',\n",
    "       'speed_mph', \n",
    "    #'height_value', 'height_unit', \n",
    "    'height_ft',\n",
    "       'Inversions_clean', 'Gforce_clean']].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e32030b3",
   "metadata": {},
   "source": [
    "Or we can use _drop_ command"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "56a74cf9",
   "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>coaster_name</th>\n",
       "      <th>Length</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Location</th>\n",
       "      <th>Status</th>\n",
       "      <th>Type</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Height restriction</th>\n",
       "      <th>Model</th>\n",
       "      <th>Height</th>\n",
       "      <th>Inversions</th>\n",
       "      <th>Lift/launch system</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Trains</th>\n",
       "      <th>Park section</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Capacity</th>\n",
       "      <th>G-force</th>\n",
       "      <th>Designer</th>\n",
       "      <th>Max vertical angle</th>\n",
       "      <th>Drop</th>\n",
       "      <th>Soft opening date</th>\n",
       "      <th>Fast Lane available</th>\n",
       "      <th>Replaced</th>\n",
       "      <th>Track layout</th>\n",
       "      <th>Fastrack available</th>\n",
       "      <th>Soft opening date.1</th>\n",
       "      <th>Closing date</th>\n",
       "      <th>Opened</th>\n",
       "      <th>Replaced by</th>\n",
       "      <th>Website</th>\n",
       "      <th>Flash Pass Available</th>\n",
       "      <th>Must transfer from wheelchair</th>\n",
       "      <th>Theme</th>\n",
       "      <th>Single rider line available</th>\n",
       "      <th>Restraint Style</th>\n",
       "      <th>Flash Pass available</th>\n",
       "      <th>Acceleration</th>\n",
       "      <th>Restraints</th>\n",
       "      <th>Name</th>\n",
       "      <th>year_introduced</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Type_Main</th>\n",
       "      <th>opening_date_clean</th>\n",
       "      <th>speed1</th>\n",
       "      <th>speed2</th>\n",
       "      <th>speed1_value</th>\n",
       "      <th>speed1_unit</th>\n",
       "      <th>speed_mph</th>\n",
       "      <th>height_value</th>\n",
       "      <th>height_unit</th>\n",
       "      <th>height_ft</th>\n",
       "      <th>Inversions_clean</th>\n",
       "      <th>Gforce_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switchback Railway</td>\n",
       "      <td>600 ft (180 m)</td>\n",
       "      <td>6 mph (9.7 km/h)</td>\n",
       "      <td>Coney Island</td>\n",
       "      <td>Removed</td>\n",
       "      <td>Wood</td>\n",
       "      <td>LaMarcus Adna Thompson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lift Packed</td>\n",
       "      <td>50 ft (15 m)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gravity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Coney Island Cyclone Site</td>\n",
       "      <td>1:00</td>\n",
       "      <td>1600 riders per hour</td>\n",
       "      <td>2.9</td>\n",
       "      <td>LaMarcus Adna Thompson</td>\n",
       "      <td>30°</td>\n",
       "      <td>43 ft (13 m)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gravity pulled coaster</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1884</td>\n",
       "      <td>40.5740</td>\n",
       "      <td>-73.9780</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1884-06-16</td>\n",
       "      <td>6 mph</td>\n",
       "      <td>9.7 km/h</td>\n",
       "      <td>6.0</td>\n",
       "      <td>mph</td>\n",
       "      <td>6.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>ft</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Flip Flap Railway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sea Lion Park</td>\n",
       "      <td>Removed</td>\n",
       "      <td>Wood</td>\n",
       "      <td>Lina Beecher</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a single car. Riders are arranged 1 across in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>Lina Beecher</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1902</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>40.5780</td>\n",
       "      <td>-73.9790</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1895-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Switchback Railway (Euclid Beach Park)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cleveland, Ohio, United States</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1896</td>\n",
       "      <td>41.5800</td>\n",
       "      <td>-81.5700</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Loop the Loop (Coney Island)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>Removed</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Edwin Prescott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a single car. Riders are arranged 2 across in ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Edward A. Green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Switchback Railway</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1910</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Giant Racer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1901</td>\n",
       "      <td>40.5745</td>\n",
       "      <td>-73.9780</td>\n",
       "      <td>Steel</td>\n",
       "      <td>1901-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Loop the Loop (Young's Pier)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>Removed</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Edwin Prescott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Edward A. Green</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1912</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1901</td>\n",
       "      <td>39.3538</td>\n",
       "      <td>-74.4342</td>\n",
       "      <td>Steel</td>\n",
       "      <td>1901-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</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",
       "      <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",
       "      <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",
       "      <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",
       "      <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>1082</th>\n",
       "      <td>American Dreier Looping</td>\n",
       "      <td>3,444 ft (1,050 m)</td>\n",
       "      <td>53 mph (85 km/h)</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Steel</td>\n",
       "      <td>Anton Schwarzkopf</td>\n",
       "      <td>55 in (140 cm)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111 ft (34 m)</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Booster Wheel Lift Hill</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3 trains with 5 cars. Riders are arranged 2 ac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,500 riders per hour</td>\n",
       "      <td>4.7</td>\n",
       "      <td>Werner Stengel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Steel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53 mph</td>\n",
       "      <td>85 km/h</td>\n",
       "      <td>53.0</td>\n",
       "      <td>mph</td>\n",
       "      <td>53.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>ft</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>Pantheon (roller coaster)</td>\n",
       "      <td>3,328 ft (1,014 m)</td>\n",
       "      <td>73 mph (117 km/h)</td>\n",
       "      <td>Busch Gardens Williamsburg</td>\n",
       "      <td>Under construction</td>\n",
       "      <td>Steel – Launched</td>\n",
       "      <td>Intamin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Blitz Coaster</td>\n",
       "      <td>178 ft (54 m)</td>\n",
       "      <td>2.0</td>\n",
       "      <td>LSM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 trains with 5 cars. Riders are arranged 2 ac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95°</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022</td>\n",
       "      <td>37.2339</td>\n",
       "      <td>-76.6426</td>\n",
       "      <td>Steel</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>73 mph</td>\n",
       "      <td>117 km/h</td>\n",
       "      <td>73.0</td>\n",
       "      <td>mph</td>\n",
       "      <td>73.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>ft</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1084</th>\n",
       "      <td>Tron Lightcycle Power Run</td>\n",
       "      <td>3,169.3 ft (966.0 m)</td>\n",
       "      <td>59.3[1] mph (95.4 km/h)</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Steel – Launched</td>\n",
       "      <td>Vekoma</td>\n",
       "      <td>4[2] ft (122 cm)</td>\n",
       "      <td>Motorbike roller coaster</td>\n",
       "      <td>78.1 ft (23.8 m)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>LIM Launch</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7 trains with 7 cars. Riders are arranged 2 ac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>~2:00</td>\n",
       "      <td>1,680 riders per hour</td>\n",
       "      <td>4</td>\n",
       "      <td>Walt Disney Imagineering</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Must transfer from wheelchair</td>\n",
       "      <td>Tron</td>\n",
       "      <td>Single rider line available</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TRON Lightcycle / Run</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Steel</td>\n",
       "      <td>2016-06-16</td>\n",
       "      <td>59.3 mph</td>\n",
       "      <td>95.4 km/h</td>\n",
       "      <td>59.3</td>\n",
       "      <td>mph</td>\n",
       "      <td>59.3</td>\n",
       "      <td>78.1</td>\n",
       "      <td>ft</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>Tumbili</td>\n",
       "      <td>770 ft (230 m)</td>\n",
       "      <td>34 mph (55 km/h)</td>\n",
       "      <td>Kings Dominion</td>\n",
       "      <td>Under construction</td>\n",
       "      <td>Steel – 4th Dimension – Wing Coaster</td>\n",
       "      <td>S&amp;S – Sansei Technologies</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4D Free Spin</td>\n",
       "      <td>112 ft (34 m)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Vertical chain lift hill</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single car trains with riders arranged 4 acros...</td>\n",
       "      <td>Jungle X-Pedition</td>\n",
       "      <td>0:55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Crypt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Official website</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Steel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34 mph</td>\n",
       "      <td>55 km/h</td>\n",
       "      <td>34.0</td>\n",
       "      <td>mph</td>\n",
       "      <td>34.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>ft</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1086</th>\n",
       "      <td>Wonder Woman Flight of Courage</td>\n",
       "      <td>3,300 ft (1,000 m)</td>\n",
       "      <td>58 mph (93 km/h)</td>\n",
       "      <td>Six Flags Magic Mountain</td>\n",
       "      <td>Under construction</td>\n",
       "      <td>Steel – Single-rail</td>\n",
       "      <td>Rocky Mountain Construction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raptor – Custom</td>\n",
       "      <td>131 ft (40 m)</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Chain lift hill</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DC Universe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87°</td>\n",
       "      <td>127 ft (39 m)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Green Lantern: First Flight Tidal Wave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Steel</td>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>58 mph</td>\n",
       "      <td>93 km/h</td>\n",
       "      <td>58.0</td>\n",
       "      <td>mph</td>\n",
       "      <td>58.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>ft</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1087 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                coaster_name                Length  \\\n",
       "0                         Switchback Railway        600 ft (180 m)   \n",
       "1                          Flip Flap Railway                   NaN   \n",
       "2     Switchback Railway (Euclid Beach Park)                   NaN   \n",
       "3               Loop the Loop (Coney Island)                   NaN   \n",
       "4               Loop the Loop (Young's Pier)                   NaN   \n",
       "...                                      ...                   ...   \n",
       "1082                 American Dreier Looping    3,444 ft (1,050 m)   \n",
       "1083               Pantheon (roller coaster)    3,328 ft (1,014 m)   \n",
       "1084               Tron Lightcycle Power Run  3,169.3 ft (966.0 m)   \n",
       "1085                                 Tumbili        770 ft (230 m)   \n",
       "1086          Wonder Woman Flight of Courage    3,300 ft (1,000 m)   \n",
       "\n",
       "                        Speed                        Location  \\\n",
       "0            6 mph (9.7 km/h)                    Coney Island   \n",
       "1                         NaN                   Sea Lion Park   \n",
       "2                         NaN  Cleveland, Ohio, United States   \n",
       "3                         NaN                           Other   \n",
       "4                         NaN                           Other   \n",
       "...                       ...                             ...   \n",
       "1082         53 mph (85 km/h)                           Other   \n",
       "1083        73 mph (117 km/h)      Busch Gardens Williamsburg   \n",
       "1084  59.3[1] mph (95.4 km/h)                           Other   \n",
       "1085         34 mph (55 km/h)                  Kings Dominion   \n",
       "1086         58 mph (93 km/h)        Six Flags Magic Mountain   \n",
       "\n",
       "                  Status                                  Type  \\\n",
       "0                Removed                                  Wood   \n",
       "1                Removed                                  Wood   \n",
       "2                 Closed                                 Other   \n",
       "3                Removed                                 Steel   \n",
       "4                Removed                                 Steel   \n",
       "...                  ...                                   ...   \n",
       "1082                 NaN                                 Steel   \n",
       "1083  Under construction                      Steel – Launched   \n",
       "1084                 NaN                      Steel – Launched   \n",
       "1085  Under construction  Steel – 4th Dimension – Wing Coaster   \n",
       "1086  Under construction                   Steel – Single-rail   \n",
       "\n",
       "                     Manufacturer Height restriction  \\\n",
       "0          LaMarcus Adna Thompson                NaN   \n",
       "1                    Lina Beecher                NaN   \n",
       "2                             NaN                NaN   \n",
       "3                  Edwin Prescott                NaN   \n",
       "4                  Edwin Prescott                NaN   \n",
       "...                           ...                ...   \n",
       "1082            Anton Schwarzkopf     55 in (140 cm)   \n",
       "1083                      Intamin                NaN   \n",
       "1084                       Vekoma   4[2] ft (122 cm)   \n",
       "1085    S&S – Sansei Technologies                NaN   \n",
       "1086  Rocky Mountain Construction                NaN   \n",
       "\n",
       "                         Model            Height  Inversions  \\\n",
       "0                  Lift Packed      50 ft (15 m)         NaN   \n",
       "1                          NaN               NaN         1.0   \n",
       "2                          NaN               NaN         NaN   \n",
       "3                          NaN               NaN         1.0   \n",
       "4                          NaN               NaN         1.0   \n",
       "...                        ...               ...         ...   \n",
       "1082                       NaN     111 ft (34 m)         3.0   \n",
       "1083             Blitz Coaster     178 ft (54 m)         2.0   \n",
       "1084  Motorbike roller coaster  78.1 ft (23.8 m)         0.0   \n",
       "1085              4D Free Spin     112 ft (34 m)         0.0   \n",
       "1086           Raptor – Custom     131 ft (40 m)         3.0   \n",
       "\n",
       "            Lift/launch system Cost  \\\n",
       "0                      gravity  NaN   \n",
       "1                          NaN  NaN   \n",
       "2                          NaN  NaN   \n",
       "3                          NaN  NaN   \n",
       "4                          NaN  NaN   \n",
       "...                        ...  ...   \n",
       "1082   Booster Wheel Lift Hill  NaN   \n",
       "1083                       LSM  NaN   \n",
       "1084                LIM Launch  NaN   \n",
       "1085  Vertical chain lift hill  NaN   \n",
       "1086           Chain lift hill  NaN   \n",
       "\n",
       "                                                 Trains  \\\n",
       "0                                                   NaN   \n",
       "1     a single car. Riders are arranged 1 across in ...   \n",
       "2                                                   NaN   \n",
       "3     a single car. Riders are arranged 2 across in ...   \n",
       "4                                                   NaN   \n",
       "...                                                 ...   \n",
       "1082  3 trains with 5 cars. Riders are arranged 2 ac...   \n",
       "1083  2 trains with 5 cars. Riders are arranged 2 ac...   \n",
       "1084  7 trains with 7 cars. Riders are arranged 2 ac...   \n",
       "1085  Single car trains with riders arranged 4 acros...   \n",
       "1086                                                NaN   \n",
       "\n",
       "                   Park section Duration               Capacity G-force  \\\n",
       "0     Coney Island Cyclone Site     1:00   1600 riders per hour     2.9   \n",
       "1                           NaN      NaN                    NaN      12   \n",
       "2                           NaN      NaN                    NaN     NaN   \n",
       "3                           NaN      NaN                    NaN     NaN   \n",
       "4                           NaN      NaN                    NaN     NaN   \n",
       "...                         ...      ...                    ...     ...   \n",
       "1082                        NaN      NaN  1,500 riders per hour     4.7   \n",
       "1083                        NaN      NaN                    NaN     NaN   \n",
       "1084                        NaN    ~2:00  1,680 riders per hour       4   \n",
       "1085          Jungle X-Pedition     0:55                    NaN     NaN   \n",
       "1086                DC Universe      NaN                    NaN     NaN   \n",
       "\n",
       "                      Designer Max vertical angle           Drop  \\\n",
       "0       LaMarcus Adna Thompson                30°   43 ft (13 m)   \n",
       "1                 Lina Beecher                NaN            NaN   \n",
       "2                          NaN                NaN            NaN   \n",
       "3              Edward A. Green                NaN            NaN   \n",
       "4              Edward A. Green                NaN            NaN   \n",
       "...                        ...                ...            ...   \n",
       "1082            Werner Stengel                NaN            NaN   \n",
       "1083                       NaN                95°            NaN   \n",
       "1084  Walt Disney Imagineering                NaN            NaN   \n",
       "1085                       NaN                NaN            NaN   \n",
       "1086                       NaN                87°  127 ft (39 m)   \n",
       "\n",
       "     Soft opening date Fast Lane available  \\\n",
       "0                  NaN                 NaN   \n",
       "1                  NaN                 NaN   \n",
       "2                  NaN                 NaN   \n",
       "3                  NaN                 NaN   \n",
       "4                  NaN                 NaN   \n",
       "...                ...                 ...   \n",
       "1082               NaN                 NaN   \n",
       "1083               NaN                 NaN   \n",
       "1084               NaN                 NaN   \n",
       "1085               NaN                 NaN   \n",
       "1086               NaN                 NaN   \n",
       "\n",
       "                                    Replaced            Track layout  \\\n",
       "0                                        NaN  Gravity pulled coaster   \n",
       "1                                        NaN                     NaN   \n",
       "2                                        NaN                     NaN   \n",
       "3                         Switchback Railway                     NaN   \n",
       "4                                        NaN                     NaN   \n",
       "...                                      ...                     ...   \n",
       "1082                                     NaN                     NaN   \n",
       "1083                                     NaN                     NaN   \n",
       "1084                                     NaN                     NaN   \n",
       "1085                               The Crypt                     NaN   \n",
       "1086  Green Lantern: First Flight Tidal Wave                     NaN   \n",
       "\n",
       "     Fastrack available Soft opening date.1 Closing date Opened  Replaced by  \\\n",
       "0                   NaN                 NaN          NaN    NaN          NaN   \n",
       "1                   NaN                 NaN         1902    NaN          NaN   \n",
       "2                   NaN                 NaN          NaN   1895          NaN   \n",
       "3                   NaN                 NaN         1910    NaN  Giant Racer   \n",
       "4                   NaN                 NaN         1912    NaN          NaN   \n",
       "...                 ...                 ...          ...    ...          ...   \n",
       "1082                NaN                 NaN          NaN    NaN          NaN   \n",
       "1083                NaN                 NaN          NaN    NaN          NaN   \n",
       "1084                NaN                 NaN          NaN    NaN          NaN   \n",
       "1085                NaN                 NaN          NaN    NaN          NaN   \n",
       "1086                NaN                 NaN          NaN    NaN          NaN   \n",
       "\n",
       "               Website Flash Pass Available  Must transfer from wheelchair  \\\n",
       "0                  NaN                  NaN                            NaN   \n",
       "1                  NaN                  NaN                            NaN   \n",
       "2                  NaN                  NaN                            NaN   \n",
       "3                  NaN                  NaN                            NaN   \n",
       "4                  NaN                  NaN                            NaN   \n",
       "...                ...                  ...                            ...   \n",
       "1082               NaN                  NaN                            NaN   \n",
       "1083               NaN                  NaN                            NaN   \n",
       "1084               NaN                  NaN  Must transfer from wheelchair   \n",
       "1085  Official website                  NaN                            NaN   \n",
       "1086               NaN                  NaN                            NaN   \n",
       "\n",
       "     Theme  Single rider line available Restraint Style Flash Pass available  \\\n",
       "0      NaN                          NaN             NaN                  NaN   \n",
       "1      NaN                          NaN             NaN                  NaN   \n",
       "2      NaN                          NaN             NaN                  NaN   \n",
       "3      NaN                          NaN             NaN                  NaN   \n",
       "4      NaN                          NaN             NaN                  NaN   \n",
       "...    ...                          ...             ...                  ...   \n",
       "1082   NaN                          NaN             NaN                  NaN   \n",
       "1083   NaN                          NaN             NaN                  NaN   \n",
       "1084  Tron  Single rider line available             NaN                  NaN   \n",
       "1085   NaN                          NaN             NaN                  NaN   \n",
       "1086   NaN                          NaN             NaN                  NaN   \n",
       "\n",
       "     Acceleration Restraints                   Name  year_introduced  \\\n",
       "0             NaN        NaN                    NaN             1884   \n",
       "1             NaN        NaN                    NaN             1895   \n",
       "2             NaN        NaN                    NaN             1896   \n",
       "3             NaN        NaN                    NaN             1901   \n",
       "4             NaN        NaN                    NaN             1901   \n",
       "...           ...        ...                    ...              ...   \n",
       "1082          NaN        NaN                    NaN             2022   \n",
       "1083          NaN        NaN                    NaN             2022   \n",
       "1084          NaN        NaN  TRON Lightcycle / Run             2022   \n",
       "1085          NaN        NaN                    NaN             2022   \n",
       "1086          NaN        NaN                    NaN             2022   \n",
       "\n",
       "      latitude  longitude Type_Main opening_date_clean     speed1     speed2  \\\n",
       "0      40.5740   -73.9780      Wood         1884-06-16     6 mph    9.7 km/h   \n",
       "1      40.5780   -73.9790      Wood         1895-01-01        NaN        NaN   \n",
       "2      41.5800   -81.5700     Other                NaN        NaN        NaN   \n",
       "3      40.5745   -73.9780     Steel         1901-01-01        NaN        NaN   \n",
       "4      39.3538   -74.4342     Steel         1901-01-01        NaN        NaN   \n",
       "...        ...        ...       ...                ...        ...        ...   \n",
       "1082       NaN        NaN     Steel                NaN    53 mph     85 km/h   \n",
       "1083   37.2339   -76.6426     Steel         2022-01-01    73 mph    117 km/h   \n",
       "1084       NaN        NaN     Steel         2016-06-16  59.3 mph   95.4 km/h   \n",
       "1085       NaN        NaN     Steel                NaN    34 mph     55 km/h   \n",
       "1086       NaN        NaN     Steel         2022-01-01    58 mph     93 km/h   \n",
       "\n",
       "      speed1_value speed1_unit  speed_mph  height_value height_unit  \\\n",
       "0              6.0         mph        6.0          50.0          ft   \n",
       "1              NaN         NaN        NaN           NaN         NaN   \n",
       "2              NaN         NaN        NaN           NaN         NaN   \n",
       "3              NaN         NaN        NaN           NaN         NaN   \n",
       "4              NaN         NaN        NaN           NaN         NaN   \n",
       "...            ...         ...        ...           ...         ...   \n",
       "1082          53.0         mph       53.0         111.0          ft   \n",
       "1083          73.0         mph       73.0         178.0          ft   \n",
       "1084          59.3         mph       59.3          78.1          ft   \n",
       "1085          34.0         mph       34.0         112.0          ft   \n",
       "1086          58.0         mph       58.0         131.0          ft   \n",
       "\n",
       "      height_ft  Inversions_clean  Gforce_clean  \n",
       "0           NaN                 0           2.9  \n",
       "1           NaN                 1          12.0  \n",
       "2           NaN                 0           NaN  \n",
       "3           NaN                 1           NaN  \n",
       "4           NaN                 1           NaN  \n",
       "...         ...               ...           ...  \n",
       "1082        NaN                 3           4.7  \n",
       "1083        NaN                 2           NaN  \n",
       "1084        NaN                 0           4.0  \n",
       "1085        NaN                 0           NaN  \n",
       "1086        NaN                 3           NaN  \n",
       "\n",
       "[1087 rows x 55 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Example of dropping 1 columns\n",
    "df.drop(['Opening date'], axis = 1)    # axis = 0 drop row, axis = 1 drop column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "315ed011",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1087, 12)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "93193593",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "coaster_name           object\n",
       "Manufacturer           object\n",
       "Opened                 object\n",
       "year_introduced         int64\n",
       "latitude              float64\n",
       "longitude             float64\n",
       "Type_Main              object\n",
       "opening_date_clean     object\n",
       "speed_mph             float64\n",
       "height_ft             float64\n",
       "Inversions_clean        int64\n",
       "Gforce_clean          float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "061e20ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['coaster_name', 'Manufacturer', 'Opened', 'year_introduced', 'latitude',\n",
       "       'longitude', 'Type_Main', 'opening_date_clean', 'speed_mph',\n",
       "       'height_ft', 'Inversions_clean', 'Gforce_clean'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "06ba0f35",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['opening_date_clean'] = pd.to_datetime(df['opening_date_clean'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "f3da9850",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "coaster_name                  object\n",
       "Manufacturer                  object\n",
       "Opened                        object\n",
       "year_introduced                int64\n",
       "latitude                     float64\n",
       "longitude                    float64\n",
       "Type_Main                     object\n",
       "opening_date_clean    datetime64[ns]\n",
       "speed_mph                    float64\n",
       "height_ft                    float64\n",
       "Inversions_clean               int64\n",
       "Gforce_clean                 float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "f5db7237",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Coaster_Name', 'Manufacturer', 'Opened', 'Year_Introduced', 'latitude',\n",
       "       'longitude', 'Type_Main', 'Opening_Date', 'Speed_mph', 'Height_ft',\n",
       "       'Inversions', 'Gforce'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Rename our columns to make easier to manipulate ex. avoiding lower case or upper case\n",
    "df = df.rename(columns = {'coaster_name':'Coaster_Name',\n",
    "                    'year_introduced':'Year_Introduced',\n",
    "                    'opening_date_clean':'Opening_Date',\n",
    "                    'speed_mph':'Speed_mph',\n",
    "                    'height_ft':'Height_ft',\n",
    "                    'Inversions_clean':'Inversions',\n",
    "                    'Gforce_clean':'Gforce'})\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9be4376a",
   "metadata": {},
   "source": [
    "Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "9238fa4b",
   "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>Coaster_Name</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Opened</th>\n",
       "      <th>Year_Introduced</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Type_Main</th>\n",
       "      <th>Opening_Date</th>\n",
       "      <th>Speed_mph</th>\n",
       "      <th>Height_ft</th>\n",
       "      <th>Inversions</th>\n",
       "      <th>Gforce</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</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>1082</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1084</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1086</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1087 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Coaster_Name  Manufacturer  Opened  Year_Introduced  latitude  \\\n",
       "0            False         False    True            False     False   \n",
       "1            False         False    True            False     False   \n",
       "2            False          True   False            False     False   \n",
       "3            False         False    True            False     False   \n",
       "4            False         False    True            False     False   \n",
       "...            ...           ...     ...              ...       ...   \n",
       "1082         False         False    True            False      True   \n",
       "1083         False         False    True            False     False   \n",
       "1084         False         False    True            False      True   \n",
       "1085         False         False    True            False      True   \n",
       "1086         False         False    True            False      True   \n",
       "\n",
       "      longitude  Type_Main  Opening_Date  Speed_mph  Height_ft  Inversions  \\\n",
       "0         False      False         False      False       True       False   \n",
       "1         False      False         False       True       True       False   \n",
       "2         False      False          True       True       True       False   \n",
       "3         False      False         False       True       True       False   \n",
       "4         False      False         False       True       True       False   \n",
       "...         ...        ...           ...        ...        ...         ...   \n",
       "1082       True      False          True      False       True       False   \n",
       "1083      False      False         False      False       True       False   \n",
       "1084       True      False         False      False       True       False   \n",
       "1085       True      False          True      False       True       False   \n",
       "1086       True      False         False      False       True       False   \n",
       "\n",
       "      Gforce  \n",
       "0      False  \n",
       "1      False  \n",
       "2       True  \n",
       "3       True  \n",
       "4       True  \n",
       "...      ...  \n",
       "1082   False  \n",
       "1083    True  \n",
       "1084   False  \n",
       "1085    True  \n",
       "1086    True  \n",
       "\n",
       "[1087 rows x 12 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "94f95b1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Coaster_Name          0\n",
       "Manufacturer         59\n",
       "Opened             1060\n",
       "Year_Introduced       0\n",
       "latitude            275\n",
       "longitude           275\n",
       "Type_Main             0\n",
       "Opening_Date        250\n",
       "Speed_mph           150\n",
       "Height_ft           916\n",
       "Inversions            0\n",
       "Gforce              725\n",
       "dtype: int64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "908b691f",
   "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>Coaster_Name</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Opened</th>\n",
       "      <th>Year_Introduced</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Type_Main</th>\n",
       "      <th>Opening_Date</th>\n",
       "      <th>Speed_mph</th>\n",
       "      <th>Height_ft</th>\n",
       "      <th>Inversions</th>\n",
       "      <th>Gforce</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Coaster_Name, Manufacturer, Opened, Year_Introduced, latitude, longitude, Type_Main, Opening_Date, Speed_mph, Height_ft, Inversions, Gforce]\n",
       "Index: []"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "6a55cdad",
   "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>Coaster_Name</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Opened</th>\n",
       "      <th>Year_Introduced</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Type_Main</th>\n",
       "      <th>Opening_Date</th>\n",
       "      <th>Speed_mph</th>\n",
       "      <th>Height_ft</th>\n",
       "      <th>Inversions</th>\n",
       "      <th>Gforce</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Crystal Beach Cyclone</td>\n",
       "      <td>Traver Engineering</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1927</td>\n",
       "      <td>42.8617</td>\n",
       "      <td>-79.0598</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1926-01-01</td>\n",
       "      <td>60.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Derby Racer</td>\n",
       "      <td>Fred W. Pearce</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1937</td>\n",
       "      <td>42.4200</td>\n",
       "      <td>-70.9860</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1911-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Blue Streak (Conneaut Lake)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1938</td>\n",
       "      <td>41.6349</td>\n",
       "      <td>-80.3180</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1938-05-23</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>Big Thunder Mountain Railroad</td>\n",
       "      <td>Arrow Development (California and Florida)Dyna...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1980</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Steel</td>\n",
       "      <td>NaT</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>Thunder Run (Canada's Wonderland)</td>\n",
       "      <td>Mack Rides</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986</td>\n",
       "      <td>43.8427</td>\n",
       "      <td>-79.5423</td>\n",
       "      <td>Steel</td>\n",
       "      <td>1981-05-23</td>\n",
       "      <td>39.8</td>\n",
       "      <td>32.8</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Coaster_Name  \\\n",
       "43               Crystal Beach Cyclone   \n",
       "60                         Derby Racer   \n",
       "61         Blue Streak (Conneaut Lake)   \n",
       "167      Big Thunder Mountain Railroad   \n",
       "237  Thunder Run (Canada's Wonderland)   \n",
       "\n",
       "                                          Manufacturer Opened  \\\n",
       "43                                  Traver Engineering    NaN   \n",
       "60                                      Fred W. Pearce    NaN   \n",
       "61                                                 NaN    NaN   \n",
       "167  Arrow Development (California and Florida)Dyna...    NaN   \n",
       "237                                         Mack Rides    NaN   \n",
       "\n",
       "     Year_Introduced  latitude  longitude Type_Main Opening_Date  Speed_mph  \\\n",
       "43              1927   42.8617   -79.0598      Wood   1926-01-01       60.0   \n",
       "60              1937   42.4200   -70.9860      Wood   1911-01-01        NaN   \n",
       "61              1938   41.6349   -80.3180      Wood   1938-05-23       50.0   \n",
       "167             1980       NaN        NaN     Steel          NaT       35.0   \n",
       "237             1986   43.8427   -79.5423     Steel   1981-05-23       39.8   \n",
       "\n",
       "     Height_ft  Inversions  Gforce  \n",
       "43         NaN           0     4.0  \n",
       "60         NaN           0     NaN  \n",
       "61         NaN           0     NaN  \n",
       "167        NaN           0     NaN  \n",
       "237       32.8           0     NaN  "
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check for duplicate coaster name\n",
    "df.loc[df.duplicated(subset=['Coaster_Name'])].head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "8a4fb43a",
   "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>Coaster_Name</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Opened</th>\n",
       "      <th>Year_Introduced</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Type_Main</th>\n",
       "      <th>Opening_Date</th>\n",
       "      <th>Speed_mph</th>\n",
       "      <th>Height_ft</th>\n",
       "      <th>Inversions</th>\n",
       "      <th>Gforce</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Crystal Beach Cyclone</td>\n",
       "      <td>Traver Engineering</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1926</td>\n",
       "      <td>42.8617</td>\n",
       "      <td>-79.0598</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1926-01-01</td>\n",
       "      <td>60.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Crystal Beach Cyclone</td>\n",
       "      <td>Traver Engineering</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1927</td>\n",
       "      <td>42.8617</td>\n",
       "      <td>-79.0598</td>\n",
       "      <td>Wood</td>\n",
       "      <td>1926-01-01</td>\n",
       "      <td>60.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Coaster_Name        Manufacturer Opened  Year_Introduced  \\\n",
       "39  Crystal Beach Cyclone  Traver Engineering    NaN             1926   \n",
       "43  Crystal Beach Cyclone  Traver Engineering    NaN             1927   \n",
       "\n",
       "    latitude  longitude Type_Main Opening_Date  Speed_mph  Height_ft  \\\n",
       "39   42.8617   -79.0598      Wood   1926-01-01       60.0        NaN   \n",
       "43   42.8617   -79.0598      Wood   1926-01-01       60.0        NaN   \n",
       "\n",
       "    Inversions  Gforce  \n",
       "39           0     4.0  \n",
       "43           0     4.0  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking an example duplicate\n",
    "df.query('Coaster_Name == \"Crystal Beach Cyclone\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "ee48adb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Coaster_Name', 'Manufacturer', 'Opened', 'Year_Introduced', 'latitude',\n",
       "       'longitude', 'Type_Main', 'Opening_Date', 'Speed_mph', 'Height_ft',\n",
       "       'Inversions', 'Gforce'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9714380",
   "metadata": {},
   "source": [
    "### FEATURE UNDERSTANDING ###\n",
    "Univariate Analysis\n",
    "\n",
    "- Plotting Feature Distributions\n",
    " - Histogram\n",
    " - KDE\n",
    " - Boxplot\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "86e76fcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1999    49\n",
       "2000    47\n",
       "1998    32\n",
       "2011    31\n",
       "2001    30\n",
       "        ..\n",
       "1956     1\n",
       "1959     1\n",
       "1961     1\n",
       "1895     1\n",
       "1884     1\n",
       "Name: Year_Introduced, Length: 101, dtype: int64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Year_Introduced'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "d6f6fe45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df['Year_Introduced'].value_counts() \\\n",
    "    .head(10) \\\n",
    "    .plot(kind='bar', title='Top 10 Years Coasters Introduced')\n",
    "ax.set_xlabel('Year Introduced')\n",
    "ax.set_ylabel('Count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "c67e28fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Speed (mph)')"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df['Speed_mph'].plot(kind='hist',\n",
    "                          bins=20,\n",
    "                          title='Coaster Speed (mph)')\n",
    "ax.set_xlabel('Speed (mph)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "29bd03c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Speed (mph)')"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZEAAAEaCAYAAADQVmpMAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAA0MklEQVR4nO3deZxcVZnw8d/p7iydtZOubJ0d0iwJKBA2ZRkQQZgZiAs+gCgww8A4wqjD6LzqQERkZsBRkBeYcRBUYEbxEUHzjsgiiMoelrAkIZCEbN2dpbNvndBd5/3j3Eoqle50d3VV3Vqe7+dTn66699S9z+lanrrnnHuu895jjDHGZKMq7gCMMcaULksixhhjsmZJxBhjTNYsiRhjjMmaJRFjjDFZsyRijDEma5ZEjKkwzrnrnXOLe1DuWOdci3NucDHE5Jz7kHNuhXOuNt/xmJ6zJGLyzjlX75z7jnNukXOuzTm31jn3R+fcJc65mgLGcbdz7uk876PKOfcV59xbzrntzrlNzrnXnXM35nO/eXIr8B3v/fa4AwHw3j8PvAX8Y9yxmL0K9gE2lck5NxF4BmgHZgOvAe8DHwa+ArwBzIsrvmw55/p773d3smo28CXg74HngYHAEcCJBQyvz5xzxwHHAefFHUuGu4E7nXM3e+/fjzsYA3jv7Wa3vN2A/wesBoZ3sq4fMDjt/k1AE7AbWAB8JqP8lwgJZ1u0zQeAcRnbuwVYBewCWoAHonXXAz7jdlm0bghwW7TvHYRE98m07U6Jyl8MPAJsB27uor7zgO928z+5HlgMfAZYCrQBTwBTMsqdCTwL7Ixi+zFQn1HmwmifbcCyqP6D09YPBP4T2AxsjO7/G7C4mxi/Dzyesewywo+B04E3o7ieBhqAU6P/23bgd8D43tQ3rcws4O1oO08DjRkxDIxe27Pjfm/bLXpN4g7AbuV7A0YCHcC1PSj778B64NPAIcA3gCRwRlqZLwEfBaYCHwKeA/6Qtv6aKIGcBkwi/JL+crRuCPA/0XPGRrdawAG/j76wTgYOAq4kJLIzoudOISSRVYREMhWY2kU9fgvMTf8S7aTM9dGX5DPAsVGcLwKvAi4q8xFCQvt7oDEq83vgD2llLosSw+eiuE8lHNndn7avW4G10ZfzYcB3gS10n0ReA27MWHZZ9Jo8DZwAHAO8C/wpWnYicFSUBH7ey/qmyjwKzAQ+CLwC/KmT2F6iiyRutxg+53EHYLfyvQHHR1++n+ym3CDCr8svZCx/GHjqAM87Otr++OjxbcBTqS+mTsrfDTydsew0wi/j4RnLfwT8KrqfSiLX9aDOhxHa7ZPAIuDeKPHUpJW5PtretLRlh0TLUonraeCmjG1PisocFT1eBnw+o8ypUZkRwOCobldklHm5B0lkE/B3GcsuS99/tOyr0bKZacv+AWjtZX2vJxzljEorc0H0fxyYEcdDwC/ifn/bLdysY93kk+thuWlAf+CPGcv/AMzYszHnTnPOPeacW+mc20r4ZQswOfr7Y+BIYLFz7gfOuU855/p3s+/jon03Oee2pW7AZwlHAOle6q4i3vu3oxhmAndE274beCFjVNE67/3itOe9A7Sm1fc44MsZMS2I1jU650ZF9b4lo8xvozLTgIOBAYSjr3TP0L1aQgLar4qEpqyU1dHfNzKW1TvnqtOWdVdfgGbv/br0x4T30OiMGNqi+EwRsI51k0/vEn5JTif8esyac24SoT/ifuAGwhfQBEL7e38A7/0859xUQl/C6YQjk28750703m/pYtNVhP6C4zpZl9lx3qNRSj78XH4tut3unDuZ0OQjhCOTnqgCbibUN9NqwlEGhCa+33dSZhXh13621hGaIzMlvfcdaY89gN+3kzs1NXhPf0SkZP6/U9vJ/LE7ktDfZYqAJRGTN977Dc653wJXO+du995vTl/vnOtHSACLCc1ZpxKaglL+LO3xcYRfn1/23u+Mnj+zk31uIzSDPeyc+1fCl82fETr4dwPVGU95GagjNJm8RX4sjP6m/6Ie5Zw72Hu/BMA5dwiQYO/RxsvAjPRf7xm2OedWAod673/YWQHn3BJCnT8MzE9bdVIPYn6VfY8S+qq7+vbGkYTX0xQBSyIm375AGGH0inNuNmEk0W5CJ+xXgUujI4j/SzhqWAe8DpxP6Aw+M9rOu4Rfpv/onPsfQsfr7PQdOee+SmgCmUfolL6I0LH/TlTkPeDTzrkZwBpgK6EP5XfAQ865fyI0y4wgfPG2dfUF3RXn3C8JzUfPRbGMB64lDGv+TVrRHcCPnXPXRI9vj+J+Mno8G3jcOXcLcF8UayNh4MHVUSL9Z+Ae59xG4NfRPg4HzvHe/633frtz7gfAjc65NYQ+msuBQwmd7QfyCGEIdq50V98ecc41AuPY22xn4hZ3p4zdyv8GjCKMCnqH0J69ltDf8VmiDmd6NsT3KmAlYWjpM8DZhMRyWrT+bwkjerYQhgHPBWalPX8k4ctxM/sO8a2N9v1etO/VhFFCH4nWT4nKn9yDul5BGL7aQji6agJ+BXworcz1hKOvzxI6x9sIX6ZTM7Z1CiHBbSU0pS0kDL1N76T/OOF8lB1RvecBs9PW1wL/FdV5M3AXPRviOzTa3ofTll0GtGeU+yxRC17asguj/1dNT+ubKpOxnZOj7UxJW/Yt4LG439N223tLDa8zxhSIc+564LPe+2lxx3IgzrnrCKOuPt7H7VxPDurrnBtCSEYf996/0Jdtmdyx0VnGmK78O6EZMu9zZ/XQVMI5R5ZAioj1iRhjOuW9bwO+HXccKd77N9l3eLEpAtacZYwxJmvWnGWMMSZrldicZYdexhiTnf1OIK3EJEJzc3Os+08kErS2tsYaQ65ZnYpfudUHrE6F1NDQ0Olya84yxhiTNUsixhhjsmZJxBhjTNYsiRhjjMmaJRFjjDFZsyRijDEma5ZEjDHGZM2SiDGd8E0r2P6rn+K3b4s7FGOKWkWebGjMgfjdu0h+fzbbNm2AeS9RffW1cYdkTNGyIxFjMvgXfg+bNtDviGPg9Zfw69fFHZIxRcuSiDEZ/LyXYNRYhl319fD45WdijsiY4mVJxJg0vv19WPQm7oiZ1IwdD2PH4995K+6wjClalkSMSde8AnbvgsbpALhp02HJ2/hkMubAjClOlkSMSeNXvgeAm3hQWHDQobB9K6xbHWNUxhQvSyLGpFv5HgwYCKPHAuAmTAnLm1fEF5MxRcySiDFp/IolMGEKrqo6LBg3MSxvWh5jVMYUL0sixkS897BqGW7i1D3L3MBaqB9tRyLGdMGSiDEpWzfBzh0wduK+yxsm4S2JGNMpSyLGpKxpAcCNHrfPYtcwCVY34Ts64ojKmKJmScSYiF8bkghj9k0ijGmAjnbYYGeuG5PJkogxKWuboaoKRo7eZ7EbFUZq0bomhqCMKW6WRIxJWdsCiTG4mox5SaMk4u1cEWP2Y0nEmIhf2wwZ/SEAjKiH6mpotSRiTCZLIsaktK7BJcbut9hVVYdhvuusOcuYTJZEjAH8zh2wYzvUj+q8QGKsNWcZ0wlLIsYAbGgNf0d2nkRcYox1rBvTCUsixsCe4buuiyTCyARs34rftauAQRlT/Ap2eVwRORu4DagG7lbVmzLWDwDuA2YC64ELVHWZiJwJ3AT0B3YDX1XVp6LnPA2MA3ZGmzlLVdcWoDqmzPjUOSBdJpFo+cZWGDu+MEEZUwIKciQiItXAncA5wHTgIhGZnlHscmCjqk4DbgVujpa3Aueq6pHApcD9Gc+7WFWPim6WQEx21q8NI7DqRnS62o2oD3c2thYwKGOKX6Gas44HFqvqUlXdDTwAzMooMwu4N7r/IHCGiDhVfU1Vm6Pl84Ha6KjFmNzZsA7q6vfO3ptpZAIAb0nEmH0UqjlrPLAy7fEq4ISuyqhqu4hsBuoJRyIpnwJeVdX0hukfi0gH8EvgRlX1mTsXkSuBK6Ntk0gk+lidvqmpqYk9hlwr9Tpt2LoJxjQwMq0O6XXyQ4eyFhi0awdDSrSepf4adcbqFL+C9Yn0lYjMIDRxnZW2+GJVbRKRoYQk8jlCv8o+VPUu4K7ooW9tjffXZCKRIO4Ycq3U69SxpgXXOH2fOuxXpyHD2LFqBW0lWs9Sf406Y3UqnIaGhk6XF6o5qwlIn197QrSs0zIiUgMMJ3SwIyITgIeBS1R1SeoJqtoU/d0K/JTQbGZMr/hkR+jr6KpTPWVkAr9xfWGCMqZEFOpIZC7QKCJTCcniQuAzGWXmEDrOnwfOB55SVS8idcBvgK+p6rOpwlGiqVPVVhHpB/wl8Lu818SUn00bIZnsPomMSNi5IsZkKEgSifo4rgYeIwzx/ZGqzheRG4CXVXUOcA9wv4gsBjYQEg3A1cA0YLaIzI6WnQVsBx6LEkg1IYH8sBD1MWWmu3NEIm5EAv/ugkJEZEzJKFifiKo+AjySsWx22v024NOdPO9G4MYuNjszlzGaytTtOSIpI+phxzb8rjbcgIH5D8yYEmBnrBuzJ4l0MyImtd6G+RqzhyURYzasg0GDcbWDDljMjYiOVDZYEjEmxZKIqXh+/brum7IgNGdhJxwak86SiDEbeppErDnLmEyWRIzZsK7bkVkArl8/GDIMNm4oQFDGlAZLIqai+bboYlQ9ORIBqKvHb7ITDo1JsSRiKtv6aGRWV1c0zDSi3pqzjEljScRUth6eaJjiRtTDJmvOMibFkoipaH59dAma+tE9e0JdPWzdjH///fwFZUwJsSRiKtuGdeFiVMPrelY+dXEq6xcxBrAkYird+nUwItH1xagyuLpUErEmLWPAkoipcH7Dup43ZcHeEw7tSMQYwJKIqXTr1+G6mzMrnV1r3Zh9WBIxFcu3t4dmqd4cidQOhv4D7IRDYyKWREzl2rQefA8uRpXGORdGaFlzljGAJRFTyVLniPT0RMOUEfU2CaMxEUsipmL59T28GFUGO+HQmL0siZjK1dMrGmaqC0nEJ5O5j8mYEmNJxFSudathWB2u/4DePa+uHjraYdvm/MRlTAmxJGIqll/XAqMbev08t2eYrzVpGWNJxFSutS240eN6/zyb+sSYPSyJmIrkd7WFzvFskkidXSbXmBRLIqYyrWsJf7NozmJ4HVRVWXOWMVgSMZVqbUgi2TRnuapqGDbCmrOMwZKIqVA+SiKMGpvdBuyEQ2MASyKmUq1tgaHDcYMGZ/d8O+HQGABqCrUjETkbuA2oBu5W1Zsy1g8A7gNmAuuBC1R1mYicCdwE9Ad2A19V1aei58wEfgLUAo8AX1JVX5gamVLm17Zk16kecXX1+IWv5zAiY0pTQY5ERKQauBM4B5gOXCQi0zOKXQ5sVNVpwK3AzdHyVuBcVT0SuBS4P+05/wlcATRGt7PzVglTNrz30LQc1zAp+43U1cPOHfi2HbkLzJgSVKgjkeOBxaq6FEBEHgBmAQvSyswCro/uPwjcISJOVV9LKzMfqI2OWkYCw1T1hWib9wEfB36bx3qYcrBlE2zbAuMnZ7+N9BMOxw3KSVjGlKJCJZHxwMq0x6uAE7oqo6rtIrIZqCcciaR8CnhVVXeJyPhoO+nbHN/ZzkXkSuDKaNskEr24CFEe1NTUxB5DrpVSnXatWsomoO7wI+l/gJgPVKfdUw5iIzDMtzOgROpdSq9RT1md4lewPpG+EpEZhCaus3r7XFW9C7greuhbW+MdVZNIJIg7hlwrpTolF74JwOahI3AHiPlAdfIufHQ2L1tCVcOUnMeYD6X0GvWU1alwGho6P6eqUKOzmoCJaY8nRMs6LSMiNcBwQgc7IjIBeBi4RFWXpJWf0M02jdlf07IwMmvo8Oy3UZdqzrJzRUxlK9SRyFygUUSmEr7oLwQ+k1FmDqHj/HngfOApVfUiUgf8Bviaqj6bKqyqLSKyRUROBF4ELgFuz3tNTMnz770Lkw/u0zbcgAEwaIgN8zUVryBHIqraDlwNPAYsDIt0vojcICLnRcXuAepFZDFwDfC1aPnVwDRgtojMi26pi2J/AbgbWAwswTrVTTf8ju3QshJ30GF935idcGgMzvuKO63CNzc3xxpAsbZ59kWp1MkvmEfy1tlUfflbuBlHH7Bsd3XquO162LqF6mtvyXGU+VEqr1FvWJ0KJ+oTcZnL7Yx1U1H80kXhztTGPm/L1dXb/Fmm4lkSMRXFv/0GTJiCGzSk7xurq4ctm/Dt7X3fljElypKIqRi+bQcsXoCbcUxuNjhiJHgPmzfmZnvGlCBLIqZyLHwDOjpwR87MyebciOiEMGvSMhXMkoipGP6156F2MBycg5FZsPdcEUsipoJZEjEVwe9qw7/6PO7Yk3A1/XKz0Wj+LL9+XW62Z0wJsiRiKoJ/5TnY1YY74bTcbXTwUBhQCxssiZjKZUnElD3vPf6JX8O4idCYeQWC7DnnIDEa37omZ9s0ptRYEjHlb8E8WPUe7mOfwFXl+C2fGAOWREwFsyRiyl7ysYegbiTu+D/L+bZdYgy0rqUCZ34wBrAkYsqcX74YFr6O++h5uH456lBPlxgNu3bC9q2537YxJcCSiClr/tGHoHYQ7pSP5WX7rn5MuGNNWqZCWRIxZcuvbcG/8hzu1LNxgwbnZyeJKImsX5uf7RtT5CyJmLLln/g1VFfhPnpu/nZSH65KYCO0TKWyJGLKkt/Vhn/+97jjTg2z7eaJGzQ4XJyq1Y5ETGWyJGLKkn/5Wdi1E3fKWfnfmZ0rYiqYJRFTlvyzT8CY8TDt8PzvLDHG+kRMxepxEhGRWSJSqGuyG5M1v6YZ3l2AO+mj4azyPHPRCYc+mcz7vowpNr05ErkBaBGRO0TkhHwFZExf+ZefAcCdeFphdji6Ad7fbbP5morU4ySiqh8EPgrsBH4pIotE5FoRmZKv4IzJhn/1OTj4MNyI/HWop3Ojx4U7a5oLsj9jikmv+kRU9XVV/SowEbgK+DSwRET+KCIXi4j1sZhY+XWrYcVS3DEfKtxOxzSEfVsSMRWo130cInIw8NnolgRmAyuAq4FPAZ/MZYDG9IZ/7XkA3NEFTCJ19dC/P6y1JGIqT4+TiIhcBXwOaAR+DnxOVV9IW/9LwIaomFj5116AiVNxo8YWbJ+uqgpGjbMjEVORenMkcg7wPWCOqu7KXKmqO0TEjkJMbPz2rbBkEe4vpPA7H9MAzSsKv19jYtabPoynVfUXmQlERK5J3VfVx3MWmTG95Be8Dj6JO+KYgu/bjW6AdWvwHR0F37cxcepNEpndxfJrcxGIMX02/5UwBcnUxsLve0wDdLTbSYem4nTbnCUiH0mVFZHTgfSztw4CenQhBRE5G7gNqAbuVtWbMtYPAO4DZgLrgQtUdZmI1AMPAscBP1HVq9Oe8zQwjjDsGOAsVbVPcQXy3uPfeg0342hcVXXB9+9GN+AhdK6nhvwaUwF60idyT/R3APCjtOUeWA38fXcbEJFq4E7gTGAVMFdE5qjqgrRilwMbVXWaiFwI3AxcALQB1wFHRLdMF6vqyz2ohylnq5bB5g0wo/BNWcA+w3zdETPjicGYGHSbRFR1KoCI3Keql2S5n+OBxaq6NNrWA8AsID2JzAKuj+4/CNwhIk5VtwPPiMi0LPdtKoB/61UA3Iyj4wlgWB0MGgwtK+PZvzEx6fHorD4kEIDxQPqnaxWQOXXKnjKq2i4im4F6oLWbbf9YRDqAXwI3qup+F7sWkSuBK6Ntk0gksqpErtTU1MQeQ67FXacNi97AT22kftohOdtmb+u0YdJBsG41I4v0tY37NcoHq1P8DphERGShqh4e3V9JaMLaj6pOykNsPXGxqjaJyFBCEvkcoV9lH6p6F3BX9NC3tnaXl/IrkUgQdwy5Fmed/K42km+/ifvoeTmNobd1So4ah3/thaJ9be19VxqKtU4NDQ2dLu/uSOSKtPuf7cP+mwhTpaRMiJZ1VmZVNFvwcEIHe5dUtSn6u1VEfkpoNtsviZgyt2QhdLTjDvtAvHE0TIQ/PY7fuhk3dHi8sRhTIAdMIqr6TNr9P/RhP3OBRhGZSkgWFwKfySgzB7gUeB44H3iqs6aplCjR1Klqq4j0A/4S+F0fYjQlyr/9JlRXF+baIQfgxk0Kh+rNK+DQI2ONxZhC6c20J9cQvtjniciJgAIdwGdU9fkDPTfq47gaeIwwxPdHqjpfRG4AXlbVOYRRYPeLyGJgAyHRpPa9DBgG9BeRjwNnAcuBx6IEUk1IID/saX1M+fDvvAVTGnEDa+MNZFw42PbNK3GWREyF6M20J//A3uG+/wbcQjhH5Pvs30m+H1V9BHgkY9nstPtthFmBO3vulC42a2MpK5xv2wnL3sWd9Ym4Q4ER9VA7CFps+hNTOXpzxvpwVd0cdWJ/ELhdVe8BDs1PaMb0wOKF0NFRFL/8nXMwbiK+2Yb5msrRmyORlSLyYWAG8EdV7RCRYYQmLWNi4d8pjv6QFDduIv6NuXGHYUzB9CaJfJVwEuBuwnVDIHRmv5TroIzpKf/O/NAfMmBg3KEEDZPg2d/ht27BDR0WdzTG5F1vTjZ8BMgcKPyL6GZMwfn334fli3EfOTfuUPZwDRPDCK2WlTB0RtzhGJN3vbqyoYgMJ/SBDMlY9VTOIjKmp1YuhfZ23EFF1C03Lpx361tW4g6xJGLKX2+G+F5GmERxG7AjbZUnzOZrTEH5pYvCnWJKIiMTMLDWLlBlKkZvjkT+BThfVX+br2CM6ZWli2BEAjeiPu5I9nDOwfjJ+KblcYdiTEH0ZohvDWBXLjRFwy9dBAflbsLFXHHjp8DK9/C+ywkXjCkbvUkiNwPXikhvnmNMXvjNG2H92uLqD0mZMAV2bIONB5z6zZiy0Nsz1scC/yQi+3w6YpzF11Sq994BKMok4iZMCSO0mpaFPhJjylhvkkhfZvE1Jqf8iqXgHEyYGnco+xs/GQC/ahnuyGNjDsaY/OrNeSJ9mcXXmJzyK9+D0Q3xT7rYCTdoMNSPDpfsNabM9WaI7wBgNnARUK+qw0XkLOAQVb0jXwEa06mVS4uyKWuPCVNCojOmzPWmk/xW4AjgYvZe4XA+8He5DsqYA/Hbt8H6tTCxCJuyIm7CFFjThH9/d9yhGJNXvUkin2DvtUOSsOfKguPzEZgxXVq5FABX7EkkmQzTnxhTxnqTRHaT0fwlIqPo5hK2xuTanmaiSUU8UcKEKUDoXDemnPUmifwCuDe6xC0iMg64A3ggH4EZ06WVS2H4CNywEXFH0rXR46B/f+tcN2WvN0nkG8BS4E2gDngXaAG+lfuwjOmaX/leUfeHALiqamiYbEcipuz15jyRacAi4F8J1zT/laq+mZeojOmCT3bA6ibc9KPjDqVbbsIU/Osv4b0Pc2oZU4a6TSIi4gjXVr8UWAU0EzrTvyki9wN/rao2SZApjNY10P4+jJsQdyTdmzAFnnkCtmyC4UXc9GZMH/TkSORK4DTgRFXdc91PETkO+Bnwt8AP8hKdMZmi65e7cRNjDqR7e6Y/WbXMkogpWz3pE/kc8MX0BAIQPf5ytN6YgvCpIbMlkETSpz8xplz1JIlMB7qa8uQP0XpjCqNlJdSNDFOLFDk3ZBjU1e85r8WYctSTJFKtqls7WxEtt6nhTcH45pWlcRSSMvngMFmkMWWqJ30i/UTkdKCr4SW9uk67Mdny3sPqVbiTz4w7lB5zkw7Cv/EyflcbbsDAuMMxJud6kgDWAj/qZr0x+behFXa1wdgSGJkVcZOn4X0yNGlNs5ZfU366TSKqOiUXOxKRs4HbCOeY3K2qN2WsHwDcB8wkTKVygaouE5F64EHgOOAnqnp12nNmAj8BaoFHgC/ZcOMyFnWqu4bSas4C8MuX4iyJmDJUkP4MEakG7gTOIXTEXyQimZ+oy4GNqjqNMGPwzdHyNuA64CudbPo/gSuAxuh2du6jN8Vi78isErqQ5vCRMKwOli+OOxJj8qJQneLHA4tVdamq7ibMtzUro8ws4N7o/oPAGSLiVHW7qj5DSCZ7RHN3DVPVF6Kjj/uAj+ezEiZmLSthyDDc0GFxR9JjzjmYPA2/YkncoRiTF4VKIuOB9DmxV7H/FPJ7yqhqO7AZqO9mm6u62aYpI75lJZRSU1bETToImlfid+2KOxRjcq4iRlaJyJWEM+9RVRKJRKzx1NTUxB5DruW7Tt571q1excAPn8GwAv3vclWntiOPZvNvlOHbNtJ//BE5iCw79r4rDaVWp0IlkSYg/SfkhGhZZ2VWiUgNMJwDX6ukKdrOgbYJgKreBdwVPfStra09jzwPEokEcceQa/muk9+6Gb9tK20j6tldoP9drurkR4wGYNMbr1JVP7bP28uWve9KQ7HWqaGhodPlhUoic4HG6FokTcCFwGcyyswhTPL4PHA+8NSBRlqpaouIbBGRE4EXgUuA2/MRvCkCq8PvAzemdIb37jEiAUOGWee6KUsF6ROJ+jiuBh4DFoZFOl9EbhCR86Ji9wD1IrIYuAb4Wur5IrIMuAW4TERWpY3s+gJwN7AYWAL8thD1MYXnV0fdX2NLr9srdK4fjF9uneum/DjvK+60Ct/c3BxrAMV6uNoX+a5T8sEf45/8X6ru1HDBpwLIZZ2SD92Hf/xhqm7/Oa5f/5xss7fsfVcairVOUXPWfjOX2LxXpiT41U0welzBEkiuuSmN0NEBNo+WKTOWRExpWNNUkk1Zexx8GAB+ydsxB2JMblkSMUXPt7fDutW4MaWbRNzwEVA/Gr/UkogpL5ZETPFrXROagkr5SARwBx8GSxbFHYYxOWVJxBS/NanhvaWdRDjoUNi0Hr9hXdyRGJMzlkRM0fPROSKlNAV8Z9xBoV+EpXY0YsqHJRFT/NY0wdDhuMFD4o6kbyZOgX798dakZcqIJRFT9PzqVVDqTVmAq+kXZvS1znVTRiyJmOK3uglX4p3qKe7gw2D5EpvR15QNSyKmqPkd22Dr5pIfmZXiDj0SOtrBjkZMmbAkYorb6jIZmZUy7XBwVfh33oo7EmNywpKIKWp7R2aVRxJxtYPCZIyL3ow7FGNywpKIKW5rmqC6GhLxXYcj19yhR8B77+B3W7+IKX2WRExR86ubIDEWV1M+F+F0hx4J7e12vogpC5ZETHEr9YkXOzNteugXWWT9Iqb0WRIxRcsnO2BNc/l0qkdc7SCYdBD+HesXMaXPkogpXuvWQPv70DAx7khyzh16JCxdZP0ipuRZEjHFq2k5AK5hcsyB5J47/AOhX+TdBXGHYkyfWBIxRcs3rwh3xpX2xIudajwCavrh578adyTG9IklEVO8mldA/WjcwNq4I8k5N2AANE7HL5gXdyjG9IklEVO0fPMKGF9+TVkpbsbR0LQcv3F93KEYkzVLIqYo+fb2MPFiw6S4Q8kbN+NoADsaMSXNkogpTutawkSFZZxEGD8Fho8A6xcxJcySiClOUae6G1++ScQ5h5t+FH7hPHwyGXc4xmTFkogpSr5pOThX8pfE7db0o2HbVlixJO5IjMmKJRFTlPyKpTB2Aq7/gLhDySs3/SgA/PzX4g3EmCxZEjHFacVS3OSD444i79ywujAFivWLmBJVsKlRReRs4DagGrhbVW/KWD8AuA+YCawHLlDVZdG6rwOXAx3AF1X1sWj5MmBrtLxdVY8tSGVMXvktm2BjK0wq/yQC4I44Fv/og/jt23CDh8QdjjG9UpAjERGpBu4EzgGmAxeJyPSMYpcDG1V1GnArcHP03OnAhcAM4GzgP6LtpZyuqkdZAikjUf+Aq5Qk8oFjIZm0oxFTkgrVnHU8sFhVl6rqbuABYFZGmVnAvdH9B4EzRMRFyx9Q1V2q+h6wONqeKVN+edTJPHFqvIEUytRGGDocXp8bdyTG9FqhmrPGAyvTHq8CTuiqjKq2i8hmoD5a/kLGc1Nzg3vgcRHxwH+p6l2d7VxErgSujLZNIpHoW236qKamJvYYci2Xddq0ehXt4yaQmBTv2eqFfJ02H3sSu+b+ifoRdbjq/Hws7X1XGkqtTqV+ubiTVbVJREYDT4jI26r6x8xCUXJJJRjf2tpa0CAzJRIJ4o4h13JVJ+89yYVv4A49Mvb/USFfJ3/okfjfP0Lri8/iDpmRl33Y+640FGudGhoaOl1eqOasJiD9ohATomWdlhGRGmA4oYO9y+eqaurvWuBhrJmr9LWugc0boDGzy6zMTT8aqqvxb1iTlikthUoic4FGEZkqIv0JHeVzMsrMAS6N7p8PPKWqPlp+oYgMEJGpQCPwkogMFpGhACIyGDgLsOuNljgfXV/DVVgScbWD4JAjLImYklOQJKKq7cDVwGPAwrBI54vIDSJyXlTsHqBeRBYD1wBfi547H1BgAfAocJWqdgBjgGdE5HXgJeA3qvpoIepj8mjxAhg0GMaV39UMu+M+cCy0rMSvWx13KMb0mPPexx1Dofnm5uZYAyjWNs++yFWdOmZfBYkxVH9xdg6i6ptCv05+bTPJf/487sIrqDrj3Jxv3953paFY6xT1ibjM5XbGuikafuN6aFmZt47lYudGN8C4ifhXn487FGN6zJKIKRr+rVcAcEdW7nmjbuZJ8O58/JaNcYdiTI9YEjFFw7/1CoxMlPc1RLrhjj0JvLejEVMyLImYouDb34cF83BHHItz+zW7Vo6GSTB2PP6V5+KOxJgesSRiisPbb0DbzjBCqYI553DHnASL3goTURpT5CyJmKLgn38aBg0JJ91VuNCklcTPe6H7wsbEzJKIiZ1v24Gf9zzuuJNx/frFHU78JkyB0Q34l/4UdyTGdMuSiImdf+U52L0bd8JpcYdSFJxzuA+dDovetBMPTdGzJGJi5b3HP/FrGD8Zph0edzhFw334I+Ac/rmn4g7FmAOyJGLitWAeNC3Hnfnxyh6VlcGNHAWHH4V/7kl8Mhl3OMZ0yZKIiY33nuT/PgDDR+KOPzXucIqOO+kM2LAujFwzpkhZEjHxmfciLF6IO+9C61DvhDv6RBg8lOTvfxN3KMZ0yZKIiYXftYvkgz+GcRNxJ50ZdzhFyfXrjzvtHHj9JfzqzMvvGFMcLImYWPg5P4W1LVRddCWuujrucIqW+8hfhItV/e7XcYdiTKcsiZiC80vexj/xa9ypZ+MO/2Dc4RQ1N2wE7kMfwT/3VJjl2JgiY0nEFJTfuoXkf30H6kfhzr8s7nBKgjvnfEgmw9GbMUXGkogpGJ/sIHn392DrZqo+/7VwSVjTLTdqLO70P8c/+yR+5Xtxh2PMPiyJmILxv/4ZLHgNd9EVuMkHxx1OSXF/eQEMHUbyJ7fh29vjDseYPSyJmIJIPvsk/hHFnXwm7pSPxR1OyXGDh1J18edhxVL8r+6POxxj9rAkYvLOL3oTf/+dcPgHcRf/nZ2ZniV3zIdxf3Y2/rGHSf7xsbjDMQaAmrgDMOXNr15F8j/+DUaPo+rz/wdXY2+5vnAXXolvXYO//06S27bgzv4Ursp+C5r42LvP5I1fv47krbOhupqqv78ON2hI3CGVPFdTQ9VV1+KOOwX/8P0k//3r+IWv472POzRToexnockLv2VjSCA7d1L1lRtxo8bGHVLZcP36wRVfgRnH4B+6l+Qt18GY8bijT8QddQJMbcRV2QmcpjAsiZicCwnkm7Cxlap/+BZuko3EyjXnHO6kM/DHn4J/4Wn83D/hH38Y/+gvYchQ3PRj4MiZuBnH4IYOiztcU8YsiZic8utWk/z+N2HTBqqu+mfctOlxh1TWXL/+uFPOglPOwm/fip//Grz5Cn7+q/DSH/DOwZRG3AePp/3Mc6F/bdwhmzJjScTkjH/rFZL33ArJJFXXfBt38GFxh1RR3OChYUr9408N1yBZvgT/5svh9qv/Zv2v/hsmTsUddwru2JOtidHkRMGSiIicDdwGVAN3q+pNGesHAPcBM4H1wAWquixa93XgcqAD+KKqPtaTbZrC8BvXs/mnPyD5+0dg/OQwCmvshLjDqmiuqir0jUxthPMuwm9Yx6C3X2fb04/iH7oP/9B9MHlaSChTD4FhdYCH9nZo2wm72mDXTnzbTnBVYVDE4Og2KNxs+n4D4AoxqkNEqoF3gDOBVcBc4CJVXZBW5gvAB1T18yJyIfAJVb1ARKYDPwOOBxqA3wGHRE874Da74Jubm3NXuSwkEglaW1tjjSFb3nvYuQPWr8UvXYR/6xV4Yy5UVePOOBd33kW4/gPiDjMnSvl16kyqPr51Df6VZ/Fzn4Hli7PfYP8BIaHUDoIBA/fc3ICBMLA2PO4/EAam1tXiBgyA2sEwZBgMHQZDhnX6fvE+LaHt3Abbw81v3wo7tsP2rbC7jUF1I9mRTELtYNzgITB4WJTshsLgIbia0kt0xfq+a2hoANjvJK9CHYkcDyxW1aUAIvIAMAtI/8KfBVwf3X8QuENEXLT8AVXdBbwnIouj7dGDbeZMxx03wtoW2Cfp+n3+dL5u/yTdWlVFR0dHl+v3Lktbt98+Olm3z7Ku93/AOnS2j/R1He/D7t17Hw8fiTtzFvWfuJiN1f3335cpOi4xBvexT8LHPolfvxZaVuG3bQ5HHDU1MKA2+uKvDckgmYQdGV/iO7btXda2A3btgl07YdN6fFsb7G4LRzNtbeD3Xt6305+s/fpDdTVUVUNVVdjfrp2Q+ox0pbqG7R17p4DpdNsDaqG2FlxV2LZz0d/ofhGe+NpaXb33+yHHqq77fs6PIAuVRMYDK9MerwJO6KqMqraLyGagPlr+QsZzx0f3u9smACJyJXBltG0SiUSvK7B10lQ6BkfnOaS/8dy+d/Y5G7uzN6hzOFeF3+ct77rd7j7ro7/7bN11so0st9tZuT31qq6makQ91fWjqTn4MKrHjsc5R01NDYkym9OppqYmq/dKseq0PokEHJq/wQ/ee3h/N74tNI35nTtIbt9Gcusmkls247dsIrl1CyQ78MmOkDiqqnG1g6iqHYQbWIsbPISqwcNwQ4dRNXjo3r/9+lENvL9tC37HdpJbt5Dcuhm/LfxNbtsSZo3euSMkpmQyJDTvw76SxXluTZVzJPPUQjQ8kSjZJBIrVb0LuCt66LM6VDzv4pzFU6yHq1lZH65xUVZ1ipRbnWKvT1U/GDw83EaP7758V9qTsHkzEOq0oW132Pbw+nArcfl8ndZH/7dsRM1Z+ynUGetNwMS0xxOiZZ2WEZEaYDihg72r5/Zkm8YYY/KoUEcic4FGEZlK+KK/EPhMRpk5wKXA88D5wFOq6kVkDvBTEbmF0LHeCLxEaGfpbpvGGGPyqCBHIqraDlwNPAYsDIt0vojcICLnRcXuAeqjjvNrgK9Fz50PKKHD/FHgKlXt6GqbhaiPMcaYoCBDfIuMDfHNA6tT8Su3+oDVqZC6GuJrs/gaY4zJmiURY4wxWbMkYowxJmuWRIwxxmStIjvW4w7AGGNKlHWsE/4Jsd5E5JW4Y7A6VV6dyq0+VqdYbvupxCRijDEmRyyJGGOMyZolkXjc1X2RkmN1Kn7lVh+wOsWuEjvWjTHG5IgdiRhjjMmaJRFjjDFZq4iLUhULEbkeuAJYFy36hqo+Eq37OnA50AF8UVUfiyXIXhKRs4HbgGrgblW9KeaQsiIiy4CthP9/u6oeKyIjgZ8DU4BlgKjqxrhi7I6I/Aj4S2Ctqh4RLeu0DtGlp28D/hzYAVymqq/GEfeBdFGn6ynRz5GITATuA8YQzlm7S1VvK+XXyY5ECu9WVT0quqXe+NMJ10OZAZwN/IeIVMcZZE9EMd4JnANMBy6K6lKqTo9el2Ojx18DnlTVRuDJ6HEx+wnh/ZOuqzqcQ7g2TyPh0tH/WaAYe+sn7F8nKN3PUTvwj6o6HTgRuCqKu2RfJ0sixWEW8ICq7lLV94DFwPExx9QTxwOLVXWpqu4GHiDUpVzMAu6N7t8LfDy+ULqnqn8ENmQs7qoOs4D7VNWr6gtAnYiMK0igvdBFnbpS9J8jVW1JHUmo6lbCtZDGU8KvkzVnFd7VInIJ8DLhF8lGwpvohbQyq6JlxW48sDLt8SrghJhi6SsPPC4iHvgvVb0LGKOqLdH61YQmiFLTVR06e+3GAy2UhpL/HInIFOBo4EVK+HWyJJJjIvI7YGwnq/6ZcCj6bcIX1reB7wF/XbjozAGcrKpNIjIaeEJE3k5fGV2quaTHw5dDHSIl/zkSkSHAL4Evq+oWEdmzrtReJ0siOaaqH+1JORH5IfC/0cMmYGLa6gnRsmJXqnHvR1Wbor9rReRhQjPIGhEZp6otURPC2liDzE5XdSjZ105V16Tul+LnSET6ERLI/6jqQ9Hikn2drE+kgDLaMj8BvBXdnwNcKCIDRGQqoRPtpULHl4W5QKOITBWR/oROzTkxx9RrIjJYRIam7gNnEV6bOcClUbFLgV/HE2GfdFWHOcAlIuJE5ERgc1pzSlEr5c9RNNrqHmChqt6StqpkXyc7Eims74jIUYTD8GXA3wKo6nwRUWABYfTGVaraEVeQPaWq7SJyNfAYYYjvj1R1fsxhZWMM8HDUpFAD/FRVHxWRuYCKyOXAckAOsI3YicjPgNOAhIisAr4J3ETndXiEMGx0MWHo6F8VPOAe6KJOp5Xw5+gk4HPAmyIyL1r2DUr4dbJpT4wxxmTNmrOMMcZkzZKIMcaYrFkSMcYYkzVLIsYYY7JmScQYY0zWLIkYExMReVpE/uYA66eLyMvRuQW53vf1IvLfB1j/kojMyPV+Tfmx80RMxRGRk4HvEGZ77SBMgvdlVZ0ba2D7+zbwXVWNYxz+d4EbgE/FsG9TQuxIxFQUERlGmCbjdmAkYTK7bwG74owrU3RW9unAr2IKYQ5wuoh0Ng+cMXvYkYipNIcAqOrPosc7gcdTK0XkMsIFj14jnFncQjjz+clo/XDgFsJZxEngx8A3U2dGi8hfA18lTML5EnClqi6P1p1JSF7jgPuBAzVTnQm8qqptabEtI1y/5XPAwYSp979BuObGyYTZYD8dXcxoCvAe4Wzu66N9fU9Vv5u2j/4ich9h6pAVwKWq+nL0/2kTkVeAj7F3inJj9mNHIqbSvAN0iMi9InKOiIzopMwJwBIgQZhm46HoynMQvrDbgWmEabzPAv4GQERmEb7UPwmMAv4E/CxalwAeAq6NtruEMAVGV44EFnWy/FOEBHMIcC7w22ifowif5y9mlD+dMIfUWcD/EZH0CULPIySiOsKRxx0Zz10IfPAAMRpjScRUFlXdQvjV7oEfAutEZI6IpF8rZC3wfVV9X1V/Tvgy/4uozJ8T+k+2q+pa4FbCxJMAnwf+TVUXqmo78K/AUSIyOXrefFV9UFXfB75PuG5EV+oIl+vNdLuqrolmHf4T8KKqvhYdsTxMSGzpvhXF+ibhqOmitHXPqOoj0VHU/eyfMLZGcRjTJWvOMhVHVRcClwGIyGHAfxO+1FNfsE0ZndnLgQZgMtAPaEm7/kMVey8aNBm4TUS+l/ZcR+h3aUgrl7pmRPrFhjJtBIZ2snxN2v2dnTweklE+fR/LCUc4KelJbAcwUERqogRItP9NB4jRGEsiprKp6tsi8hOimWAj40XEpSWSSYTmnpWEDvhE2hdtupXAv6jq/2SuEJFG0q4LEQ3bnZhZLs0b7J0avC8mAqkLbE0Cmnvx3MMJCdaYLlkSMRUlOvL4C+DnqrpKRCYSjkDSL6s6GviiiPwH4VrXhwOPqOp6EXkc+J6IXAdsA6YCE1T1D8APgG+LyLxoWvLhwFmq+gvgN8AdIvJJQkK6is6vgJnyBOGoZmB653oWrhORK6I4/wr4bE+eJCIDgZnkJpGZMmZ9IqbSbCV0nL8oItsJyeMt4B/TyrxI6IxuBf4FOF9V10frLgH6E65ZsRF4kDDaClV9GLgZeEBEtkTbPSda1wp8mnDdiPXR9p/tKsjo6n1PAbP6WN8/EK5F8SThnJPHuymfci7wtKr25sjFVCC7nogxaaIhvn+jqicXQSzTCcNrj+/tCYdpQ3z7ddH01t3zXwQuV9W3ui1sKpo1ZxlTpFR1AXBcTPs+IY79mtJjzVnGGGOyZs1ZxhhjsmZHIsYYY7JmScQYY0zWLIkYY4zJmiURY4wxWbMkYowxJmv/H5etA/W8JdmVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df['Speed_mph'].plot(kind='kde',\n",
    "                          title='Coaster Speed (mph)')\n",
    "ax.set_xlabel('Speed (mph)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "38e6c921",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Steel    816\n",
       "Wood     198\n",
       "Other     73\n",
       "Name: Type_Main, dtype: int64"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Type_Main'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29b63605",
   "metadata": {},
   "source": [
    "### STEP 4: FEATURE RELATIONSHIP ###\n",
    "\n",
    "- Scatterplot\n",
    "- Heatmap Correlation\n",
    "- Pairplot\n",
    "- Groupby comparisons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "f332991c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind='scatter',\n",
    "        x='Speed_mph',\n",
    "        y='Height_ft',\n",
    "        title='Coaster Speed vs. Height')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "07545a68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.scatterplot(x='Speed_mph',\n",
    "                y='Height_ft',\n",
    "                hue='Year_Introduced',\n",
    "                data=df)\n",
    "ax.set_title('Coaster Speed vs. Height')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "7a05b866",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 964.25x900 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df,\n",
    "             vars=['Year_Introduced','Speed_mph',\n",
    "                   'Height_ft','Inversions','Gforce'],\n",
    "            hue='Type_Main')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "a0c4cda4",
   "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>Year_Introduced</th>\n",
       "      <th>Speed_mph</th>\n",
       "      <th>Height_ft</th>\n",
       "      <th>Inversions</th>\n",
       "      <th>Gforce</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Year_Introduced</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.178619</td>\n",
       "      <td>0.145457</td>\n",
       "      <td>-0.172829</td>\n",
       "      <td>0.168763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Speed_mph</th>\n",
       "      <td>0.178619</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.734499</td>\n",
       "      <td>-0.026413</td>\n",
       "      <td>0.605090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Height_ft</th>\n",
       "      <td>0.145457</td>\n",
       "      <td>0.734499</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.076255</td>\n",
       "      <td>0.460841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inversions</th>\n",
       "      <td>-0.172829</td>\n",
       "      <td>-0.026413</td>\n",
       "      <td>-0.076255</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.270942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gforce</th>\n",
       "      <td>0.168763</td>\n",
       "      <td>0.605090</td>\n",
       "      <td>0.460841</td>\n",
       "      <td>0.270942</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Year_Introduced  Speed_mph  Height_ft  Inversions    Gforce\n",
       "Year_Introduced         1.000000   0.178619   0.145457   -0.172829  0.168763\n",
       "Speed_mph               0.178619   1.000000   0.734499   -0.026413  0.605090\n",
       "Height_ft               0.145457   0.734499   1.000000   -0.076255  0.460841\n",
       "Inversions             -0.172829  -0.026413  -0.076255    1.000000  0.270942\n",
       "Gforce                  0.168763   0.605090   0.460841    0.270942  1.000000"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_corr = df[['Year_Introduced','Speed_mph',\n",
    "    'Height_ft','Inversions','Gforce']].dropna().corr()\n",
    "df_corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "045ce661",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df_corr, annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7d5109e",
   "metadata": {},
   "source": [
    "#### END ####"
   ]
  }
 ],
 "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": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}