charts.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Load the JSON data from the file\n",
    "with open('prizepicks.json', 'r') as file:\n",
    "    data = json.load(file)\n",
    "\n",
    "# Clean the score data\n",
    "for item in data:\n",
    "    item['score'] = float(item['score'].split('.')[0] + '.' + item['score'].split('.')[1])\n",
    "    \n",
    "# Sort the data by score for better visualization\n",
    "sorted_data = sorted(data, key=lambda x: x['score'])\n",
    "\n",
    "# Separate names and scores for plotting\n",
    "names = [item['name'] for item in sorted_data]\n",
    "scores = [item['score'] for item in sorted_data]\n",
    "\n",
    "# Create a bar chart\n",
    "plt.figure(figsize=(14,10))\n",
    "plt.barh(names, scores, color='blue')\n",
    "plt.xlabel('Score')\n",
    "plt.title('Player Scores')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: kaleido in c:\\users\\ccscr\\anaconda3\\envs\\propbot\\lib\\site-packages (0.2.1)\n"
     ]
    }
   ],
   "source": [
    "! pip install kaleido"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'name': 'Oscar Piastri', 'score': 2.52}, {'name': 'Lando Norris', 'score': 2.52}, {'name': 'Max Verstappen', 'score': 2.452}, {'name': 'Sergio Perez', 'score': 2.42}, {'name': 'Charles Leclerc', 'score': 2.52}, {'name': 'Carlos Sainz Jr.', 'score': 2.652}, {'name': 'Logan Sargeant', 'score': 3.13}, {'name': 'Alexander Albon', 'score': 3.13}, {'name': 'Liam Lawson', 'score': 2.652}, {'name': 'Yuki Tsunoda', 'score': 2.92}, {'name': 'Pierre Gasly', 'score': 2.752}, {'name': 'Esteban Ocon', 'score': 2.652}, {'name': 'Lewis Hamilton', 'score': 2.852}, {'name': 'George Russell', 'score': 2.952}, {'name': 'Fernando Alonso', 'score': 2.82}, {'name': 'Lance Stroll', 'score': 2.72}, {'name': 'Valtteri Bottas', 'score': 3.33}, {'name': 'Zhou Guanyu', 'score': 3.253}, {'name': 'Nico Hulkenberg', 'score': 3.553}, {'name': 'Kevin Magnussen', 'score': 3.23}, {'name': 'Max Verstappen', 'score': 2.45}, {'name': 'Lando Norris', 'score': 2.5}]\n",
      "Index(['name', 'score'], dtype='object')\n"
     ]
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "hovertemplate": "x=%{x}<br>y=%{y}<br>color=%{marker.color}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": [
           2.42,
           2.45,
           2.5,
           2.52,
           2.52,
           2.652,
           2.652,
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           2.952,
           3.13,
           3.13,
           3.23,
           3.253,
           3.33,
           3.553
          ],
          "coloraxis": "coloraxis",
          "pattern": {
           "shape": ""
          }
         },
         "name": "",
         "offsetgroup": "",
         "orientation": "v",
         "showlegend": false,
         "text": [
          2.42,
          2.45,
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   ],
   "source": [
    "import plotly.express as px\n",
    "import pandas as pd \n",
    "# Clean the score data\n",
    "# for item in data:\n",
    "#     if isinstance(item['score'], str) and item['score'].count('.') > 1:\n",
    "#         item['score'] = float(item['score'][:item['score'].rfind('.')])\n",
    "print(data)\n",
    "for item in data:\n",
    "    item['score'] = str(item['score'])\n",
    "    item['score'] = float(item['score'].split('.')[0] + '.' + item['score'].split('.')[1])\n",
    "\n",
    "# Create and display a dataframe\n",
    "df = pd.DataFrame(data)\n",
    "#Print cols\n",
    "print(df.columns)\n",
    "\n",
    "# Drop the duplicated 'name' rows and keep the lowest score\n",
    "df = df.sort_values('score').drop_duplicates('name', keep='first')\n",
    "\n",
    "# Plotly chart\n",
    "# Make it horizontal so it fits in twitter better\n",
    "# fig = px.bar(x=df['name'], y=df['score'], color=df['score'], color_continuous_scale='reds')\n",
    "fig = px.bar(x=df['name'], y=df['score'], color=df['score'], color_continuous_scale='purples')\n",
    "fig.update_layout(title='Japan GP: 1st Pit Stop Time (Sec) - Over/Under (Prize Picks', xaxis_title='Name', yaxis_title='1st Pit Stop Time (Sec)')\n",
    "\n",
    "# Add data labels\n",
    "fig.update_traces(texttemplate='%{text:.3s}', textposition='outside', text=df['score'])\n",
    "\n",
    "\n",
    "fig.update_layout(xaxis=dict(autorange=\"reversed\"))\n",
    "fig.show()\n",
    "\n",
    "# Export for posting to twitter\n",
    "# fig.write_image('prizepicks1.png', width=1000, height=600, scale=2)\n",
    "# Write html file for posting to twitter\n",
    "fig.write_html('prizepicks1.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Grand Prix</th>\n",
       "      <th>Team</th>\n",
       "      <th>Driver</th>\n",
       "      <th>Fastest Stop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>Bahrain</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>2.22s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>2.10s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Australia</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>2.11s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>2.30s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Miami</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>2.21s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Emilia-Romagna</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Monaco</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>2.15s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>2.07s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Canada</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>2.23s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Austria</td>\n",
       "      <td>McLaren</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>2.10s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Great Britain</td>\n",
       "      <td>McLaren</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>2.23s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Hungary</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>1.98s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>Ferrari</td>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>2.19s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>2.01s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Italy</td>\n",
       "      <td>McLaren</td>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>2.13s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>Red Bull</td>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>2.32s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Japan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>United States</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Mexico</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Grand Prix      Team           Driver Fastest Stop\n",
       "0          Bahrain   Ferrari  Charles Leclerc        2.22s\n",
       "1     Saudi Arabia   Ferrari  Charles Leclerc        2.10s\n",
       "2        Australia  Red Bull     Sergio Perez        2.11s\n",
       "3       Azerbaijan  Red Bull     Sergio Perez        2.30s\n",
       "4            Miami   Ferrari     Carlos Sainz        2.21s\n",
       "5   Emilia-Romagna       NaN              NaN          NaN\n",
       "6           Monaco  Red Bull     Sergio Perez        2.15s\n",
       "7            Spain  Red Bull     Sergio Perez        2.07s\n",
       "8           Canada  Red Bull     Sergio Perez        2.23s\n",
       "9          Austria   McLaren     Lando Norris        2.10s\n",
       "10   Great Britain   McLaren     Lando Norris        2.23s\n",
       "11         Hungary  Red Bull     Sergio Perez        1.98s\n",
       "12         Belgium   Ferrari  Charles Leclerc        2.19s\n",
       "13     Netherlands  Red Bull   Max Verstappen        2.01s\n",
       "14           Italy   McLaren     Lando Norris        2.13s\n",
       "15       Singapore  Red Bull     Sergio Perez        2.32s\n",
       "16           Japan       NaN              NaN          NaN\n",
       "17           Qatar       NaN              NaN          NaN\n",
       "18   United States       NaN              NaN          NaN\n",
       "19          Brazil       NaN              NaN          NaN\n",
       "20          Mexico       NaN              NaN          NaN\n",
       "21       Las Vegas       NaN              NaN          NaN\n",
       "22       Abu Dhabi       NaN              NaN          NaN"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in standings.xlsx\n",
    "import pandas as pd\n",
    "df2 = pd.read_excel('standings.xlsx')\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Grand Prix', 'Team', 'Driver', 'Fastest Stop'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# print cols\n",
    "print(df2.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Teams with Most Fastest Stops:\n",
      "- Red Bull: 8\n",
      "- Ferrari: 4\n",
      "- McLaren: 3\n",
      "\n",
      "Driver with Most Fastest Stops:\n",
      "- Sergio Perez: 7\n",
      "- Charles Leclerc: 3\n",
      "- Lando Norris: 3\n",
      "- Carlos Sainz: 1\n",
      "- Max Verstappen: 1\n",
      "\n",
      "Fastest Pit Stop:\n",
      "- 1.98s by Sergio Perez in Hungary\n",
      "The average fastest pit stop was 2.16s\n",
      "Sergio Perez has had the fastest time the most (7 races), had an average fastest pit stop of 2.17s,\n",
      "winning in:\n",
      "Australia, Azerbaijan, Monaco, Spain, Canada, Hungary, Singapore\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "def pit_stop_stats(df):\n",
    "    team_counts = {}\n",
    "    driver_counts = {}\n",
    "    fastest_stop = float('inf')\n",
    "    fastest_stop_driver = \"\"\n",
    "    fastest_stop_gp = \"\"\n",
    "    \n",
    "    # Remove \"s\" from 'Fastest Stop' column\n",
    "    df['Fastest Stop'] = df['Fastest Stop'].str.replace('s', '').astype(float)\n",
    "\n",
    "    # Drop columns witb NaN values for 'Fastest Stop'\n",
    "    df = df.dropna(subset=['Fastest Stop'])\n",
    "\n",
    "    for index, row in df.iterrows():\n",
    "        gp, team, driver, time = row['Grand Prix'], row['Team'], row['Driver'], row['Fastest Stop']\n",
    "        if time:  # make sure time is not 'n/a'\n",
    "            team_counts[team] = team_counts.get(team, 0) + 1\n",
    "            driver_counts[driver] = driver_counts.get(driver, 0) + 1\n",
    "            \n",
    "            if time < fastest_stop:\n",
    "                fastest_stop = time\n",
    "                fastest_stop_driver = driver\n",
    "                fastest_stop_gp = gp\n",
    "\n",
    "    print(\"Teams with Most Fastest Stops:\")\n",
    "    for team, count in sorted(team_counts.items(), key=lambda x: x[1], reverse=True):\n",
    "        print(f\"- {team}: {count}\")\n",
    "\n",
    "    print(\"\\nDriver with Most Fastest Stops:\")\n",
    "    for driver, count in sorted(driver_counts.items(), key=lambda x: x[1], reverse=True):\n",
    "        print(f\"- {driver}: {count}\")\n",
    "\n",
    "    print(f\"\\nFastest Pit Stop:\\n- {fastest_stop}s by {fastest_stop_driver} in {fastest_stop_gp}\")\n",
    "    print(\"The average fastest pit stop was {:.2f}s\".format(df['Fastest Stop'].mean()))\n",
    "    print(\"{} has had the fastest time the most ({} races), had an average fastest pit stop of {:.2f}s,\".format(df['Driver'].mode()[0], df['Driver'].value_counts().max(), df[df['Driver'] == df['Driver'].mode()[0]]['Fastest Stop'].mean()))\n",
    "    print(\"winning in:\")\n",
    "    comma_sep = []\n",
    "    for gp in df[df['Driver'] == df['Driver'].mode()[0]]['Grand Prix']:\n",
    "        comma_sep.append(gp)\n",
    "    print(', '.join(comma_sep))\n",
    "\n",
    "    return df\n",
    "\n",
    "# Call the function\n",
    "\n",
    "df2 = pit_stop_stats(df2)\n",
    "\n"
   ]
  },
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          "Charles Leclerc",
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   ],
   "source": [
    "# plotly chart\n",
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "df2\n",
    "\n",
    "# Chart Pit Stop Box Plot for each driver, and put the number of fastest stops in data labels\n",
    "fig = px.box(df2, x='Driver', y='Fastest Stop', color='Driver', title='Pit Stop Times by Driver')\n",
    "fig.update_layout(xaxis_title='Driver', yaxis_title='Pit Stop Time (Sec)')\n",
    "# fig.update_traces(texttemplate='%{text:.2s}', textposition='outside', text=df2['Fastest Stop']) # Did you mean \"hovertemplate\"?\n",
    "# Add data labels\n",
    "# fig.update_traces(texttemplate='%{text:.2s}', textposition='outside', text=df2['Fastest Stop'])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ccscr\\AppData\\Local\\Temp\\ipykernel_46264\\1424501979.py:3: FutureWarning:\n",
      "\n",
      "The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "\n"
     ]
    },
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Driver</th>\n",
       "      <th>Grand Prix</th>\n",
       "      <th>Team</th>\n",
       "      <th>Fastest Stop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Carlos Sainz</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Driver  Grand Prix  Team  Fastest Stop\n",
       "0     Carlos Sainz           1     1             1\n",
       "1  Charles Leclerc           3     3             3\n",
       "2     Lando Norris           3     3             3\n",
       "3   Max Verstappen           1     1             1\n",
       "4     Sergio Perez           7     7             7"
      ]
     },
     "execution_count": 34,
     "metadata": {},
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   ],
   "source": [
    "# Create a dataframe with the average number of fastest stops per driver\n",
    "df3 = df2.groupby('Driver').count().reset_index()\n",
    "df3_mean = df2.groupby('Driver').mean().reset_index()\n",
    "# In df3_mean, rename 'Fastes Stop' to 'Average Fastest Stop'\n",
    "df3_mean = df3_mean.rename(columns={'Fastest Stop': 'Average Fastest Stop'})\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>Fastest Stop</th>\n",
       "      <th>Average Fastest Stop</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>2.420</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.165714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>2.450</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.010000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>2.500</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.153333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Oscar Piastri</td>\n",
       "      <td>2.520</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>2.520</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.170000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Carlos Sainz Jr.</td>\n",
       "      <td>2.652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Liam Lawson</td>\n",
       "      <td>2.652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>2.652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>2.720</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>2.752</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>2.820</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>2.852</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>2.920</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>George Russell</td>\n",
       "      <td>2.952</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Alexander Albon</td>\n",
       "      <td>3.130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Logan Sargeant</td>\n",
       "      <td>3.130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Kevin Magnussen</td>\n",
       "      <td>3.230</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Zhou Guanyu</td>\n",
       "      <td>3.253</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>3.330</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Nico Hulkenberg</td>\n",
       "      <td>3.553</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                name  score  Fastest Stop  Average Fastest Stop\n",
       "0       Sergio Perez  2.420           7.0              2.165714\n",
       "1     Max Verstappen  2.450           1.0              2.010000\n",
       "2       Lando Norris  2.500           3.0              2.153333\n",
       "3      Oscar Piastri  2.520           0.0                   NaN\n",
       "4    Charles Leclerc  2.520           3.0              2.170000\n",
       "5   Carlos Sainz Jr.  2.652           0.0                   NaN\n",
       "6        Liam Lawson  2.652           0.0                   NaN\n",
       "7       Esteban Ocon  2.652           0.0                   NaN\n",
       "8       Lance Stroll  2.720           0.0                   NaN\n",
       "9       Pierre Gasly  2.752           0.0                   NaN\n",
       "10   Fernando Alonso  2.820           0.0                   NaN\n",
       "11    Lewis Hamilton  2.852           0.0                   NaN\n",
       "12      Yuki Tsunoda  2.920           0.0                   NaN\n",
       "13    George Russell  2.952           0.0                   NaN\n",
       "14   Alexander Albon  3.130           0.0                   NaN\n",
       "15    Logan Sargeant  3.130           0.0                   NaN\n",
       "16   Kevin Magnussen  3.230           0.0                   NaN\n",
       "17       Zhou Guanyu  3.253           0.0                   NaN\n",
       "18   Valtteri Bottas  3.330           0.0                   NaN\n",
       "19   Nico Hulkenberg  3.553           0.0                   NaN"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Left join df.name on df3.Driver to get the 'Fastest Stop' column\n",
    "df4 = df.merge(df3[['Driver', 'Fastest Stop']], how='left', left_on='name', right_on='Driver')\n",
    "\n",
    "# Drop the 'Driver' column\n",
    "df4 = df4.drop('Driver', axis=1)\n",
    "\n",
    "# Do the same with df3_mean\n",
    "df4 = df4.merge(df3_mean[['Driver', 'Average Fastest Stop']], how='left', left_on='name', right_on='Driver')\n",
    "df4 = df4.drop('Driver', axis=1)\n",
    "\n",
    "# Fill Fastest Stop NaN values with 0\n",
    "df4['Fastest Stop'] = df4['Fastest Stop'].fillna(0)\n",
    "\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
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   "source": [
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   "source": [
    "# import go \n",
    "import plotly.graph_objects as go\n",
    "# Create combination chart\n",
    "fig = go.Figure()\n",
    "\n",
    "# Add bars for Fastest Stop\n",
    "fig.add_trace(go.Bar(\n",
    "    x=df['name'],\n",
    "    y=df['Fastest Stop'],\n",
    "    name='Number of Fastest Stops',\n",
    "    marker_color='green',\n",
    "    opacity=1,\n",
    "))\n",
    "# Add bars for Score (Japan GP - 1st Stop (O/U))\n",
    "fig.add_trace(go.Bar(\n",
    "    x=df['name'],\n",
    "    y=df['score'],\n",
    "    name='Japan GP - 1st Stop (O/U)',\n",
    "    # Use shades of blue to indicate score\n",
    "    marker_color=df['score'],\n",
    "    # set the market color scale to 'Blues'\n",
    "    marker=dict(colorscale='purples'),\n",
    "    yaxis='y2',\n",
    "    opacity=0.9,\n",
    "))\n",
    "\n",
    "\n",
    "# Add line for Average Fastest Stop\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=df['name'],\n",
    "    y=df['Average Fastest Stop'],\n",
    "    mode='lines+markers',\n",
    "    name='Average Fastest Stop',\n",
    "    line=dict(color='red', width=2.5),\n",
    "    yaxis='y2'  # Line on secondary y-axis\n",
    "))\n",
    "\n",
    "# Update layout for dual y-axes, grouped bars, and set range for y-axes\n",
    "fig.update_layout(\n",
    "    title=\"Japan GP - 1st Stop (O/U) + Fastest Stop Standings\",\n",
    "    xaxis_title=\"Driver\",\n",
    "    yaxis_title=\"Number of Fastest Stops\",\n",
    "    # yaxis=dict(range=[0, 3.5]),  # Adjust as necessary for your data\n",
    "    yaxis2=dict(title=\"Average Stop Time (Seconds)\", overlaying='y', side='right', range=[2, 3.5]),\n",
    "    barmode='group',\n",
    "    legend=dict(\n",
    "        orientation='h',\n",
    "        yanchor='bottom',\n",
    "        y=1.02,\n",
    "        xanchor='right',\n",
    "        x=1\n",
    "    )\n",
    ")\n",
    "\n",
    "\n",
    "# Make the plot less wide, and taller\n",
    "fig.update_layout(width=1000, height=600)\n",
    "# Show figure\n",
    "fig.show()\n",
    "\n",
    "# Write html file for posting to twitter\n",
    "fig.write_html('prizepicks2.html')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>Fastest Stop</th>\n",
       "      <th>Average Fastest Stop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sergio Perez</td>\n",
       "      <td>2.420</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.165714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Max Verstappen</td>\n",
       "      <td>2.450</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.010000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lando Norris</td>\n",
       "      <td>2.500</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.153333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Oscar Piastri</td>\n",
       "      <td>2.520</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Charles Leclerc</td>\n",
       "      <td>2.520</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.170000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Carlos Sainz Jr.</td>\n",
       "      <td>2.652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Liam Lawson</td>\n",
       "      <td>2.652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Esteban Ocon</td>\n",
       "      <td>2.652</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Lance Stroll</td>\n",
       "      <td>2.720</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Pierre Gasly</td>\n",
       "      <td>2.752</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Fernando Alonso</td>\n",
       "      <td>2.820</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Lewis Hamilton</td>\n",
       "      <td>2.852</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Yuki Tsunoda</td>\n",
       "      <td>2.920</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>George Russell</td>\n",
       "      <td>2.952</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Alexander Albon</td>\n",
       "      <td>3.130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Logan Sargeant</td>\n",
       "      <td>3.130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Kevin Magnussen</td>\n",
       "      <td>3.230</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Zhou Guanyu</td>\n",
       "      <td>3.253</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Valtteri Bottas</td>\n",
       "      <td>3.330</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Nico Hulkenberg</td>\n",
       "      <td>3.553</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "                name  score  Fastest Stop  Average Fastest Stop\n",
       "0       Sergio Perez  2.420           7.0              2.165714\n",
       "1     Max Verstappen  2.450           1.0              2.010000\n",
       "2       Lando Norris  2.500           3.0              2.153333\n",
       "3      Oscar Piastri  2.520           0.0                   NaN\n",
       "4    Charles Leclerc  2.520           3.0              2.170000\n",
       "5   Carlos Sainz Jr.  2.652           0.0                   NaN\n",
       "6        Liam Lawson  2.652           0.0                   NaN\n",
       "7       Esteban Ocon  2.652           0.0                   NaN\n",
       "8       Lance Stroll  2.720           0.0                   NaN\n",
       "9       Pierre Gasly  2.752           0.0                   NaN\n",
       "10   Fernando Alonso  2.820           0.0                   NaN\n",
       "11    Lewis Hamilton  2.852           0.0                   NaN\n",
       "12      Yuki Tsunoda  2.920           0.0                   NaN\n",
       "13    George Russell  2.952           0.0                   NaN\n",
       "14   Alexander Albon  3.130           0.0                   NaN\n",
       "15    Logan Sargeant  3.130           0.0                   NaN\n",
       "16   Kevin Magnussen  3.230           0.0                   NaN\n",
       "17       Zhou Guanyu  3.253           0.0                   NaN\n",
       "18   Valtteri Bottas  3.330           0.0                   NaN\n",
       "19   Nico Hulkenberg  3.553           0.0                   NaN"
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           "line": {
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          },
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           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
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            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
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           "bgcolor": "#E5ECF6",
           "caxis": {
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            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
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           "ticks": "",
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           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
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           "ticks": "",
           "title": {
            "standoff": 15
           },
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         }
        },
        "title": {
         "text": "Japan GP - 1st Stop (O/U) vs. Fastest Stop Standings"
        },
        "xaxis": {
         "gridcolor": "#F5F5F5",
         "gridwidth": 2,
         "linecolor": "#E5E5E5",
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          "text": "Driver"
         },
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         "zerolinewidth": 0
        },
        "yaxis": {
         "gridcolor": "#F5F5F5",
         "gridwidth": 2,
         "linecolor": "#E5E5E5",
         "title": {
          "text": "Number of Fastest Stops"
         },
         "zerolinecolor": "#979797",
         "zerolinewidth": 1
        },
        "yaxis2": {
         "overlaying": "y",
         "range": [
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         "side": "right",
         "title": {
          "text": "Stop Time (s)"
         }
        }
       }
      }
     },
     "metadata": {},
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   ],
   "source": [
    "# Create combination chart\n",
    "fig = go.Figure()\n",
    "\n",
    "# Updated Color Palette\n",
    "colors = {\n",
    "    \"bars1\": \"#2E91E5\",  # Light blue\n",
    "    \"bars2\": \"#E15F99\",  # Pinkish\n",
    "    \"line\": \"#1CA71C\"    # Dark green\n",
    "}\n",
    "\n",
    "# Add bars for Fastest Stop\n",
    "fig.add_trace(go.Bar(\n",
    "    x=df['name'],\n",
    "    y=df['Fastest Stop'],\n",
    "    name='Number of Fastest Stops',\n",
    "    marker_color=colors[\"bars1\"],\n",
    "    opacity=0.7  # Adding some opacity\n",
    "))\n",
    "\n",
    "# Add bars for Score (Japan GP - 1st Stop (O/U))\n",
    "fig.add_trace(go.Bar(\n",
    "    x=df['name'],\n",
    "    y=df['score'],\n",
    "    name='Japan GP - 1st Stop (O/U)',\n",
    "    marker_color=colors[\"bars2\"],\n",
    "    yaxis='y2',\n",
    "    opacity=0.7  # Adding some opacity\n",
    "))\n",
    "\n",
    "# Add line for Average Fastest Stop\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=df['name'],\n",
    "    y=df['Average Fastest Stop'],\n",
    "    mode='lines+markers',\n",
    "    name='Average Fastest Stop',\n",
    "    line=dict(color=colors[\"line\"], width=2.5),\n",
    "    yaxis='y2'  # Line on secondary y-axis\n",
    "))\n",
    "\n",
    "# Update layout for dual y-axes, grouped bars, and set range for y-axes\n",
    "fig.update_layout(\n",
    "    title=\"Japan GP - 1st Stop (O/U) vs. Fastest Stop Standings\",\n",
    "    xaxis_title=\"Driver\",\n",
    "    yaxis_title=\"Number of Fastest Stops\",\n",
    "    yaxis2=dict(title=\"Stop Time (s)\", overlaying='y', side='right', range=[2, 3.5]),\n",
    "    barmode='group',\n",
    "    legend=dict(\n",
    "        orientation='h',\n",
    "        yanchor='bottom',\n",
    "        y=1.02,\n",
    "        xanchor='right',\n",
    "        x=1\n",
    "    ),\n",
    "    font=dict(\n",
    "        family=\"Arial, sans-serif\",  # Consistent font\n",
    "        size=12,\n",
    "        color=\"#7f7f7f\"  # Greyish tone\n",
    "    ),\n",
    "    plot_bgcolor=\"white\",  # White background\n",
    "    paper_bgcolor=\"white\",\n",
    "    xaxis=dict(\n",
    "        gridcolor=\"#F5F5F5\",  # Light grey grid lines\n",
    "        gridwidth=2,\n",
    "        zerolinewidth=0,\n",
    "        zerolinecolor=\"#979797\",  # Grey zero line\n",
    "        linecolor=\"#E5E5E5\"  # Grey axis line\n",
    "    ),\n",
    "    yaxis=dict(\n",
    "        gridcolor=\"#F5F5F5\",\n",
    "        gridwidth=2,\n",
    "        zerolinewidth=1,\n",
    "        zerolinecolor=\"#979797\",\n",
    "        linecolor=\"#E5E5E5\"\n",
    "    )\n",
    ")\n",
    "\n",
    "# Show figure\n",
    "fig.show()\n"
   ]
  }
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