diff --git "a/live_data/analysis_of_markets_data.ipynb" "b/live_data/analysis_of_markets_data.ipynb"
deleted file mode 100644--- "a/live_data/analysis_of_markets_data.ipynb"
+++ /dev/null
@@ -1,1040 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import matplotlib.pyplot as plt\n",
-    "import seaborn as sns\n",
-    "import gc"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 77,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "old_fpmms = pd.read_parquet('./markets_live_data_old.parquet')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 83,
-   "metadata": {},
-   "outputs": [
-    {
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-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>creationTimestamp</th>\n",
-       "      <th>id</th>\n",
-       "      <th>liquidityMeasure</th>\n",
-       "      <th>liquidityParameter</th>\n",
-       "      <th>openingTimestamp</th>\n",
-       "      <th>outcomeTokenAmounts</th>\n",
-       "      <th>question</th>\n",
-       "      <th>title</th>\n",
-       "      <th>tokens_timestamp</th>\n",
-       "      <th>open</th>\n",
-       "      <th>first_token_perc</th>\n",
-       "      <th>second_token_perc</th>\n",
-       "      <th>votes_first_outcome_perc</th>\n",
-       "      <th>votes_second_outcome_perc</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
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-       "      <td>45.95</td>\n",
-       "      <td>54.05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1721871925</td>\n",
-       "      <td>0x0682e2988497bcad4c0a60b20c06af2425ad1d1e</td>\n",
-       "      <td>0</td>\n",
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-       "      <td>1722268929</td>\n",
-       "      <td>True</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>55.41</td>\n",
-       "      <td>44.59</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1722045065</td>\n",
-       "      <td>0x17f2c97bf52a79671878201bf2995a3b6daba041</td>\n",
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-       "      <td>[11991768897697257799, 4086136117033519393]</td>\n",
-       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
-       "      <td>Will Apple Maps surpass Google Maps in terms o...</td>\n",
-       "      <td>1722268929</td>\n",
-       "      <td>True</td>\n",
-       "      <td>74.59</td>\n",
-       "      <td>25.41</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>100.00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1722127095</td>\n",
-       "      <td>0x18386924426f7c8ab7f5db4ad586c12dac5cd5e3</td>\n",
-       "      <td>6563087300183711249</td>\n",
-       "      <td>7000000000000000003</td>\n",
-       "      <td>1722556800</td>\n",
-       "      <td>[4869629170878169903, 10062367847850626262]</td>\n",
-       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
-       "      <td>Will the new AI-powered upgrade for the Philip...</td>\n",
-       "      <td>1722268929</td>\n",
-       "      <td>True</td>\n",
-       "      <td>32.61</td>\n",
-       "      <td>67.39</td>\n",
-       "      <td>66.67</td>\n",
-       "      <td>33.33</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1722133525</td>\n",
-       "      <td>0x1f0f1fd3fcb3b49eeeb6197abcb5c44c1907dfbd</td>\n",
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-       "      <td>[5714974221256982642, 8573966933699076673]</td>\n",
-       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
-       "      <td>Will Harvey Weinstein recover from Covid-19 an...</td>\n",
-       "      <td>1722268929</td>\n",
-       "      <td>True</td>\n",
-       "      <td>40.00</td>\n",
-       "      <td>60.00</td>\n",
-       "      <td>72.73</td>\n",
-       "      <td>27.27</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "  creationTimestamp                                          id  \\\n",
-       "0        1721960955  0x043c1634e14ab83238c8c6a1309788c3aca784e5   \n",
-       "1        1721871925  0x0682e2988497bcad4c0a60b20c06af2425ad1d1e   \n",
-       "2        1722045065  0x17f2c97bf52a79671878201bf2995a3b6daba041   \n",
-       "3        1722127095  0x18386924426f7c8ab7f5db4ad586c12dac5cd5e3   \n",
-       "4        1722133525  0x1f0f1fd3fcb3b49eeeb6197abcb5c44c1907dfbd   \n",
-       "\n",
-       "      liquidityMeasure   liquidityParameter openingTimestamp  \\\n",
-       "0  6279485274437737553  7000000000000000010       1722384000   \n",
-       "1                    0                    0       1722297600   \n",
-       "2  6095321493080794870  7000000000000000003       1722470400   \n",
-       "3  6563087300183711249  7000000000000000003       1722556800   \n",
-       "4  6858450807323054238  7000000000000000002       1722556800   \n",
-       "\n",
-       "                           outcomeTokenAmounts  \\\n",
-       "0  [11251336507351233310, 4355038174174694575]   \n",
-       "1                                       [0, 0]   \n",
-       "2  [11991768897697257799, 4086136117033519393]   \n",
-       "3  [4869629170878169903, 10062367847850626262]   \n",
-       "4   [5714974221256982642, 8573966933699076673]   \n",
-       "\n",
-       "                                            question  \\\n",
-       "0  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "1  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "2  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "3  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "4  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "\n",
-       "                                               title  tokens_timestamp  open  \\\n",
-       "0  Will Conns HomePlus close more than 70 stores ...        1722268929  True   \n",
-       "1  Will the missing plane in Alaska be found by 2...        1722268929  True   \n",
-       "2  Will Apple Maps surpass Google Maps in terms o...        1722268929  True   \n",
-       "3  Will the new AI-powered upgrade for the Philip...        1722268929  True   \n",
-       "4  Will Harvey Weinstein recover from Covid-19 an...        1722268929  True   \n",
-       "\n",
-       "   first_token_perc  second_token_perc  votes_first_outcome_perc  \\\n",
-       "0             72.09              27.91                     45.95   \n",
-       "1              0.00               0.00                     55.41   \n",
-       "2             74.59              25.41                      0.00   \n",
-       "3             32.61              67.39                     66.67   \n",
-       "4             40.00              60.00                     72.73   \n",
-       "\n",
-       "   votes_second_outcome_perc  \n",
-       "0                      54.05  \n",
-       "1                      44.59  \n",
-       "2                     100.00  \n",
-       "3                      33.33  \n",
-       "4                      27.27  "
-      ]
-     },
-     "execution_count": 83,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "live_fpmms = pd.read_parquet('./markets_live_data.parquet')\n",
-    "live_fpmms.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 84,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "openingTimestamp\n",
-       "1722384000    10\n",
-       "1722297600    10\n",
-       "1722470400    10\n",
-       "1722556800    10\n",
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-       "Name: count, dtype: int64"
-      ]
-     },
-     "execution_count": 84,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "live_fpmms.openingTimestamp.value_counts()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 85,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "      <th></th>\n",
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-       "      <th>votes_second_outcome_perc</th>\n",
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-       "      <td>True</td>\n",
-       "      <td>25.81</td>\n",
-       "      <td>74.19</td>\n",
-       "      <td>100.00</td>\n",
-       "      <td>0.00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>49</th>\n",
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-       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
-       "      <td>Will Twitter implement a new misinformation po...</td>\n",
-       "      <td>1722268929</td>\n",
-       "      <td>True</td>\n",
-       "      <td>1.01</td>\n",
-       "      <td>98.99</td>\n",
-       "      <td>60.71</td>\n",
-       "      <td>39.29</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50</th>\n",
-       "      <td>1722223250</td>\n",
-       "      <td>0xf2d66476f8c4b9e7a5401bf3e777ddb54f83b597</td>\n",
-       "      <td>6408885494720959939</td>\n",
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-       "      <td>[4570617012444494780, 10720653221783161222]</td>\n",
-       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
-       "      <td>Will Intel release a patch to fix the instabil...</td>\n",
-       "      <td>1722268929</td>\n",
-       "      <td>True</td>\n",
-       "      <td>29.89</td>\n",
-       "      <td>70.11</td>\n",
-       "      <td>90.91</td>\n",
-       "      <td>9.09</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>51</th>\n",
-       "      <td>1722043025</td>\n",
-       "      <td>0xf7d0728752d98c5506d0add8ae72f8acd23d3daa</td>\n",
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-       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
-       "      <td>Will Microsoft fix the bug in the Windows 11's...</td>\n",
-       "      <td>1722268929</td>\n",
-       "      <td>True</td>\n",
-       "      <td>23.03</td>\n",
-       "      <td>76.97</td>\n",
-       "      <td>100.00</td>\n",
-       "      <td>0.00</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
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-      "text/plain": [
-       "   creationTimestamp                                          id  \\\n",
-       "47        1722038975  0xe4d078b9be12319c0063f58dc10f19604a5df163   \n",
-       "48        1722221950  0xe67bb5f7355c5383db4ca3d04496dbc5258fe4f0   \n",
-       "49        1690321980  0xe7ed8a5f2f0f17f7d584ae8ddd0592d1ac67791f   \n",
-       "50        1722223250  0xf2d66476f8c4b9e7a5401bf3e777ddb54f83b597   \n",
-       "51        1722043025  0xf7d0728752d98c5506d0add8ae72f8acd23d3daa   \n",
-       "\n",
-       "       liquidityMeasure   liquidityParameter openingTimestamp  \\\n",
-       "47  6868403098642120683  7000000000000000002       1722470400   \n",
-       "48  6126294842535304016  7000000000000000002       1722643200   \n",
-       "49     1999600120148065    10000000000001930       1730502000   \n",
-       "50  6408885494720959939  7000000000000000004       1722643200   \n",
-       "51  5894516319320961420  7000000000000000003       1722470400   \n",
-       "\n",
-       "                            outcomeTokenAmounts  \\\n",
-       "47   [8510941937601870124, 5757294593153662167]   \n",
-       "48  [4128819631808010336, 11867798637293074830]   \n",
-       "49        [1009999000296889, 99009998990735258]   \n",
-       "50  [4570617012444494780, 10720653221783161222]   \n",
-       "51  [3829193421170799405, 12796428545262137507]   \n",
-       "\n",
-       "                                             question  \\\n",
-       "47  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "48  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "49  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "50  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "51  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "\n",
-       "                                                title  tokens_timestamp  open  \\\n",
-       "47  Will the George Floyd Justice in Policing Act ...        1722268929  True   \n",
-       "48  Will HP release a new AI software or hardware ...        1722268929  True   \n",
-       "49  Will Twitter implement a new misinformation po...        1722268929  True   \n",
-       "50  Will Intel release a patch to fix the instabil...        1722268929  True   \n",
-       "51  Will Microsoft fix the bug in the Windows 11's...        1722268929  True   \n",
-       "\n",
-       "    first_token_perc  second_token_perc  votes_first_outcome_perc  \\\n",
-       "47             59.65              40.35                     30.00   \n",
-       "48             25.81              74.19                    100.00   \n",
-       "49              1.01              98.99                     60.71   \n",
-       "50             29.89              70.11                     90.91   \n",
-       "51             23.03              76.97                    100.00   \n",
-       "\n",
-       "    votes_second_outcome_perc  \n",
-       "47                      70.00  \n",
-       "48                       0.00  \n",
-       "49                      39.29  \n",
-       "50                       9.09  \n",
-       "51                       0.00  "
-      ]
-     },
-     "execution_count": 85,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "live_fpmms.tail()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 86,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 52 entries, 0 to 51\n",
-      "Data columns (total 14 columns):\n",
-      " #   Column                     Non-Null Count  Dtype  \n",
-      "---  ------                     --------------  -----  \n",
-      " 0   creationTimestamp          52 non-null     object \n",
-      " 1   id                         52 non-null     object \n",
-      " 2   liquidityMeasure           52 non-null     object \n",
-      " 3   liquidityParameter         52 non-null     object \n",
-      " 4   openingTimestamp           52 non-null     object \n",
-      " 5   outcomeTokenAmounts        52 non-null     object \n",
-      " 6   question                   52 non-null     object \n",
-      " 7   title                      52 non-null     object \n",
-      " 8   tokens_timestamp           52 non-null     int64  \n",
-      " 9   open                       52 non-null     bool   \n",
-      " 10  first_token_perc           52 non-null     float64\n",
-      " 11  second_token_perc          52 non-null     float64\n",
-      " 12  votes_first_outcome_perc   52 non-null     float64\n",
-      " 13  votes_second_outcome_perc  52 non-null     float64\n",
-      "dtypes: bool(1), float64(4), int64(1), object(8)\n",
-      "memory usage: 5.5+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "live_fpmms.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 87,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "count     52.000000\n",
-       "mean      51.236346\n",
-       "std       27.848295\n",
-       "min        0.000000\n",
-       "25%       39.467500\n",
-       "50%       54.610000\n",
-       "75%       69.525000\n",
-       "max      100.000000\n",
-       "Name: votes_first_outcome_perc, dtype: float64"
-      ]
-     },
-     "execution_count": 87,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "live_fpmms.votes_first_outcome_perc.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 89,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "count     52.000000\n",
-       "mean      46.840577\n",
-       "std       27.693111\n",
-       "min        0.000000\n",
-       "25%       28.372500\n",
-       "50%       44.905000\n",
-       "75%       58.230000\n",
-       "max      100.000000\n",
-       "Name: votes_second_outcome_perc, dtype: float64"
-      ]
-     },
-     "execution_count": 89,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "live_fpmms.votes_second_outcome_perc.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 75,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      " title = Will Conns HomePlus close more than 70 stores by 30 July 2024?\n",
-      " title = Will the missing plane in Alaska be found by 29 July 2024?\n",
-      " title = Will Apple Maps surpass Google Maps in terms of users by 31 July 2024?\n",
-      " title = Will the new AI-powered upgrade for the Philips Hue camera be released by 1 August 2024?\n",
-      " title = Will Harvey Weinstein recover from Covid-19 and double pneumonia by August 1, 2024?\n",
-      " title = Will Roku successfully introduce Instagram-style shoppable ads on its platform by 30 July 2024?\n",
-      " title = Will the Google Pixel 9 and Pixel 9 Pro be released by 29th July 2024?\n",
-      " title = Will Southwest Airlines start assigning seats and premium seating by 31st July 2024?\n",
-      " title = Will Tesla's net income increase in the third quarter of 2024?\n",
-      " title = Will the wildfire in California be under control on or by 1 August 2024?\n",
-      " title = Will the Disney Plus, Hulu, and Max streaming bundle surpass 50 million subscribers on or before 31 July 2024?\n",
-      " title = Will Aston Martin officially announce their return to Le Mans in 2025 on 29 July 2024?\n",
-      " title = Will the Disney Plus, Hulu, and Max streaming bundle surpass 5 million subscribers by 2nd August 2024?\n",
-      " title = Will the population of Florida exceed 23 million by 29 July 2024?\n",
-      " title = Will non-binary athletes win any medals at the Paris Olympics on 1 August 2024?\n",
-      " title = Will Call of Duty: Modern Warfare III be available on Xbox Game Pass by 29 July 2024?\n",
-      " title = Will Netflix launch a new game under the leadership of the new gaming boss, Alain Tascan, by 29 July 2024?\n",
-      " title = Will OpenAI's SearchGPT be launched fully on or before 31 July 2024?\n",
-      " title = Will the Kids Online Safety Act be passed by Congress by 1 August 2024?\n",
-      " title = Will the G7 framework deal on a $50 billion Ukraine loan be completed by 31 July 2024?\n",
-      " title = Will Kamala Harris secure the 2024 Democratic presidential nomination on 30 July 2024?\n",
-      " title = Will the Paris Olympics occur without any major security concerns on 2 August 2024?\n",
-      " title = Will Apple's launch of Maps on the web surpass Google Maps in user count by August 1, 2024?\n",
-      " title = Will Microsoft implement the proposed changes to Windows by 1 August 2024?\n",
-      " title = Will a new bill to protect illegal immigrants from deportation, cosponsored by Kamala Harris, be passed on or before 31 July 2024?\n",
-      " title = Will US GDP growth exceed 2.8% in the third quarter of 2024?\n",
-      " title = Will Andy Murray retire from tennis after the 2024 Paris Olympics?\n",
-      " title = Will Christopher Dunn be released from prison by 30 July 2024?\n",
-      " title = Will the US Olympic Committee win the lawsuit against Logan Paul's Prime energy drink for copyright violation claims by 30th July 2024?\n",
-      " title = Will Russia increase its naval visits to Cuba by 2 August 2024?\n",
-      " title = Will the death toll from the Ethiopian landslides exceed 500 by 30 July 2024?\n",
-      " title = Will 'Hillbilly Elegy' by VP candidate JD Vance be in the top 10 bestsellers on 2 August 2024?\n",
-      " title = Will Microsoft introduce taskbar-related changes to Windows 11 by 2 August 2024?\n",
-      " title = Will the US operation succeed in capturing all Sinaloa cartel leaders by August 1, 2024?\n",
-      " title = Will the Boeing capsule return the two NASA astronauts from the International Space Station on or before 31 July 2024?\n",
-      " title = Will Kamala Harris win the 2024 presidential election on 29 July 2024?\n",
-      " title = Will there be another eruption at Yellowstone on 30 July 2024?\n",
-      " title = Will the Google Pixel 9 series be launched by 31st July 2024?\n",
-      " title = Will TSMC start 4-nanometer chip production in its Phoenix, Arizona factory by the end of 2025?\n",
-      " title = Will the Park Fire in California be fully contained on or by 2 August 2024?\n",
-      " title = Will Arsenal sign Riccardo Calafiori by 29th July 2024?\n",
-      " title = Will Hungary host the EU's foreign and defense ministers' meeting by 29 July 2024?\n",
-      " title = Will the 2024 Paris Olympics be considered the most sustainable Olympic Games ever on 30 July 2024?\n",
-      " title = Will the conflict in Ukraine escalate further with the use of drones by 30 July 2024?\n",
-      " title = Will Pep Guardiola announce his extension with Manchester City on 1 August 2024?\n",
-      " title = Will Kamala Harris beat Donald Trump in the 2024 Presidential Elections?\n",
-      " title = Will a solar-powered car break the Cannonball Run record by 2nd August 2024?\n",
-      " title = Will the George Floyd Justice in Policing Act be passed by 31st July 2024?\n",
-      " title = Will HP release a new AI software or hardware on or before August 2, 2024?\n",
-      " title = Will Twitter implement a new misinformation policy before the 2024 elections?\n",
-      " title = Will Intel release a patch to fix the instability problems with 14th-gen and 13th-gen CPUs on or by 2 August 2024?\n",
-      " title = Will Microsoft fix the bug in the Windows 11's July cumulative update by 31 July 2024?\n"
-     ]
-    }
-   ],
-   "source": [
-    "for i in range(len(live_fpmms)):\n",
-    "    print(f\" title = {live_fpmms.iloc[i][\"title\"]}\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 76,
-   "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>creationTimestamp</th>\n",
-       "      <th>id</th>\n",
-       "      <th>liquidityMeasure</th>\n",
-       "      <th>liquidityParameter</th>\n",
-       "      <th>openingTimestamp</th>\n",
-       "      <th>outcomeTokenAmounts</th>\n",
-       "      <th>question</th>\n",
-       "      <th>title</th>\n",
-       "      <th>tokens_timestamp</th>\n",
-       "      <th>open</th>\n",
-       "      <th>first_token_perc</th>\n",
-       "      <th>second_token_perc</th>\n",
-       "      <th>market_id</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>1722221300</td>\n",
-       "      <td>0x5470db6b2c2413c9d5018b29da6f6855cb43e2d8</td>\n",
-       "      <td>6894859094417068722</td>\n",
-       "      <td>7000000000000000002</td>\n",
-       "      <td>1722643200</td>\n",
-       "      <td>[5879628341375273143, 8333860093704267379]</td>\n",
-       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
-       "      <td>Will the Disney Plus, Hulu, and Max streaming ...</td>\n",
-       "      <td>1722265929</td>\n",
-       "      <td>True</td>\n",
-       "      <td>41.37</td>\n",
-       "      <td>58.63</td>\n",
-       "      <td>12</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   creationTimestamp                                          id  \\\n",
-       "12        1722221300  0x5470db6b2c2413c9d5018b29da6f6855cb43e2d8   \n",
-       "\n",
-       "       liquidityMeasure   liquidityParameter openingTimestamp  \\\n",
-       "12  6894859094417068722  7000000000000000002       1722643200   \n",
-       "\n",
-       "                           outcomeTokenAmounts  \\\n",
-       "12  [5879628341375273143, 8333860093704267379]   \n",
-       "\n",
-       "                                             question  \\\n",
-       "12  {'answers': [], 'currentAnswerTimestamp': None...   \n",
-       "\n",
-       "                                                title  tokens_timestamp  open  \\\n",
-       "12  Will the Disney Plus, Hulu, and Max streaming ...        1722265929  True   \n",
-       "\n",
-       "    first_token_perc  second_token_perc  market_id  \n",
-       "12             41.37              58.63         12  "
-      ]
-     },
-     "execution_count": 76,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "live_fpmms.loc[live_fpmms[\"title\"]==\"Will the Disney Plus, Hulu, and Max streaming bundle surpass 5 million subscribers by 2nd August 2024?\"]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Too long id let's create a new market_id"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "live_fpmms[\"market_id\"] = live_fpmms.groupby([\"id\"]).ngroup()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'0'"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "live_fpmms.outcomeTokenAmounts[0][0]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# TODO Paint a bigger stacked barplot with the percentages"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 74,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x30bd851c0>"
-      ]
-     },
-     "execution_count": 74,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "\n",
-    "ax = live_fpmms.plot(x=\"market_id\", y=[\"first_token_perc\", \"second_token_perc\"], kind=\"bar\", rot=0, stacked=True)\n",
-    "ax.legend(bbox_to_anchor=(1, 1.02), loc='upper left')\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 65,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 2000x1500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Initialize the matplotlib figure\n",
-    "f, ax = plt.subplots(figsize=(20, 15))\n",
-    "\n",
-    "only_tokens = selected_fpmms[[\"market_id\", \"first_token_perc\", \"second_token_perc\"]]\n",
-    "# Plot the first token\n",
-    "sns.set_color_codes(\"pastel\")\n",
-    "sns.barplot(y=\"first_token_perc\", x=\"market_id\", data=only_tokens,\n",
-    "            label=\"First token perc\", color=\"b\")\n",
-    "\n",
-    "# Plot the second token\n",
-    "sns.set_color_codes(\"muted\")\n",
-    "sns.barplot(y=\"second_token_perc\", x=\"market_id\", data=only_tokens,\n",
-    "            label=\"Second token perc\", color=\"b\")\n",
-    "\n",
-    "# Add a legend and informative axis label\n",
-    "ax.legend(ncol=2, loc=\"lower right\", frameon=True)\n",
-    "ax.set(xlim=(0, 62), ylabel=\"Percentages of outcome tokens\",\n",
-    "       xlabel=\"Market id\")\n",
-    "sns.despine(left=True, bottom=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "count     63\n",
-       "unique    43\n",
-       "top        0\n",
-       "freq      21\n",
-       "Name: total_tokens, dtype: int64"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "old_fpmms.total_tokens.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x12fe32960>"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 500x500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sns.displot(old_fpmms, x=\"total_tokens\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 52,
-   "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>market_id</th>\n",
-       "      <th>token</th>\n",
-       "      <th>amounts</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0</td>\n",
-       "      <td>token_first_amount</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1</td>\n",
-       "      <td>token_first_amount</td>\n",
-       "      <td>6767700181775398163</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>2</td>\n",
-       "      <td>token_first_amount</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>3</td>\n",
-       "      <td>token_first_amount</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4</td>\n",
-       "      <td>token_first_amount</td>\n",
-       "      <td>7582886067296150575</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   market_id               token              amounts\n",
-       "0          0  token_first_amount                    0\n",
-       "1          1  token_first_amount  6767700181775398163\n",
-       "2          2  token_first_amount                    0\n",
-       "3          3  token_first_amount                    0\n",
-       "4          4  token_first_amount  7582886067296150575"
-      ]
-     },
-     "execution_count": 52,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "token_distributions = live_fpmms[[\"market_id\", \"token_first_amount\", \"token_second_amount\"]].melt('market_id', var_name='token', value_name='amounts')\n",
-    "token_distributions.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 60,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: xlabel='market_id', ylabel='amounts'>"
-      ]
-     },
-     "execution_count": 60,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sns.barplot(token_distributions, x=\"market_id\", y=\"amounts\", hue=\"token\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 2000x1500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Initialize the matplotlib figure\n",
-    "f, ax = plt.subplots(figsize=(20, 15))\n",
-    "\n",
-    "only_tokens = live_fpmms[[\"market_id\", \"token_first_amount\", \"token_second_amount\"]]\n",
-    "# Plot the first token\n",
-    "sns.set_color_codes(\"pastel\")\n",
-    "sns.barplot(y=\"token_first_amount\", x=\"market_id\", data=only_tokens,\n",
-    "            label=\"First token\", color=\"b\")\n",
-    "\n",
-    "# Plot the second token\n",
-    "sns.set_color_codes(\"muted\")\n",
-    "sns.barplot(y=\"token_second_amount\", x=\"market_id\", data=only_tokens,\n",
-    "            label=\"Second token\", color=\"b\")\n",
-    "\n",
-    "# Add a legend and informative axis label\n",
-    "ax.legend(ncol=2, loc=\"lower right\", frameon=True)\n",
-    "ax.set(xlim=(0, 62), ylabel=\"Amount of outcome tokens\",\n",
-    "       xlabel=\"Market id\")\n",
-    "sns.despine(left=True, bottom=True)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Preparing a timeseries (WIP)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "hf_dashboards",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}