diff --git "a/live_data/analysis_of_markets_data.ipynb" "b/live_data/analysis_of_markets_data.ipynb"
new file mode 100644--- /dev/null
+++ "b/live_data/analysis_of_markets_data.ipynb"
@@ -0,0 +1,1040 @@
+{
+ "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": [
+    {
+     "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>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",
+       "      <td>1721960955</td>\n",
+       "      <td>0x043c1634e14ab83238c8c6a1309788c3aca784e5</td>\n",
+       "      <td>6279485274437737553</td>\n",
+       "      <td>7000000000000000010</td>\n",
+       "      <td>1722384000</td>\n",
+       "      <td>[11251336507351233310, 4355038174174694575]</td>\n",
+       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
+       "      <td>Will Conns HomePlus close more than 70 stores ...</td>\n",
+       "      <td>1722268929</td>\n",
+       "      <td>True</td>\n",
+       "      <td>72.09</td>\n",
+       "      <td>27.91</td>\n",
+       "      <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",
+       "      <td>0</td>\n",
+       "      <td>1722297600</td>\n",
+       "      <td>[0, 0]</td>\n",
+       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
+       "      <td>Will the missing plane in Alaska be found by 2...</td>\n",
+       "      <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",
+       "      <td>6095321493080794870</td>\n",
+       "      <td>7000000000000000003</td>\n",
+       "      <td>1722470400</td>\n",
+       "      <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",
+       "      <td>6858450807323054238</td>\n",
+       "      <td>7000000000000000002</td>\n",
+       "      <td>1722556800</td>\n",
+       "      <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",
+       "1722643200    10\n",
+       "1767225600     1\n",
+       "1730502000     1\n",
+       "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": {
+      "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>votes_first_outcome_perc</th>\n",
+       "      <th>votes_second_outcome_perc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>1722038975</td>\n",
+       "      <td>0xe4d078b9be12319c0063f58dc10f19604a5df163</td>\n",
+       "      <td>6868403098642120683</td>\n",
+       "      <td>7000000000000000002</td>\n",
+       "      <td>1722470400</td>\n",
+       "      <td>[8510941937601870124, 5757294593153662167]</td>\n",
+       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
+       "      <td>Will the George Floyd Justice in Policing Act ...</td>\n",
+       "      <td>1722268929</td>\n",
+       "      <td>True</td>\n",
+       "      <td>59.65</td>\n",
+       "      <td>40.35</td>\n",
+       "      <td>30.00</td>\n",
+       "      <td>70.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>1722221950</td>\n",
+       "      <td>0xe67bb5f7355c5383db4ca3d04496dbc5258fe4f0</td>\n",
+       "      <td>6126294842535304016</td>\n",
+       "      <td>7000000000000000002</td>\n",
+       "      <td>1722643200</td>\n",
+       "      <td>[4128819631808010336, 11867798637293074830]</td>\n",
+       "      <td>{'answers': [], 'currentAnswerTimestamp': None...</td>\n",
+       "      <td>Will HP release a new AI software or hardware ...</td>\n",
+       "      <td>1722268929</td>\n",
+       "      <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",
+       "      <td>1690321980</td>\n",
+       "      <td>0xe7ed8a5f2f0f17f7d584ae8ddd0592d1ac67791f</td>\n",
+       "      <td>1999600120148065</td>\n",
+       "      <td>10000000000001930</td>\n",
+       "      <td>1730502000</td>\n",
+       "      <td>[1009999000296889, 99009998990735258]</td>\n",
+       "      <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",
+       "      <td>7000000000000000004</td>\n",
+       "      <td>1722643200</td>\n",
+       "      <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",
+       "      <td>5894516319320961420</td>\n",
+       "      <td>7000000000000000003</td>\n",
+       "      <td>1722470400</td>\n",
+       "      <td>[3829193421170799405, 12796428545262137507]</td>\n",
+       "      <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",
+       "</div>"
+      ],
+      "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
+}