{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "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": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "unknown_traders = pd.read_parquet(\"../data/unknown_traders.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "old_unknown_traders = pd.read_parquet(\"../data/old_unknown_traders.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['trader_address', 'market_creator', 'trade_id', 'creation_timestamp',\n",
       "       'title', 'market_status', 'collateral_amount', 'outcome_index',\n",
       "       'trade_fee_amount', 'outcomes_tokens_traded', 'current_answer',\n",
       "       'is_invalid', 'winning_trade', 'earnings', 'redeemed',\n",
       "       'redeemed_amount', 'num_mech_calls', 'mech_fee_amount', 'net_earnings',\n",
       "       'roi', 'staking', 'nr_mech_calls'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unknown_traders.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2025-01-11 02:06:25+0000', tz='UTC')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(unknown_traders.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-12-01 12:55:00+0000', tz='UTC')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(unknown_traders.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-12-14 03:18:30+0000', tz='UTC')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(old_unknown_traders.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-10-13 00:01:10+0000', tz='UTC')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(old_unknown_traders.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime, timezone\n",
    "def transform_to_datetime(x):\n",
    "    return datetime.fromtimestamp(int(x), tz=timezone.utc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_creation_date(df):\n",
    "    try:\n",
    "        df[\"creationTimestamp\"] = df[\"creationTimestamp\"].apply(\n",
    "            lambda x: transform_to_datetime(x)\n",
    "        )\n",
    "        df[\"creation_timestamp\"] = pd.to_datetime(df[\"creationTimestamp\"])\n",
    "    except Exception:\n",
    "        print(\"Ignore\")\n",
    "    \n",
    "    df[\"creation_date\"] = df[\"creation_timestamp\"].dt.date\n",
    "    df[\"creation_date\"] = pd.to_datetime(df[\"creation_date\"])\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ignore\n"
     ]
    }
   ],
   "source": [
    "old_unknown_traders = add_creation_date(old_unknown_traders)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ignore\n"
     ]
    }
   ],
   "source": [
    "unknown_traders = add_creation_date(unknown_traders)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/gp/02mb1d514ng739czlxw1lhh00000gn/T/ipykernel_6876/1622588175.py:2: UserWarning: Converting to PeriodArray/Index representation will drop timezone information.\n",
      "  pd.to_datetime(unknown_traders[\"creation_timestamp\"]).dt.to_period(\"W\").dt.strftime(\"%b-%d-%Y\")\n"
     ]
    }
   ],
   "source": [
    "unknown_traders[\"month_year_week\"] =(\n",
    "        pd.to_datetime(unknown_traders[\"creation_timestamp\"]).dt.to_period(\"W\").dt.strftime(\"%b-%d-%Y\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>trader_address</th>\n",
       "      <th>market_creator</th>\n",
       "      <th>trade_id</th>\n",
       "      <th>creation_timestamp</th>\n",
       "      <th>title</th>\n",
       "      <th>market_status</th>\n",
       "      <th>collateral_amount</th>\n",
       "      <th>outcome_index</th>\n",
       "      <th>trade_fee_amount</th>\n",
       "      <th>outcomes_tokens_traded</th>\n",
       "      <th>...</th>\n",
       "      <th>redeemed</th>\n",
       "      <th>redeemed_amount</th>\n",
       "      <th>num_mech_calls</th>\n",
       "      <th>mech_fee_amount</th>\n",
       "      <th>net_earnings</th>\n",
       "      <th>roi</th>\n",
       "      <th>staking</th>\n",
       "      <th>nr_mech_calls</th>\n",
       "      <th>creation_date</th>\n",
       "      <th>month_year_week</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <td>2025-01-12 12:21:40+00:00</td>\n",
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       "      <td>CLOSED</td>\n",
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       "      <td>0.353167</td>\n",
       "      <td>non_Olas</td>\n",
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       "      <td>2025-01-12</td>\n",
       "      <td>Jan-12-2025</td>\n",
       "    </tr>\n",
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       "      <td>2024-12-27 00:21:40+00:00</td>\n",
       "      <td>Will a third fight between Usyk and Fury be of...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>0.943883</td>\n",
       "      <td>1</td>\n",
       "      <td>0.009439</td>\n",
       "      <td>1.302968</td>\n",
       "      <td>...</td>\n",
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       "      <td>1.302968</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.349646</td>\n",
       "      <td>0.366766</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2024-12-27</td>\n",
       "      <td>Dec-29-2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0x05e8bbdb89c84a14d05194bbbae81caf2340db72</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x0de08cc50fa523de23b95ce7ad773e038fb8590d0x05...</td>\n",
       "      <td>2025-01-09 06:21:15+00:00</td>\n",
       "      <td>Will record-low temperatures be recorded in at...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>2.185557</td>\n",
       "      <td>1</td>\n",
       "      <td>0.021856</td>\n",
       "      <td>3.456138</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.207412</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2025-01-09</td>\n",
       "      <td>Jan-12-2025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>0x0f90a2ea8a8b0fbca021405563e763acb9f7d9460x05...</td>\n",
       "      <td>2024-12-27 18:21:35+00:00</td>\n",
       "      <td>Will any new unfair labor practice charges be ...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>0.430373</td>\n",
       "      <td>0</td>\n",
       "      <td>0.004304</td>\n",
       "      <td>0.586244</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>0.586244</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.151567</td>\n",
       "      <td>0.348688</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2024-12-27</td>\n",
       "      <td>Dec-29-2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0x05e8bbdb89c84a14d05194bbbae81caf2340db72</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x13e42a5f5422df80a05c4b7b8d01bd21be82289b0x05...</td>\n",
       "      <td>2025-01-08 18:22:00+00:00</td>\n",
       "      <td>Will the Israeli government publicly acknowled...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>3.227216</td>\n",
       "      <td>1</td>\n",
       "      <td>0.032272</td>\n",
       "      <td>7.405353</td>\n",
       "      <td>...</td>\n",
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       "      <td>7.405353</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.145865</td>\n",
       "      <td>1.271938</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2025-01-08</td>\n",
       "      <td>Jan-12-2025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               trader_address market_creator  \\\n",
       "0  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "1  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "2  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "3  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "4  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "\n",
       "                                            trade_id  \\\n",
       "0  0x083c9f03dfc4072082b9e10aa2137151346f6fd30x05...   \n",
       "1  0x0b52672f29f059b1d0c3a297b28670fb8d92c4bd0x05...   \n",
       "2  0x0de08cc50fa523de23b95ce7ad773e038fb8590d0x05...   \n",
       "3  0x0f90a2ea8a8b0fbca021405563e763acb9f7d9460x05...   \n",
       "4  0x13e42a5f5422df80a05c4b7b8d01bd21be82289b0x05...   \n",
       "\n",
       "         creation_timestamp  \\\n",
       "0 2025-01-12 12:21:40+00:00   \n",
       "1 2024-12-27 00:21:40+00:00   \n",
       "2 2025-01-09 06:21:15+00:00   \n",
       "3 2024-12-27 18:21:35+00:00   \n",
       "4 2025-01-08 18:22:00+00:00   \n",
       "\n",
       "                                               title market_status  \\\n",
       "0  Will federal prosecutors announce any new char...        CLOSED   \n",
       "1  Will a third fight between Usyk and Fury be of...        CLOSED   \n",
       "2  Will record-low temperatures be recorded in at...        CLOSED   \n",
       "3  Will any new unfair labor practice charges be ...        CLOSED   \n",
       "4  Will the Israeli government publicly acknowled...        CLOSED   \n",
       "\n",
       "   collateral_amount outcome_index  trade_fee_amount  outcomes_tokens_traded  \\\n",
       "0           0.204245             1          0.002042                0.279142   \n",
       "1           0.943883             1          0.009439                1.302968   \n",
       "2           2.185557             1          0.021856                3.456138   \n",
       "3           0.430373             0          0.004304                0.586244   \n",
       "4           3.227216             1          0.032272                7.405353   \n",
       "\n",
       "   ...  redeemed  redeemed_amount  num_mech_calls  mech_fee_amount  \\\n",
       "0  ...      True         0.279142               0              0.0   \n",
       "1  ...      True         1.302968               0              0.0   \n",
       "2  ...      True         0.000000               0              0.0   \n",
       "3  ...      True         0.586244               0              0.0   \n",
       "4  ...      True         7.405353               0              0.0   \n",
       "\n",
       "   net_earnings       roi   staking  nr_mech_calls  creation_date  \\\n",
       "0      0.072854  0.353167  non_Olas            NaN     2025-01-12   \n",
       "1      0.349646  0.366766  non_Olas            NaN     2024-12-27   \n",
       "2     -2.207412 -1.000000  non_Olas            NaN     2025-01-09   \n",
       "3      0.151567  0.348688  non_Olas            NaN     2024-12-27   \n",
       "4      4.145865  1.271938  non_Olas            NaN     2025-01-08   \n",
       "\n",
       "   month_year_week  \n",
       "0      Jan-12-2025  \n",
       "1      Dec-29-2024  \n",
       "2      Jan-12-2025  \n",
       "3      Dec-29-2024  \n",
       "4      Jan-12-2025  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unknown_traders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/gp/02mb1d514ng739czlxw1lhh00000gn/T/ipykernel_6876/928490420.py:2: UserWarning: Converting to PeriodArray/Index representation will drop timezone information.\n",
      "  pd.to_datetime(unknown_traders[\"creation_timestamp\"]).dt.to_period(\"W\").dt.start_time.dt.strftime(\"%b-%d-%Y\")\n"
     ]
    }
   ],
   "source": [
    "unknown_traders[\"month_year_week\"] = (\n",
    "        pd.to_datetime(unknown_traders[\"creation_timestamp\"]).dt.to_period(\"W\").dt.start_time.dt.strftime(\"%b-%d-%Y\")\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/gp/02mb1d514ng739czlxw1lhh00000gn/T/ipykernel_6876/589443447.py:2: UserWarning: Converting to PeriodArray/Index representation will drop timezone information.\n",
      "  unknown_traders[\"creation_timestamp\"].dt.to_period(\"W\")\n"
     ]
    }
   ],
   "source": [
    "unknown_traders[\"month_year_week\"] =(\n",
    "        unknown_traders[\"creation_timestamp\"].dt.to_period(\"W\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>trader_address</th>\n",
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       "      <th>staking</th>\n",
       "      <th>nr_mech_calls</th>\n",
       "      <th>creation_date</th>\n",
       "      <th>month_year_week</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x05e8bbdb89c84a14d05194bbbae81caf2340db72</td>\n",
       "      <td>quickstart</td>\n",
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       "      <td>1</td>\n",
       "      <td>0.002042</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0.353167</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2025-01-12</td>\n",
       "      <td>Jan-06-2025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0x05e8bbdb89c84a14d05194bbbae81caf2340db72</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x0b52672f29f059b1d0c3a297b28670fb8d92c4bd0x05...</td>\n",
       "      <td>2024-12-27 00:21:40+00:00</td>\n",
       "      <td>Will a third fight between Usyk and Fury be of...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>0.943883</td>\n",
       "      <td>1</td>\n",
       "      <td>0.009439</td>\n",
       "      <td>1.302968</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>1.302968</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.349646</td>\n",
       "      <td>0.366766</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2024-12-27</td>\n",
       "      <td>Dec-23-2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0x05e8bbdb89c84a14d05194bbbae81caf2340db72</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x0de08cc50fa523de23b95ce7ad773e038fb8590d0x05...</td>\n",
       "      <td>2025-01-09 06:21:15+00:00</td>\n",
       "      <td>Will record-low temperatures be recorded in at...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>2.185557</td>\n",
       "      <td>1</td>\n",
       "      <td>0.021856</td>\n",
       "      <td>3.456138</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.207412</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2025-01-09</td>\n",
       "      <td>Jan-06-2025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0x05e8bbdb89c84a14d05194bbbae81caf2340db72</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x0f90a2ea8a8b0fbca021405563e763acb9f7d9460x05...</td>\n",
       "      <td>2024-12-27 18:21:35+00:00</td>\n",
       "      <td>Will any new unfair labor practice charges be ...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>0.430373</td>\n",
       "      <td>0</td>\n",
       "      <td>0.004304</td>\n",
       "      <td>0.586244</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>0.586244</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.151567</td>\n",
       "      <td>0.348688</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2024-12-27</td>\n",
       "      <td>Dec-23-2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0x05e8bbdb89c84a14d05194bbbae81caf2340db72</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x13e42a5f5422df80a05c4b7b8d01bd21be82289b0x05...</td>\n",
       "      <td>2025-01-08 18:22:00+00:00</td>\n",
       "      <td>Will the Israeli government publicly acknowled...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>3.227216</td>\n",
       "      <td>1</td>\n",
       "      <td>0.032272</td>\n",
       "      <td>7.405353</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>7.405353</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.145865</td>\n",
       "      <td>1.271938</td>\n",
       "      <td>non_Olas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2025-01-08</td>\n",
       "      <td>Jan-06-2025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               trader_address market_creator  \\\n",
       "0  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "1  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "2  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "3  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "4  0x05e8bbdb89c84a14d05194bbbae81caf2340db72     quickstart   \n",
       "\n",
       "                                            trade_id  \\\n",
       "0  0x083c9f03dfc4072082b9e10aa2137151346f6fd30x05...   \n",
       "1  0x0b52672f29f059b1d0c3a297b28670fb8d92c4bd0x05...   \n",
       "2  0x0de08cc50fa523de23b95ce7ad773e038fb8590d0x05...   \n",
       "3  0x0f90a2ea8a8b0fbca021405563e763acb9f7d9460x05...   \n",
       "4  0x13e42a5f5422df80a05c4b7b8d01bd21be82289b0x05...   \n",
       "\n",
       "         creation_timestamp  \\\n",
       "0 2025-01-12 12:21:40+00:00   \n",
       "1 2024-12-27 00:21:40+00:00   \n",
       "2 2025-01-09 06:21:15+00:00   \n",
       "3 2024-12-27 18:21:35+00:00   \n",
       "4 2025-01-08 18:22:00+00:00   \n",
       "\n",
       "                                               title market_status  \\\n",
       "0  Will federal prosecutors announce any new char...        CLOSED   \n",
       "1  Will a third fight between Usyk and Fury be of...        CLOSED   \n",
       "2  Will record-low temperatures be recorded in at...        CLOSED   \n",
       "3  Will any new unfair labor practice charges be ...        CLOSED   \n",
       "4  Will the Israeli government publicly acknowled...        CLOSED   \n",
       "\n",
       "   collateral_amount outcome_index  trade_fee_amount  outcomes_tokens_traded  \\\n",
       "0           0.204245             1          0.002042                0.279142   \n",
       "1           0.943883             1          0.009439                1.302968   \n",
       "2           2.185557             1          0.021856                3.456138   \n",
       "3           0.430373             0          0.004304                0.586244   \n",
       "4           3.227216             1          0.032272                7.405353   \n",
       "\n",
       "   ...  redeemed  redeemed_amount  num_mech_calls  mech_fee_amount  \\\n",
       "0  ...      True         0.279142               0              0.0   \n",
       "1  ...      True         1.302968               0              0.0   \n",
       "2  ...      True         0.000000               0              0.0   \n",
       "3  ...      True         0.586244               0              0.0   \n",
       "4  ...      True         7.405353               0              0.0   \n",
       "\n",
       "   net_earnings       roi   staking  nr_mech_calls  creation_date  \\\n",
       "0      0.072854  0.353167  non_Olas            NaN     2025-01-12   \n",
       "1      0.349646  0.366766  non_Olas            NaN     2024-12-27   \n",
       "2     -2.207412 -1.000000  non_Olas            NaN     2025-01-09   \n",
       "3      0.151567  0.348688  non_Olas            NaN     2024-12-27   \n",
       "4      4.145865  1.271938  non_Olas            NaN     2025-01-08   \n",
       "\n",
       "   month_year_week  \n",
       "0      Jan-06-2025  \n",
       "1      Dec-23-2024  \n",
       "2      Jan-06-2025  \n",
       "3      Dec-23-2024  \n",
       "4      Jan-06-2025  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unknown_traders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Count', ylabel='creation_date'>"
      ]
     },
     "execution_count": 36,
     "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": [
    "import seaborn as sns\n",
    "\n",
    "sns.histplot(old_unknown_traders, y=\"creation_date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Count', ylabel='creation_date'>"
      ]
     },
     "execution_count": 21,
     "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.histplot(unknown_traders, y=\"creation_date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "unknown_traders_df: pd.DataFrame = pd.concat(\n",
    "    [unknown_traders, old_unknown_traders], ignore_index=True\n",
    ")\n",
    "unknown_traders_df.drop_duplicates(\"trade_id\", keep=\"last\", inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Count', ylabel='creation_date'>"
      ]
     },
     "execution_count": 38,
     "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.histplot(unknown_traders_df, y=\"creation_date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "cutoff_date1 = \"2024-11-13\"\n",
    "timestamp1 = pd.Timestamp(\n",
    "datetime.strptime(cutoff_date1, \"%Y-%m-%d\")\n",
    ").tz_localize(\"UTC\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "unknown_traders_df = unknown_traders_df.loc[unknown_traders_df[\"creation_timestamp\"]>=timestamp1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Count', ylabel='creation_date'>"
      ]
     },
     "execution_count": 41,
     "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.histplot(unknown_traders_df, y=\"creation_date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "unknown_traders_df.drop(\"creation_date\", axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "unknown_traders_df.to_parquet(\"../data/unknown_traders.parquet\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>trader_address</th>\n",
       "      <th>market_creator</th>\n",
       "      <th>trade_id</th>\n",
       "      <th>creation_timestamp</th>\n",
       "      <th>title</th>\n",
       "      <th>market_status</th>\n",
       "      <th>collateral_amount</th>\n",
       "      <th>outcome_index</th>\n",
       "      <th>trade_fee_amount</th>\n",
       "      <th>outcomes_tokens_traded</th>\n",
       "      <th>...</th>\n",
       "      <th>is_invalid</th>\n",
       "      <th>winning_trade</th>\n",
       "      <th>earnings</th>\n",
       "      <th>redeemed</th>\n",
       "      <th>redeemed_amount</th>\n",
       "      <th>num_mech_calls</th>\n",
       "      <th>mech_fee_amount</th>\n",
       "      <th>net_earnings</th>\n",
       "      <th>roi</th>\n",
       "      <th>staking</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x23522318aebb55b55879b60fb3ad4682abc6cc2f</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0xeeaadfc4d0ef3f3bb1c430bc96657ed01a52e3e20x23...</td>\n",
       "      <td>2024-12-23 12:36:05+00:00</td>\n",
       "      <td>Will any additional Amazon facilities join the...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>0.401540</td>\n",
       "      <td>0</td>\n",
       "      <td>0.004015</td>\n",
       "      <td>0.939802</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0.939802</td>\n",
       "      <td>True</td>\n",
       "      <td>0.939802</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.534247</td>\n",
       "      <td>1.317323</td>\n",
       "      <td>non_Olas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0x8c4abc95e0091bf3bffe723d2b3c958edf642549</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x6df8ac2c78c8a801d6b6f30e19d3c193daf54f1e0x8c...</td>\n",
       "      <td>2024-12-24 07:22:50+00:00</td>\n",
       "      <td>Will the World Health Organization issue an of...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>0.298503</td>\n",
       "      <td>0</td>\n",
       "      <td>0.002985</td>\n",
       "      <td>0.624681</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0.624681</td>\n",
       "      <td>True</td>\n",
       "      <td>0.624681</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.323193</td>\n",
       "      <td>1.071994</td>\n",
       "      <td>non_Olas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0xb3ead49f4797662511816d2798f774dee3603185</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x4cb63dbf490e1f8f7c10d1e62be7ae6bbbb6d0790xb3...</td>\n",
       "      <td>2024-12-23 12:50:40+00:00</td>\n",
       "      <td>Will Dominion Energy announce any additional p...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>0.423050</td>\n",
       "      <td>1</td>\n",
       "      <td>0.004230</td>\n",
       "      <td>0.687175</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.427280</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>non_Olas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0x2dd9f5678484c1f59f97ed334725858b938b4102</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x005e5be235ba39c5f17622d25e77557ee79a2cba0x2d...</td>\n",
       "      <td>2024-12-22 02:40:35+00:00</td>\n",
       "      <td>Will the Federal Reserve signal a plan to slow...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>1.568561</td>\n",
       "      <td>1</td>\n",
       "      <td>0.015686</td>\n",
       "      <td>2.474096</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.584247</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>non_Olas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0x2dd9f5678484c1f59f97ed334725858b938b4102</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x0080b3768232e8a2f187eaaf342923034275e0b90x2d...</td>\n",
       "      <td>2024-12-13 04:32:35+00:00</td>\n",
       "      <td>Will Russia officially confirm Bashar al-Assad...</td>\n",
       "      <td>CLOSED</td>\n",
       "      <td>2.677632</td>\n",
       "      <td>0</td>\n",
       "      <td>0.026776</td>\n",
       "      <td>5.135035</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>5.135035</td>\n",
       "      <td>True</td>\n",
       "      <td>5.135035</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.430627</td>\n",
       "      <td>0.898765</td>\n",
       "      <td>non_Olas</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               trader_address market_creator  \\\n",
       "0  0x23522318aebb55b55879b60fb3ad4682abc6cc2f     quickstart   \n",
       "1  0x8c4abc95e0091bf3bffe723d2b3c958edf642549     quickstart   \n",
       "2  0xb3ead49f4797662511816d2798f774dee3603185     quickstart   \n",
       "3  0x2dd9f5678484c1f59f97ed334725858b938b4102     quickstart   \n",
       "4  0x2dd9f5678484c1f59f97ed334725858b938b4102     quickstart   \n",
       "\n",
       "                                            trade_id  \\\n",
       "0  0xeeaadfc4d0ef3f3bb1c430bc96657ed01a52e3e20x23...   \n",
       "1  0x6df8ac2c78c8a801d6b6f30e19d3c193daf54f1e0x8c...   \n",
       "2  0x4cb63dbf490e1f8f7c10d1e62be7ae6bbbb6d0790xb3...   \n",
       "3  0x005e5be235ba39c5f17622d25e77557ee79a2cba0x2d...   \n",
       "4  0x0080b3768232e8a2f187eaaf342923034275e0b90x2d...   \n",
       "\n",
       "         creation_timestamp  \\\n",
       "0 2024-12-23 12:36:05+00:00   \n",
       "1 2024-12-24 07:22:50+00:00   \n",
       "2 2024-12-23 12:50:40+00:00   \n",
       "3 2024-12-22 02:40:35+00:00   \n",
       "4 2024-12-13 04:32:35+00:00   \n",
       "\n",
       "                                               title market_status  \\\n",
       "0  Will any additional Amazon facilities join the...        CLOSED   \n",
       "1  Will the World Health Organization issue an of...        CLOSED   \n",
       "2  Will Dominion Energy announce any additional p...        CLOSED   \n",
       "3  Will the Federal Reserve signal a plan to slow...        CLOSED   \n",
       "4  Will Russia officially confirm Bashar al-Assad...        CLOSED   \n",
       "\n",
       "   collateral_amount outcome_index  trade_fee_amount  outcomes_tokens_traded  \\\n",
       "0           0.401540             0          0.004015                0.939802   \n",
       "1           0.298503             0          0.002985                0.624681   \n",
       "2           0.423050             1          0.004230                0.687175   \n",
       "3           1.568561             1          0.015686                2.474096   \n",
       "4           2.677632             0          0.026776                5.135035   \n",
       "\n",
       "   ...  is_invalid  winning_trade  earnings  redeemed  redeemed_amount  \\\n",
       "0  ...       False           True  0.939802      True         0.939802   \n",
       "1  ...       False           True  0.624681      True         0.624681   \n",
       "2  ...       False          False  0.000000     False         0.000000   \n",
       "3  ...       False          False  0.000000      True         0.000000   \n",
       "4  ...       False           True  5.135035      True         5.135035   \n",
       "\n",
       "   num_mech_calls  mech_fee_amount  net_earnings       roi   staking  \n",
       "0               0              0.0      0.534247  1.317323  non_Olas  \n",
       "1               0              0.0      0.323193  1.071994  non_Olas  \n",
       "2               0              0.0     -0.427280 -1.000000  non_Olas  \n",
       "3               0              0.0     -1.584247 -1.000000  non_Olas  \n",
       "4               0              0.0      2.430627  0.898765  non_Olas  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unknown_traders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1568"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(unknown_traders)"
   ]
  }
 ],
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