{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_trades = pd.read_parquet('../data/all_trades_profitability.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <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>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",
       "      <th>nr_mech_calls</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>0.01</td>\n",
       "      <td>0.624356</td>\n",
       "      <td>0.657284</td>\n",
       "      <td>non_staking</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
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       "      <td>...</td>\n",
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       "      <td>0.613414</td>\n",
       "      <td>non_staking</td>\n",
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       "      <td>non_staking</td>\n",
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       "      <td>CLOSED</td>\n",
       "      <td>0.286552</td>\n",
       "      <td>1</td>\n",
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       "      <td>...</td>\n",
       "      <td>True</td>\n",
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       "      <td>True</td>\n",
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       "      <td>0.01</td>\n",
       "      <td>0.171040</td>\n",
       "      <td>0.571242</td>\n",
       "      <td>non_staking</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               trader_address market_creator  \\\n",
       "0  0x01274796ce41aa8e8312e05a427ffb4b0d2148f6     quickstart   \n",
       "1  0x01274796ce41aa8e8312e05a427ffb4b0d2148f6     quickstart   \n",
       "2  0x01274796ce41aa8e8312e05a427ffb4b0d2148f6     quickstart   \n",
       "3  0x01274796ce41aa8e8312e05a427ffb4b0d2148f6     quickstart   \n",
       "4  0x01274796ce41aa8e8312e05a427ffb4b0d2148f6     quickstart   \n",
       "\n",
       "                                            trade_id  \\\n",
       "0  0x007068173910cf8719b6f2e66a18b6825c9dde820x01...   \n",
       "1  0x00d659d7749fda4f1c9402182ca5d7ce26cf5cd10x01...   \n",
       "2  0x02ccdf04646d9a55332e67a73e4ffdab2368d05f0x01...   \n",
       "3  0x09f47ce8995abf1d5b91f2cbfa940ede2fb954c30x01...   \n",
       "4  0x0c86942c52740316bbdb70303c5aaee40876d8ce0x01...   \n",
       "\n",
       "         creation_timestamp  \\\n",
       "0 2024-10-10 21:43:25+00:00   \n",
       "1 2024-10-18 00:36:50+00:00   \n",
       "2 2024-10-23 22:37:35+00:00   \n",
       "3 2024-10-20 23:58:35+00:00   \n",
       "4 2024-10-24 22:42:00+00:00   \n",
       "\n",
       "                                               title market_status  \\\n",
       "0  Will the emergency public warning tests planne...        CLOSED   \n",
       "1  Will the Northern Lights be visible over UK sk...        CLOSED   \n",
       "2  Will any Republican lawmakers introduce legisl...        CLOSED   \n",
       "3  Will any new major AI-driven fraud detection t...        CLOSED   \n",
       "4  Will any new norovirus vaccine trial sites be ...        CLOSED   \n",
       "\n",
       "   collateral_amount outcome_index  trade_fee_amount  outcomes_tokens_traded  \\\n",
       "0           0.930597             0          0.009306                1.574258   \n",
       "1           1.375603             1          0.013756                1.942215   \n",
       "2           0.471695             1          0.004717                0.784784   \n",
       "3           0.289046             1          0.002890                0.445590   \n",
       "4           0.286552             1          0.002866                0.470457   \n",
       "\n",
       "   ...  winning_trade  earnings  redeemed  redeemed_amount  num_mech_calls  \\\n",
       "0  ...           True  1.574258      True         1.574258               1   \n",
       "1  ...          False  0.000000     False         0.000000               1   \n",
       "2  ...           True  0.784784      True         0.784784               1   \n",
       "3  ...          False  0.000000     False         0.000000               5   \n",
       "4  ...           True  0.470457      True         0.470457               1   \n",
       "\n",
       "   mech_fee_amount  net_earnings       roi      staking  nr_mech_calls  \n",
       "0             0.01      0.624356  0.657284  non_staking            NaN  \n",
       "1             0.01     -1.399359 -1.000000  non_staking            NaN  \n",
       "2             0.01      0.298372  0.613414  non_staking            NaN  \n",
       "3             0.05     -0.341936 -1.000000  non_staking            NaN  \n",
       "4             0.01      0.171040  0.571242  non_staking            NaN  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(all_trades.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas._libs.tslibs.timestamps.Timestamp"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(all_trades.creation_timestamp.iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/gp/02mb1d514ng739czlxw1lhh00000gn/T/ipykernel_69783/1320555996.py:2: UserWarning: Converting to PeriodArray/Index representation will drop timezone information.\n",
      "  all_trades[\"creation_timestamp\"].dt.to_period(\"W\").dt.strftime(\"%b-%d\")\n"
     ]
    }
   ],
   "source": [
    "all_trades[\"month_year_week\"] = (\n",
    "    all_trades[\"creation_timestamp\"].dt.to_period(\"W\").dt.strftime(\"%b-%d\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/gp/02mb1d514ng739czlxw1lhh00000gn/T/ipykernel_69783/353897105.py:2: UserWarning: Converting to PeriodArray/Index representation will drop timezone information.\n",
      "  all_trades[\"creation_timestamp\"].dt.to_period(\"W\")\n"
     ]
    }
   ],
   "source": [
    "all_trades[\"month_year_week\"] = (\n",
    "    all_trades[\"creation_timestamp\"].dt.to_period(\"W\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas._libs.tslibs.period.Period"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(all_trades.month_year_week.iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Period('2024-10-07/2024-10-13', 'W-SUN')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades.month_year_week.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas._libs.tslibs.timestamps.Timestamp"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(all_trades.iloc[0].creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-11-27 01:45:05+0000', tz='UTC')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(all_trades.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-09-29 00:02:45+0000', tz='UTC')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(all_trades.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_trades = pd.read_parquet('../data/new_fpmmTrades.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3798 entries, 0 to 3797\n",
      "Data columns (total 24 columns):\n",
      " #   Column                         Non-Null Count  Dtype \n",
      "---  ------                         --------------  ----- \n",
      " 0   collateralAmount               3798 non-null   object\n",
      " 1   collateralAmountUSD            3798 non-null   object\n",
      " 2   collateralToken                3798 non-null   object\n",
      " 3   creationTimestamp              3798 non-null   object\n",
      " 4   trader_address                 3798 non-null   object\n",
      " 5   feeAmount                      3798 non-null   object\n",
      " 6   id                             3798 non-null   object\n",
      " 7   oldOutcomeTokenMarginalPrice   3798 non-null   object\n",
      " 8   outcomeIndex                   3798 non-null   object\n",
      " 9   outcomeTokenMarginalPrice      3798 non-null   object\n",
      " 10  outcomeTokensTraded            3798 non-null   object\n",
      " 11  title                          3798 non-null   object\n",
      " 12  transactionHash                3798 non-null   object\n",
      " 13  type                           3798 non-null   object\n",
      " 14  market_creator                 3798 non-null   object\n",
      " 15  fpmm.answerFinalizedTimestamp  0 non-null      object\n",
      " 16  fpmm.arbitrationOccurred       3798 non-null   bool  \n",
      " 17  fpmm.currentAnswer             0 non-null      object\n",
      " 18  fpmm.id                        3798 non-null   object\n",
      " 19  fpmm.isPendingArbitration      3798 non-null   bool  \n",
      " 20  fpmm.openingTimestamp          3798 non-null   object\n",
      " 21  fpmm.outcomes                  3798 non-null   object\n",
      " 22  fpmm.title                     3798 non-null   object\n",
      " 23  fpmm.condition.id              3798 non-null   object\n",
      "dtypes: bool(2), object(22)\n",
      "memory usage: 660.3+ KB\n"
     ]
    }
   ],
   "source": [
    "new_trades.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3798"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(new_trades.id.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['collateralAmount', 'collateralAmountUSD', 'collateralToken',\n",
       "       'creationTimestamp', 'trader_address', 'feeAmount', 'id',\n",
       "       'oldOutcomeTokenMarginalPrice', 'outcomeIndex',\n",
       "       'outcomeTokenMarginalPrice', 'outcomeTokensTraded', 'title',\n",
       "       'transactionHash', 'type', 'market_creator',\n",
       "       'fpmm.answerFinalizedTimestamp', 'fpmm.arbitrationOccurred',\n",
       "       'fpmm.currentAnswer', 'fpmm.id', 'fpmm.isPendingArbitration',\n",
       "       'fpmm.openingTimestamp', 'fpmm.outcomes', 'fpmm.title',\n",
       "       'fpmm.condition.id'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_trades.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1732609530'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(new_trades.creationTimestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "old_trades = pd.read_parquet('../data/fpmmTrades.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1732609530'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(old_trades.creationTimestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_trades_before = pd.read_parquet('../data/daily_info.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7104 entries, 0 to 7103\n",
      "Data columns (total 21 columns):\n",
      " #   Column                  Non-Null Count  Dtype              \n",
      "---  ------                  --------------  -----              \n",
      " 0   trader_address          7104 non-null   object             \n",
      " 1   market_creator          7104 non-null   object             \n",
      " 2   trade_id                7104 non-null   object             \n",
      " 3   creation_timestamp      7104 non-null   datetime64[ns, UTC]\n",
      " 4   title                   7104 non-null   object             \n",
      " 5   market_status           7104 non-null   object             \n",
      " 6   collateral_amount       7104 non-null   float64            \n",
      " 7   outcome_index           7104 non-null   object             \n",
      " 8   trade_fee_amount        7104 non-null   float64            \n",
      " 9   outcomes_tokens_traded  7104 non-null   float64            \n",
      " 10  current_answer          0 non-null      object             \n",
      " 11  is_invalid              7104 non-null   bool               \n",
      " 12  winning_trade           0 non-null      object             \n",
      " 13  earnings                7104 non-null   float64            \n",
      " 14  redeemed                7104 non-null   bool               \n",
      " 15  redeemed_amount         7104 non-null   float64            \n",
      " 16  num_mech_calls          7104 non-null   int64              \n",
      " 17  mech_fee_amount         7104 non-null   float64            \n",
      " 18  net_earnings            7104 non-null   float64            \n",
      " 19  roi                     7104 non-null   float64            \n",
      " 20  staking                 7104 non-null   object             \n",
      "dtypes: bool(2), datetime64[ns, UTC](1), float64(8), int64(1), object(9)\n",
      "memory usage: 1.0+ MB\n"
     ]
    }
   ],
   "source": [
    "all_trades_before.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades_before.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2025-01-07 09:01:05+0000', tz='UTC')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(all_trades_before.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "staking\n",
       "non_agent      6140\n",
       "quickstart     1920\n",
       "non_staking    1024\n",
       "pearl           602\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades_before.staking.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    9686.0\n",
       "mean        0.0\n",
       "std         0.0\n",
       "min         0.0\n",
       "25%         0.0\n",
       "50%         0.0\n",
       "75%         0.0\n",
       "max         0.0\n",
       "Name: num_mech_calls, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades_before.num_mech_calls.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>trader_address</th>\n",
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       "      <td>pearl</td>\n",
       "      <td>0xcd34c44c5f944bcf05f958e5d25960f8fcda664b0x04...</td>\n",
       "      <td>2024-12-01 18:38:40+00:00</td>\n",
       "      <td>Will Iran install more than 6,000 new centrifu...</td>\n",
       "      <td>OPEN</td>\n",
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       "      <td>1</td>\n",
       "      <td>0.00025</td>\n",
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       "    <tr>\n",
       "      <th>8782</th>\n",
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       "      <td>pearl</td>\n",
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       "      <td>pearl</td>\n",
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       "<p>5 rows × 21 columns</p>\n",
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      "text/plain": [
       "                                  trader_address market_creator  \\\n",
       "8778  0x047f8663b254d90d28af6d8ca7181947e94577ce          pearl   \n",
       "8779  0x047f8663b254d90d28af6d8ca7181947e94577ce          pearl   \n",
       "8780  0x047f8663b254d90d28af6d8ca7181947e94577ce          pearl   \n",
       "8781  0x047f8663b254d90d28af6d8ca7181947e94577ce          pearl   \n",
       "8782  0x06d873e7465a6680f5487905d7b5daf7f2c6e299          pearl   \n",
       "\n",
       "                                               trade_id  \\\n",
       "8778  0x2379c39b63aa1a3e37d4a7e4b909a699b4c14a810x04...   \n",
       "8779  0xbb96f5a99bf452aa202fea0b36b0910734377d450x04...   \n",
       "8780  0xcd34c44c5f944bcf05f958e5d25960f8fcda664b0x04...   \n",
       "8781  0xff1d1569a94ebad89612213f083a3cb948415f740x04...   \n",
       "8782  0x2379c39b63aa1a3e37d4a7e4b909a699b4c14a810x06...   \n",
       "\n",
       "            creation_timestamp  \\\n",
       "8778 2024-11-30 16:57:40+00:00   \n",
       "8779 2024-11-30 16:45:25+00:00   \n",
       "8780 2024-12-01 18:38:40+00:00   \n",
       "8781 2024-11-30 17:00:30+00:00   \n",
       "8782 2024-12-02 17:07:05+00:00   \n",
       "\n",
       "                                                  title market_status  \\\n",
       "8778  Will the IAEA issue a formal statement regardi...          OPEN   \n",
       "8779  Will the IAEA confirm Iran has started feeding...          OPEN   \n",
       "8780  Will Iran install more than 6,000 new centrifu...          OPEN   \n",
       "8781  Will Rivian's stock price increase by at least...          OPEN   \n",
       "8782  Will the IAEA issue a formal statement regardi...          OPEN   \n",
       "\n",
       "      collateral_amount outcome_index  trade_fee_amount  \\\n",
       "8778              0.025             0           0.00025   \n",
       "8779              0.025             0           0.00025   \n",
       "8780              0.025             1           0.00025   \n",
       "8781              0.025             0           0.00025   \n",
       "8782              0.025             0           0.00025   \n",
       "\n",
       "      outcomes_tokens_traded  ...  is_invalid  winning_trade earnings  \\\n",
       "8778                0.047923  ...       False           None      0.0   \n",
       "8779                0.049461  ...       False           None      0.0   \n",
       "8780                0.046737  ...       False           None      0.0   \n",
       "8781                0.047316  ...       False           None      0.0   \n",
       "8782                0.043896  ...       False           None      0.0   \n",
       "\n",
       "      redeemed  redeemed_amount  num_mech_calls  mech_fee_amount  \\\n",
       "8778     False                0               0              0.0   \n",
       "8779     False                0               0              0.0   \n",
       "8780     False                0               0              0.0   \n",
       "8781     False                0               0              0.0   \n",
       "8782     False                0               0              0.0   \n",
       "\n",
       "      net_earnings  roi  staking  \n",
       "8778      -0.02525 -1.0    pearl  \n",
       "8779      -0.02525 -1.0    pearl  \n",
       "8780      -0.02525 -1.0    pearl  \n",
       "8781      -0.02525 -1.0    pearl  \n",
       "8782      -0.02525 -1.0    pearl  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades_before.loc[all_trades_before[\"staking\"]==\"pearl\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.247759</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>non_agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0x027592700fafc4db3221bb662d7bdc7f546a2bb5</td>\n",
       "      <td>quickstart</td>\n",
       "      <td>0x2b5f1a0eef4c846bfddc4ae88bd1a6d02a9e703d0x02...</td>\n",
       "      <td>2024-11-30 13:39:40+00:00</td>\n",
       "      <td>Will any cybersecurity firm release a detailed...</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.277566</td>\n",
       "      <td>0</td>\n",
       "      <td>0.002776</td>\n",
       "      <td>0.520043</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.280342</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>non_agent</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               trader_address market_creator  \\\n",
       "0  0x027592700fafc4db3221bb662d7bdc7f546a2bb5     quickstart   \n",
       "1  0x027592700fafc4db3221bb662d7bdc7f546a2bb5     quickstart   \n",
       "2  0x027592700fafc4db3221bb662d7bdc7f546a2bb5     quickstart   \n",
       "3  0x027592700fafc4db3221bb662d7bdc7f546a2bb5     quickstart   \n",
       "4  0x027592700fafc4db3221bb662d7bdc7f546a2bb5     quickstart   \n",
       "\n",
       "                                            trade_id  \\\n",
       "0  0x08ee7c048ea0b7e3c967a455cf7da5e38abdbaff0x02...   \n",
       "1  0x08ee7c048ea0b7e3c967a455cf7da5e38abdbaff0x02...   \n",
       "2  0x1bdd848ae9044375c11b6ab5eddd2e4f9ff0f0aa0x02...   \n",
       "3  0x25408c25b8681e994e2e12c6754ddf446124cce90x02...   \n",
       "4  0x2b5f1a0eef4c846bfddc4ae88bd1a6d02a9e703d0x02...   \n",
       "\n",
       "         creation_timestamp  \\\n",
       "0 2024-11-28 16:56:25+00:00   \n",
       "1 2024-11-30 15:00:10+00:00   \n",
       "2 2024-12-01 23:09:55+00:00   \n",
       "3 2024-11-30 13:54:45+00:00   \n",
       "4 2024-11-30 13:39:40+00:00   \n",
       "\n",
       "                                               title market_status  \\\n",
       "0  Will any major legal precedent regarding influ...          OPEN   \n",
       "1  Will any major legal precedent regarding influ...          OPEN   \n",
       "2  Will any Democratic senator publicly call for ...          OPEN   \n",
       "3  Will any major Linux distribution announce a s...          OPEN   \n",
       "4  Will any cybersecurity firm release a detailed...          OPEN   \n",
       "\n",
       "   collateral_amount outcome_index  trade_fee_amount  outcomes_tokens_traded  \\\n",
       "0           0.318926             1          0.003189                0.642313   \n",
       "1           0.106057             0          0.001061                0.244680   \n",
       "2           0.152501             0          0.001525                0.304904   \n",
       "3           0.245306             0          0.002453                0.507058   \n",
       "4           0.277566             0          0.002776                0.520043   \n",
       "\n",
       "   ...  is_invalid  winning_trade earnings  redeemed  redeemed_amount  \\\n",
       "0  ...       False           None      0.0     False                0   \n",
       "1  ...       False           None      0.0     False                0   \n",
       "2  ...       False           None      0.0     False                0   \n",
       "3  ...       False           None      0.0     False                0   \n",
       "4  ...       False           None      0.0     False                0   \n",
       "\n",
       "   num_mech_calls  mech_fee_amount  net_earnings  roi    staking  \n",
       "0               0              0.0     -0.322116 -1.0  non_agent  \n",
       "1               0              0.0     -0.107117 -1.0  non_agent  \n",
       "2               0              0.0     -0.154026 -1.0  non_agent  \n",
       "3               0              0.0     -0.247759 -1.0  non_agent  \n",
       "4               0              0.0     -0.280342 -1.0  non_agent  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades_before.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_trades_df = pd.read_parquet('../json_data/all_trades_df.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_trades_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2024-11-23 01:38:25+0000', tz='UTC')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(all_trades_df.creation_timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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