new daily graphs

app.py

@@ -1,4 +1,3 @@
-from datetime import datetime, timedelta
 import gradio as gr
 import pandas as pd
 import duckdb
@@ -15,11 +14,13 @@ from tabs.trader_plots import (
     plot_trader_daily_metrics_by_market_creator,
     default_trader_metric,
     trader_metric_choices,
+    trade_daily_metric_choices,
+    default_daily_metric,
     get_metrics_text,
     plot_winning_metric_per_trader,
     get_interpretation_text,
 )
-
+from tabs.daily_graphs import get_current_week_data, plot_daily_metrics
 from scripts.utils import get_traders_family
 from scripts.trades_volume_per_market import plot_weekly_trades_volume_by_trader_family
 from tabs.market_plots import (
@@ -66,14 +67,20 @@ def get_all_data():
     df2 = con.execute(query2).fetchdf()
     logger.info("Got all data from closed_markets_div.parquet")
 
+    # Query to fetch daily live data
+    query3 = f"""
+    SELECT *
+    FROM read_parquet('./data/daily_info.parquet')
+    """
+    df3 = con.execute(query3).fetchdf()
     con.close()
 
-    return df1, df2
+    return df1, df2, df3
 
 
 def prepare_data():
 
-    all_trades, closed_markets = get_all_data()
+    all_trades, closed_markets, daily_info = get_all_data()
 
     all_trades["creation_date"] = all_trades["creation_timestamp"].dt.date
 
@@ -88,7 +95,7 @@ def prepare_data():
     trader_agents_data = pd.merge(
         all_trades, volume_trades_per_trader_and_market, on=["trader_address", "title"]
     )
-
+    daily_info["creation_date"] = daily_info["creation_timestamp"].dt.date
     # adding the trader family column
     trader_agents_data["trader_family"] = trader_agents_data.apply(
         lambda x: get_traders_family(x), axis=1
@@ -106,28 +113,23 @@ def prepare_data():
     closed_markets["month_year_week"] = (
         closed_markets["opening_datetime"].dt.to_period("W").dt.strftime("%b-%d")
     )
-    return trader_agents_data, closed_markets
+    return trader_agents_data, closed_markets, daily_info
 
 
-trader_agents_data, closed_markets = prepare_data()
-# print("trader agents data before computing metrics")
-# print(trader_agents_data.head())
+trader_agents_data, closed_markets, daily_info = prepare_data()
+
 demo = gr.Blocks()
 # get weekly metrics by market creator: qs, pearl or all.
 weekly_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
     trader_agents_data
 )
-daily_metrics_by_market_creator = compute_daily_metrics_by_market_creator(
-    trader_agents_data
-)
+
 weekly_agent_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
     trader_agents_data, trader_filter="agent"
 )
 weekly_non_agent_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
     trader_agents_data, trader_filter="non_agent"
 )
-# print("weekly metrics by market creator")
-# print(weekly_metrics_by_market_creator.head())
 
 weekly_winning_metrics = compute_winning_metrics_by_trader(
     trader_agents_data=trader_agents_data
@@ -237,38 +239,85 @@ with demo:
                 inputs=trader_na_details_selector,
                 outputs=na_trader_markets_plot,
             )
-        # with gr.TabItem("🔥 Daily metrics (WIP)"):
-        #     with gr.Row():
-        #         gr.Markdown("# Daily metrics of last week of all traders")
-        #     with gr.Row():
-        #         trader_daily_details_selector = gr.Dropdown(
-        #             label="Select a daily trader metric",
-        #             choices=trader_metric_choices,
-        #             value=default_trader_metric,
-        #         )
-
-        #     with gr.Row():
-        #         with gr.Column(scale=3):
-        #             trader_daily_markets_plot = (
-        #                 plot_trader_daily_metrics_by_market_creator(
-        #                     metric_name=default_trader_metric,
-        #                     traders_df=daily_metrics_by_market_creator,
-        #                 )
-        #             )
-        #         with gr.Column(scale=1):
-        #             trade_details_text = get_metrics_text()
-
-        #     def update_trader_daily_details(trader_detail):
-        #         return plot_trader_daily_metrics_by_market_creator(
-        #             metric_name=trader_detail,
-        #             traders_df=daily_metrics_by_market_creator,
-        #         )
-
-        #     trader_daily_details_selector.change(
-        #         update_trader_daily_details,
-        #         inputs=trader_daily_details_selector,
-        #         outputs=trader_daily_markets_plot,
-        #     )
+        with gr.TabItem("📅 Daily trades dashboard (WIP)"):
+            current_week_trades = get_current_week_data(trades_df=trader_agents_data)
+            live_trades_current_week = get_current_week_data(trades_df=daily_info)
+            if len(current_week_trades) > 0:
+                daily_prof_metrics_by_market_creator = (
+                    compute_daily_metrics_by_market_creator(current_week_trades)
+                )
+            else:
+                daily_prof_metrics_by_market_creator = pd.DataFrame()
+            live_metrics_by_market_creator = compute_daily_metrics_by_market_creator(
+                live_trades_current_week, trader_filter=None, live_metrics=True
+            )
+            print("live metrics dataframe")
+            print(live_metrics_by_market_creator.head())
+            with gr.Row():
+                gr.Markdown("# Daily live metrics for all trades")
+            with gr.Row():
+                trade_live_details_selector = gr.Dropdown(
+                    label="Select a daily live metric",
+                    choices=trade_daily_metric_choices,
+                    value=default_daily_metric,
+                )
+
+            with gr.Row():
+                with gr.Column(scale=3):
+                    trade_live_details_plot = plot_daily_metrics(
+                        metric_name=default_daily_metric,
+                        trades_df=live_metrics_by_market_creator,
+                    )
+                with gr.Column(scale=1):
+                    trade_details_text = get_metrics_text()
+
+            def update_trade_live_details(trade_detail, trade_live_details_plot):
+                new_a_plot = plot_daily_metrics(
+                    metric_name=trade_detail, trades_df=live_metrics_by_market_creator
+                )
+                return new_a_plot
+
+            trade_live_details_selector.change(
+                update_trade_live_details,
+                inputs=[trade_live_details_selector, trade_live_details_plot],
+                outputs=[trade_live_details_plot],
+            )
+
+            with gr.Row():
+                gr.Markdown("# Daily profitability metrics available for all trades")
+            if len(current_week_trades) > 0:
+                with gr.Row():
+                    trader_daily_details_selector = gr.Dropdown(
+                        label="Select a daily trade metric",
+                        choices=trader_metric_choices,
+                        value=default_trader_metric,
+                    )
+
+                with gr.Row():
+                    with gr.Column(scale=3):
+                        trader_daily_details_plot = plot_daily_metrics(
+                            metric_name=default_trader_metric,
+                            trades_df=daily_prof_metrics_by_market_creator,
+                        )
+                    with gr.Column(scale=1):
+                        trader_details_text = get_metrics_text()
+
+                def update_trader_daily_details(
+                    trade_detail, trader_daily_details_plot
+                ):
+                    new_a_plot = plot_daily_metrics(
+                        metric_name=trade_detail,
+                        trades_df=daily_prof_metrics_by_market_creator,
+                    )
+                    return new_a_plot
+
+                trader_daily_details_selector.change(
+                    update_trader_daily_details,
+                    inputs=[trader_daily_details_selector, trader_daily_details_plot],
+                    outputs=[trader_daily_details_plot],
+                )
+            else:
+                gr.Markdown("Data not available yet")
 
         with gr.TabItem("📉Closed Markets Kullback–Leibler divergence"):
             with gr.Row():

data/daily_info.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f41fdb6fc36cf8cb28980bca049de6b4fa986a9800176e269a5259a7e744c514
+size 251792

notebooks/closed_markets.ipynb

@@ -30,20 +30,88 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    markets_df = pd.read_parquet(\"../data/fpmmTrades.parquet\")\n",
+    "except Exception:\n",
+    "    print(\"Error reading the parquet file\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 61442 entries, 0 to 61441\n",
+      "Data columns (total 24 columns):\n",
+      " #   Column                         Non-Null Count  Dtype \n",
+      "---  ------                         --------------  ----- \n",
+      " 0   collateralAmount               61442 non-null  object\n",
+      " 1   collateralAmountUSD            61442 non-null  object\n",
+      " 2   collateralToken                61442 non-null  object\n",
+      " 3   creationTimestamp              61442 non-null  object\n",
+      " 4   trader_address                 61442 non-null  object\n",
+      " 5   feeAmount                      61442 non-null  object\n",
+      " 6   id                             61442 non-null  object\n",
+      " 7   oldOutcomeTokenMarginalPrice   61442 non-null  object\n",
+      " 8   outcomeIndex                   61442 non-null  object\n",
+      " 9   outcomeTokenMarginalPrice      61442 non-null  object\n",
+      " 10  outcomeTokensTraded            61442 non-null  object\n",
+      " 11  title                          61442 non-null  object\n",
+      " 12  transactionHash                61442 non-null  object\n",
+      " 13  type                           61442 non-null  object\n",
+      " 14  market_creator                 61442 non-null  object\n",
+      " 15  fpmm.answerFinalizedTimestamp  47113 non-null  object\n",
+      " 16  fpmm.arbitrationOccurred       61442 non-null  bool  \n",
+      " 17  fpmm.currentAnswer             47113 non-null  object\n",
+      " 18  fpmm.id                        61442 non-null  object\n",
+      " 19  fpmm.isPendingArbitration      61442 non-null  bool  \n",
+      " 20  fpmm.openingTimestamp          61442 non-null  object\n",
+      " 21  fpmm.outcomes                  61442 non-null  object\n",
+      " 22  fpmm.title                     61442 non-null  object\n",
+      " 23  fpmm.condition.id              61442 non-null  object\n",
+      "dtypes: bool(2), object(22)\n",
+      "memory usage: 10.4+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "markets_df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "4686"
+       "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": 3,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "len(markets)"
+    "markets_df.columns"
    ]
   },
   {
@@ -648,103 +716,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": null,
    "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>currentAnswer</th>\n",
-       "      <th>id</th>\n",
-       "      <th>openingTimestamp</th>\n",
-       "      <th>market_creator</th>\n",
-       "      <th>opening_datetime</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>15736</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0x92ed80e541f642b564f992245abe640282dd273c</td>\n",
-       "      <td>1727568000</td>\n",
-       "      <td>quickstart</td>\n",
-       "      <td>2024-09-29 02:00:00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6272</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0x4002481fe7bc39c1baa4b5988c038da13ed05832</td>\n",
-       "      <td>1727568000</td>\n",
-       "      <td>quickstart</td>\n",
-       "      <td>2024-09-29 02:00:00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>24383</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0xf820d06509027c309b00cd386055982d9bea0c10</td>\n",
-       "      <td>1727568000</td>\n",
-       "      <td>quickstart</td>\n",
-       "      <td>2024-09-29 02:00:00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12418</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0x74e0fa941341ebe980fbdcfa8b40244cb448eb56</td>\n",
-       "      <td>1727568000</td>\n",
-       "      <td>quickstart</td>\n",
-       "      <td>2024-09-29 02:00:00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4754</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0x2f44e179b5cc964e504046bac31d6945a0652af2</td>\n",
-       "      <td>1727568000</td>\n",
-       "      <td>quickstart</td>\n",
-       "      <td>2024-09-29 02:00:00</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       currentAnswer                                          id  \\\n",
-       "15736            NaN  0x92ed80e541f642b564f992245abe640282dd273c   \n",
-       "6272             NaN  0x4002481fe7bc39c1baa4b5988c038da13ed05832   \n",
-       "24383            NaN  0xf820d06509027c309b00cd386055982d9bea0c10   \n",
-       "12418            NaN  0x74e0fa941341ebe980fbdcfa8b40244cb448eb56   \n",
-       "4754             NaN  0x2f44e179b5cc964e504046bac31d6945a0652af2   \n",
-       "\n",
-       "      openingTimestamp market_creator    opening_datetime  \n",
-       "15736       1727568000     quickstart 2024-09-29 02:00:00  \n",
-       "6272        1727568000     quickstart 2024-09-29 02:00:00  \n",
-       "24383       1727568000     quickstart 2024-09-29 02:00:00  \n",
-       "12418       1727568000     quickstart 2024-09-29 02:00:00  \n",
-       "4754        1727568000     quickstart 2024-09-29 02:00:00  "
-      ]
-     },
-     "execution_count": 52,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "trade_markets.tail()"
    ]
@@ -945,23 +919,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "currentAnswer\n",
-       "0x0000000000000000000000000000000000000000000000000000000000000001    407\n",
-       "0x0000000000000000000000000000000000000000000000000000000000000000    241\n",
-       "Name: count, dtype: int64"
-      ]
-     },
-     "execution_count": 38,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "trade_markets.currentAnswer.value_counts()"
    ]

notebooks/daily_data.ipynb

@@ -0,0 +1,430 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "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": [
+       "Timestamp('2024-11-23 01:38:25+0000', tz='UTC')"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "max(all_trades.creation_timestamp)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Timestamp('2024-09-22 00:02:05+0000', tz='UTC')"
+      ]
+     },
+     "execution_count": 4,
+     "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": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "all_trades_before = pd.read_parquet('../data/daily_info.parquet')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 3882 entries, 0 to 3881\n",
+      "Data columns (total 21 columns):\n",
+      " #   Column                  Non-Null Count  Dtype              \n",
+      "---  ------                  --------------  -----              \n",
+      " 0   trader_address          3882 non-null   object             \n",
+      " 1   market_creator          3882 non-null   object             \n",
+      " 2   trade_id                3882 non-null   object             \n",
+      " 3   creation_timestamp      3882 non-null   datetime64[ns, UTC]\n",
+      " 4   title                   3882 non-null   object             \n",
+      " 5   market_status           3882 non-null   object             \n",
+      " 6   collateral_amount       3882 non-null   float64            \n",
+      " 7   outcome_index           3882 non-null   object             \n",
+      " 8   trade_fee_amount        3882 non-null   float64            \n",
+      " 9   outcomes_tokens_traded  3882 non-null   float64            \n",
+      " 10  current_answer          0 non-null      object             \n",
+      " 11  is_invalid              3882 non-null   bool               \n",
+      " 12  winning_trade           0 non-null      object             \n",
+      " 13  earnings                3882 non-null   float64            \n",
+      " 14  redeemed                3882 non-null   bool               \n",
+      " 15  redeemed_amount         3882 non-null   int64              \n",
+      " 16  num_mech_calls          3882 non-null   int64              \n",
+      " 17  mech_fee_amount         3882 non-null   float64            \n",
+      " 18  net_earnings            3882 non-null   float64            \n",
+      " 19  roi                     3882 non-null   float64            \n",
+      " 20  staking                 3882 non-null   object             \n",
+      "dtypes: bool(2), datetime64[ns, UTC](1), float64(7), int64(2), object(9)\n",
+      "memory usage: 583.9+ KB\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": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Timestamp('2024-11-26 10:19:30+0000', tz='UTC')"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "max(all_trades_before.creation_timestamp)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "staking\n",
+       "non_agent      2376\n",
+       "quickstart      672\n",
+       "pearl           502\n",
+       "non_staking     332\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_trades_before.staking.value_counts()"
+   ]
+  },
+  {
+   "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": []
+  }
+ ],
+ "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
+}

notebooks/trader_agent_metrics.ipynb

@@ -1353,863 +1353,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Computing weekly metrics for week =Jul-21 by market creator\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Trader' metrics: 100%|██████████| 19/19 [00:00<00:00, 528.86metrics/s]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Volume of data for trader 0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57 and market creator all = 3\n",
-      "{'trader_address': '0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57', 'net_earnings': -0.7234109591878646, 'earnings': 1.7851345317122906, 'bet_amount': 2.380926951862897, 'nr_mech_calls': 8, 'roi': -0.2847035640507064}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57 and market creator quickstart = 3\n",
-      "{'trader_address': '0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57', 'net_earnings': -0.7234109591878646, 'earnings': 1.7851345317122906, 'bet_amount': 2.380926951862897, 'nr_mech_calls': 8, 'roi': -0.2847035640507064}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57     -0.723411  1.785135   \n",
-      "1  0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57     -0.723411  1.785135   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0    2.380927              8 -0.284704          Jul-21            all  \n",
-      "1    2.380927              8 -0.284704          Jul-21     quickstart  \n",
-      "Volume of data for trader 0xf089874165be0377680683fd5187a058dea82683 and market creator all = 1\n",
-      "{'trader_address': '0xf089874165be0377680683fd5187a058dea82683', 'net_earnings': 0.7996491228070175, 'earnings': 1.8396491228070175, 'bet_amount': 1.0, 'nr_mech_calls': 2, 'roi': 0.7688933873144399}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0xf089874165be0377680683fd5187a058dea82683 and market creator quickstart = 1\n",
-      "{'trader_address': '0xf089874165be0377680683fd5187a058dea82683', 'net_earnings': 0.7996491228070175, 'earnings': 1.8396491228070175, 'bet_amount': 1.0, 'nr_mech_calls': 2, 'roi': 0.7688933873144399}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0xf089874165be0377680683fd5187a058dea82683      0.799649  1.839649   \n",
-      "1  0xf089874165be0377680683fd5187a058dea82683      0.799649  1.839649   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0         1.0              2  0.768893          Jul-21            all  \n",
-      "1         1.0              2  0.768893          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2 and market creator all = 4\n",
-      "{'trader_address': '0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2', 'net_earnings': -1.0071645410215222, 'earnings': 3.350264102099237, 'bet_amount': 4.154341806981137, 'nr_mech_calls': 12, 'roi': -0.22919576702510377}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2 and market creator quickstart = 4\n",
-      "{'trader_address': '0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2', 'net_earnings': -1.0071645410215222, 'earnings': 3.350264102099237, 'bet_amount': 4.154341806981137, 'nr_mech_calls': 12, 'roi': -0.22919576702510377}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2     -1.007165  3.350264   \n",
-      "1  0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2     -1.007165  3.350264   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0    4.154342             12 -0.229196          Jul-21            all  \n",
-      "1    4.154342             12 -0.229196          Jul-21     quickstart  \n",
-      "Volume of data for trader 0xe283e408c6017447da9fe092d52c386753699680 and market creator all = 1\n",
-      "{'trader_address': '0xe283e408c6017447da9fe092d52c386753699680', 'net_earnings': -1.04, 'earnings': 0.0, 'bet_amount': 1.0, 'nr_mech_calls': 2, 'roi': -1.0}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "No data. Skipping market creator quickstart\n",
-      "Filtering only specific market creators = pearl\n",
-      "Volume of data for trader 0xe283e408c6017447da9fe092d52c386753699680 and market creator pearl = 1\n",
-      "{'trader_address': '0xe283e408c6017447da9fe092d52c386753699680', 'net_earnings': -1.04, 'earnings': 0.0, 'bet_amount': 1.0, 'nr_mech_calls': 2, 'roi': -1.0}\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0xe283e408c6017447da9fe092d52c386753699680         -1.04       0.0   \n",
-      "1  0xe283e408c6017447da9fe092d52c386753699680         -1.04       0.0   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls  roi month_year_week market_creator  \n",
-      "0         1.0              2 -1.0          Jul-21            all  \n",
-      "1         1.0              2 -1.0          Jul-21          pearl  \n",
-      "Volume of data for trader 0x480e5b5abd27cd754745871116e79caf90468dd4 and market creator all = 2\n",
-      "{'trader_address': '0x480e5b5abd27cd754745871116e79caf90468dd4', 'net_earnings': -0.36794781695584966, 'earnings': 1.9646689200064404, 'bet_amount': 2.2476634676100886, 'nr_mech_calls': 4, 'roi': -0.1580760372261362}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x480e5b5abd27cd754745871116e79caf90468dd4 and market creator quickstart = 2\n",
-      "{'trader_address': '0x480e5b5abd27cd754745871116e79caf90468dd4', 'net_earnings': -0.36794781695584966, 'earnings': 1.9646689200064404, 'bet_amount': 2.2476634676100886, 'nr_mech_calls': 4, 'roi': -0.1580760372261362}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x480e5b5abd27cd754745871116e79caf90468dd4     -0.367948  1.964669   \n",
-      "1  0x480e5b5abd27cd754745871116e79caf90468dd4     -0.367948  1.964669   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0    2.247663              4 -0.158076          Jul-21            all  \n",
-      "1    2.247663              4 -0.158076          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x3c01b79bad670a37c8784bdf47b973b341064f10 and market creator all = 4\n",
-      "{'trader_address': '0x3c01b79bad670a37c8784bdf47b973b341064f10', 'net_earnings': 0.5130050997258764, 'earnings': 5.0788528986176456, 'bet_amount': 4.3978899989135, 'nr_mech_calls': 8, 'roi': 0.11255319892497745}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x3c01b79bad670a37c8784bdf47b973b341064f10 and market creator quickstart = 4\n",
-      "{'trader_address': '0x3c01b79bad670a37c8784bdf47b973b341064f10', 'net_earnings': 0.5130050997258764, 'earnings': 5.0788528986176456, 'bet_amount': 4.3978899989135, 'nr_mech_calls': 8, 'roi': 0.11255319892497745}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x3c01b79bad670a37c8784bdf47b973b341064f10      0.513005  5.078853   \n",
-      "1  0x3c01b79bad670a37c8784bdf47b973b341064f10      0.513005  5.078853   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0     4.39789              8  0.112553          Jul-21            all  \n",
-      "1     4.39789              8  0.112553          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164 and market creator all = 6\n",
-      "{'trader_address': '0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164', 'net_earnings': -0.7499826129605537, 'earnings': 5.962404072727221, 'bet_amount': 6.345477142831152, 'nr_mech_calls': 24, 'roi': -0.10987988052209152}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164 and market creator quickstart = 6\n",
-      "{'trader_address': '0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164', 'net_earnings': -0.7499826129605537, 'earnings': 5.962404072727221, 'bet_amount': 6.345477142831152, 'nr_mech_calls': 24, 'roi': -0.10987988052209152}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164     -0.749983  5.962404   \n",
-      "1  0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164     -0.749983  5.962404   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls      roi month_year_week market_creator  \n",
-      "0    6.345477             24 -0.10988          Jul-21            all  \n",
-      "1    6.345477             24 -0.10988          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x8dd0f0f64e575a356545d9ed096122a1887e64bf and market creator all = 4\n",
-      "{'trader_address': '0x8dd0f0f64e575a356545d9ed096122a1887e64bf', 'net_earnings': -0.11720618783292708, 'earnings': 3.8719908166532613, 'bet_amount': 3.7639186318492035, 'nr_mech_calls': 15, 'roi': -0.028840682713077548}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x8dd0f0f64e575a356545d9ed096122a1887e64bf and market creator quickstart = 4\n",
-      "{'trader_address': '0x8dd0f0f64e575a356545d9ed096122a1887e64bf', 'net_earnings': -0.11720618783292708, 'earnings': 3.8719908166532613, 'bet_amount': 3.7639186318492035, 'nr_mech_calls': 15, 'roi': -0.028840682713077548}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x8dd0f0f64e575a356545d9ed096122a1887e64bf     -0.117206  3.871991   \n",
-      "1  0x8dd0f0f64e575a356545d9ed096122a1887e64bf     -0.117206  3.871991   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0    3.763919             15 -0.028841          Jul-21            all  \n",
-      "1    3.763919             15 -0.028841          Jul-21     quickstart  \n",
-      "Volume of data for trader 0xec97bdf61fcb901033a3b8fcbcde77a372927b61 and market creator all = 4\n",
-      "{'trader_address': '0xec97bdf61fcb901033a3b8fcbcde77a372927b61', 'net_earnings': -0.826361612049082, 'earnings': 1.876615508201772, 'bet_amount': 2.551938353187112, 'nr_mech_calls': 10, 'roi': -0.3002834751338252}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0xec97bdf61fcb901033a3b8fcbcde77a372927b61 and market creator quickstart = 4\n",
-      "{'trader_address': '0xec97bdf61fcb901033a3b8fcbcde77a372927b61', 'net_earnings': -0.826361612049082, 'earnings': 1.876615508201772, 'bet_amount': 2.551938353187112, 'nr_mech_calls': 10, 'roi': -0.3002834751338252}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0xec97bdf61fcb901033a3b8fcbcde77a372927b61     -0.826362  1.876616   \n",
-      "1  0xec97bdf61fcb901033a3b8fcbcde77a372927b61     -0.826362  1.876616   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0    2.551938             10 -0.300283          Jul-21            all  \n",
-      "1    2.551938             10 -0.300283          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x74d2b585a46279b4fa9feeae001efc972726c709 and market creator all = 1\n",
-      "{'trader_address': '0x74d2b585a46279b4fa9feeae001efc972726c709', 'net_earnings': 0.3248132469295979, 'earnings': 1.5588132469295979, 'bet_amount': 1.2, 'nr_mech_calls': 1, 'roi': 0.266240366335736}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x74d2b585a46279b4fa9feeae001efc972726c709 and market creator quickstart = 1\n",
-      "{'trader_address': '0x74d2b585a46279b4fa9feeae001efc972726c709', 'net_earnings': 0.3248132469295979, 'earnings': 1.5588132469295979, 'bet_amount': 1.2, 'nr_mech_calls': 1, 'roi': 0.266240366335736}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x74d2b585a46279b4fa9feeae001efc972726c709      0.324813  1.558813   \n",
-      "1  0x74d2b585a46279b4fa9feeae001efc972726c709      0.324813  1.558813   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls      roi month_year_week market_creator  \n",
-      "0         1.2              1  0.26624          Jul-21            all  \n",
-      "1         1.2              1  0.26624          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe and market creator all = 2\n",
-      "{'trader_address': '0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe', 'net_earnings': -0.06246427000467561, 'earnings': 0.46153572999532444, 'bet_amount': 0.2, 'nr_mech_calls': 32, 'roi': -0.07436222619604238}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe and market creator quickstart = 2\n",
-      "{'trader_address': '0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe', 'net_earnings': -0.06246427000467561, 'earnings': 0.46153572999532444, 'bet_amount': 0.2, 'nr_mech_calls': 32, 'roi': -0.07436222619604238}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe     -0.062464  0.461536   \n",
-      "1  0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe     -0.062464  0.461536   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0         0.2             32 -0.074362          Jul-21            all  \n",
-      "1         0.2             32 -0.074362          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x324267d9c6190f9bbcc126d10047eb9f761df540 and market creator all = 1\n",
-      "{'trader_address': '0x324267d9c6190f9bbcc126d10047eb9f761df540', 'net_earnings': 0.08069455409216866, 'earnings': 0.4426945540921687, 'bet_amount': 0.1, 'nr_mech_calls': 26, 'roi': 0.13015250660027203}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x324267d9c6190f9bbcc126d10047eb9f761df540 and market creator quickstart = 1\n",
-      "{'trader_address': '0x324267d9c6190f9bbcc126d10047eb9f761df540', 'net_earnings': 0.08069455409216866, 'earnings': 0.4426945540921687, 'bet_amount': 0.1, 'nr_mech_calls': 26, 'roi': 0.13015250660027203}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x324267d9c6190f9bbcc126d10047eb9f761df540      0.080695  0.442695   \n",
-      "1  0x324267d9c6190f9bbcc126d10047eb9f761df540      0.080695  0.442695   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0         0.1             26  0.130153          Jul-21            all  \n",
-      "1         0.1             26  0.130153          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b and market creator all = 2\n",
-      "{'trader_address': '0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b', 'net_earnings': -0.42400000000000004, 'earnings': 0.0, 'bet_amount': 0.2, 'nr_mech_calls': 22, 'roi': -0.6625000000000001}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b and market creator quickstart = 2\n",
-      "{'trader_address': '0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b', 'net_earnings': -0.42400000000000004, 'earnings': 0.0, 'bet_amount': 0.2, 'nr_mech_calls': 22, 'roi': -0.6625000000000001}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b        -0.424       0.0   \n",
-      "1  0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b        -0.424       0.0   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls     roi month_year_week market_creator  \n",
-      "0         0.2             22 -0.6625          Jul-21            all  \n",
-      "1         0.2             22 -0.6625          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9 and market creator all = 4\n",
-      "{'trader_address': '0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9', 'net_earnings': 1.0946011886656675, 'earnings': 5.0475474599643215, 'bet_amount': 3.7872022267633865, 'nr_mech_calls': 9, 'roi': 0.2759126271106906}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9 and market creator quickstart = 4\n",
-      "{'trader_address': '0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9', 'net_earnings': 1.0946011886656675, 'earnings': 5.0475474599643215, 'bet_amount': 3.7872022267633865, 'nr_mech_calls': 9, 'roi': 0.2759126271106906}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9      1.094601  5.047547   \n",
-      "1  0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9      1.094601  5.047547   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0    3.787202              9  0.275913          Jul-21            all  \n",
-      "1    3.787202              9  0.275913          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9 and market creator all = 1\n",
-      "{'trader_address': '0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9', 'net_earnings': 0.8096491228070175, 'earnings': 1.8396491228070175, 'bet_amount': 1.0, 'nr_mech_calls': 1, 'roi': 0.7937736498108015}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "No data. Skipping market creator quickstart\n",
-      "Filtering only specific market creators = pearl\n",
-      "Volume of data for trader 0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9 and market creator pearl = 1\n",
-      "{'trader_address': '0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9', 'net_earnings': 0.8096491228070175, 'earnings': 1.8396491228070175, 'bet_amount': 1.0, 'nr_mech_calls': 1, 'roi': 0.7937736498108015}\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9      0.809649  1.839649   \n",
-      "1  0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9      0.809649  1.839649   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0         1.0              1  0.793774          Jul-21            all  \n",
-      "1         1.0              1  0.793774          Jul-21          pearl  \n",
-      "Volume of data for trader 0x1b9e28e7f817e1312636a485f31cca8a4be61fac and market creator all = 1\n",
-      "{'trader_address': '0x1b9e28e7f817e1312636a485f31cca8a4be61fac', 'net_earnings': -1.03, 'earnings': 0.0, 'bet_amount': 1.0, 'nr_mech_calls': 1, 'roi': -1.0098039215686274}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "No data. Skipping market creator quickstart\n",
-      "Filtering only specific market creators = pearl\n",
-      "Volume of data for trader 0x1b9e28e7f817e1312636a485f31cca8a4be61fac and market creator pearl = 1\n",
-      "{'trader_address': '0x1b9e28e7f817e1312636a485f31cca8a4be61fac', 'net_earnings': -1.03, 'earnings': 0.0, 'bet_amount': 1.0, 'nr_mech_calls': 1, 'roi': -1.0098039215686274}\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x1b9e28e7f817e1312636a485f31cca8a4be61fac         -1.03       0.0   \n",
-      "1  0x1b9e28e7f817e1312636a485f31cca8a4be61fac         -1.03       0.0   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0         1.0              1 -1.009804          Jul-21            all  \n",
-      "1         1.0              1 -1.009804          Jul-21          pearl  \n",
-      "Volume of data for trader 0xe0113a139f591efa8bf5e19308c7c27199682d77 and market creator all = 2\n",
-      "{'trader_address': '0xe0113a139f591efa8bf5e19308c7c27199682d77', 'net_earnings': -2.08, 'earnings': 0.0, 'bet_amount': 2.0, 'nr_mech_calls': 4, 'roi': -1.0}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "No data. Skipping market creator quickstart\n",
-      "Filtering only specific market creators = pearl\n",
-      "Volume of data for trader 0xe0113a139f591efa8bf5e19308c7c27199682d77 and market creator pearl = 2\n",
-      "{'trader_address': '0xe0113a139f591efa8bf5e19308c7c27199682d77', 'net_earnings': -2.08, 'earnings': 0.0, 'bet_amount': 2.0, 'nr_mech_calls': 4, 'roi': -1.0}\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0xe0113a139f591efa8bf5e19308c7c27199682d77         -2.08       0.0   \n",
-      "1  0xe0113a139f591efa8bf5e19308c7c27199682d77         -2.08       0.0   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls  roi month_year_week market_creator  \n",
-      "0         2.0              4 -1.0          Jul-21            all  \n",
-      "1         2.0              4 -1.0          Jul-21          pearl  \n",
-      "Volume of data for trader 0x9694c0fdb79a37d048ea19deb15e051482a690c4 and market creator all = 2\n",
-      "{'trader_address': '0x9694c0fdb79a37d048ea19deb15e051482a690c4', 'net_earnings': -0.34400000000000003, 'earnings': 0.0, 'bet_amount': 0.2, 'nr_mech_calls': 14, 'roi': -0.7166666666666667}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "Volume of data for trader 0x9694c0fdb79a37d048ea19deb15e051482a690c4 and market creator quickstart = 2\n",
-      "{'trader_address': '0x9694c0fdb79a37d048ea19deb15e051482a690c4', 'net_earnings': -0.34400000000000003, 'earnings': 0.0, 'bet_amount': 0.2, 'nr_mech_calls': 14, 'roi': -0.7166666666666667}\n",
-      "Filtering only specific market creators = pearl\n",
-      "No data. Skipping market creator pearl\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings  earnings  \\\n",
-      "0  0x9694c0fdb79a37d048ea19deb15e051482a690c4        -0.344       0.0   \n",
-      "1  0x9694c0fdb79a37d048ea19deb15e051482a690c4        -0.344       0.0   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-      "0         0.2             14 -0.716667          Jul-21            all  \n",
-      "1         0.2             14 -0.716667          Jul-21     quickstart  \n",
-      "Volume of data for trader 0x66a022b113b41e08d90cfd9468b8b6565d6ea995 and market creator all = 1\n",
-      "{'trader_address': '0x66a022b113b41e08d90cfd9468b8b6565d6ea995', 'net_earnings': 3.6733333333333356, 'earnings': 13.883333333333335, 'bet_amount': 10.0, 'nr_mech_calls': 1, 'roi': 0.3666001330671992}\n",
-      "Filtering only specific market creators = quickstart\n",
-      "No data. Skipping market creator quickstart\n",
-      "Filtering only specific market creators = pearl\n",
-      "Volume of data for trader 0x66a022b113b41e08d90cfd9468b8b6565d6ea995 and market creator pearl = 1\n",
-      "{'trader_address': '0x66a022b113b41e08d90cfd9468b8b6565d6ea995', 'net_earnings': 3.6733333333333356, 'earnings': 13.883333333333335, 'bet_amount': 10.0, 'nr_mech_calls': 1, 'roi': 0.3666001330671992}\n",
-      "Total length of all trader metrics for this week = 2\n",
-      "                               trader_address  net_earnings   earnings  \\\n",
-      "0  0x66a022b113b41e08d90cfd9468b8b6565d6ea995      3.673333  13.883333   \n",
-      "1  0x66a022b113b41e08d90cfd9468b8b6565d6ea995      3.673333  13.883333   \n",
-      "\n",
-      "   bet_amount  nr_mech_calls     roi month_year_week market_creator  \n",
-      "0        10.0              1  0.3666          Jul-21            all  \n",
-      "1        10.0              1  0.3666          Jul-21          pearl  \n",
-      "End computing all weekly metrics by market creator\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<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>net_earnings</th>\n",
-       "      <th>earnings</th>\n",
-       "      <th>bet_amount</th>\n",
-       "      <th>nr_mech_calls</th>\n",
-       "      <th>roi</th>\n",
-       "      <th>month_year_week</th>\n",
-       "      <th>market_creator</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57</td>\n",
-       "      <td>-0.723411</td>\n",
-       "      <td>1.785135</td>\n",
-       "      <td>2.380927</td>\n",
-       "      <td>8</td>\n",
-       "      <td>-0.284704</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57</td>\n",
-       "      <td>-0.723411</td>\n",
-       "      <td>1.785135</td>\n",
-       "      <td>2.380927</td>\n",
-       "      <td>8</td>\n",
-       "      <td>-0.284704</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0xf089874165be0377680683fd5187a058dea82683</td>\n",
-       "      <td>0.799649</td>\n",
-       "      <td>1.839649</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0.768893</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0xf089874165be0377680683fd5187a058dea82683</td>\n",
-       "      <td>0.799649</td>\n",
-       "      <td>1.839649</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0.768893</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2</td>\n",
-       "      <td>-1.007165</td>\n",
-       "      <td>3.350264</td>\n",
-       "      <td>4.154342</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-0.229196</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2</td>\n",
-       "      <td>-1.007165</td>\n",
-       "      <td>3.350264</td>\n",
-       "      <td>4.154342</td>\n",
-       "      <td>12</td>\n",
-       "      <td>-0.229196</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>0xe283e408c6017447da9fe092d52c386753699680</td>\n",
-       "      <td>-1.040000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>0xe283e408c6017447da9fe092d52c386753699680</td>\n",
-       "      <td>-1.040000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>0x480e5b5abd27cd754745871116e79caf90468dd4</td>\n",
-       "      <td>-0.367948</td>\n",
-       "      <td>1.964669</td>\n",
-       "      <td>2.247663</td>\n",
-       "      <td>4</td>\n",
-       "      <td>-0.158076</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>0x480e5b5abd27cd754745871116e79caf90468dd4</td>\n",
-       "      <td>-0.367948</td>\n",
-       "      <td>1.964669</td>\n",
-       "      <td>2.247663</td>\n",
-       "      <td>4</td>\n",
-       "      <td>-0.158076</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>0x3c01b79bad670a37c8784bdf47b973b341064f10</td>\n",
-       "      <td>0.513005</td>\n",
-       "      <td>5.078853</td>\n",
-       "      <td>4.397890</td>\n",
-       "      <td>8</td>\n",
-       "      <td>0.112553</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>0x3c01b79bad670a37c8784bdf47b973b341064f10</td>\n",
-       "      <td>0.513005</td>\n",
-       "      <td>5.078853</td>\n",
-       "      <td>4.397890</td>\n",
-       "      <td>8</td>\n",
-       "      <td>0.112553</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164</td>\n",
-       "      <td>-0.749983</td>\n",
-       "      <td>5.962404</td>\n",
-       "      <td>6.345477</td>\n",
-       "      <td>24</td>\n",
-       "      <td>-0.109880</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164</td>\n",
-       "      <td>-0.749983</td>\n",
-       "      <td>5.962404</td>\n",
-       "      <td>6.345477</td>\n",
-       "      <td>24</td>\n",
-       "      <td>-0.109880</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>0x8dd0f0f64e575a356545d9ed096122a1887e64bf</td>\n",
-       "      <td>-0.117206</td>\n",
-       "      <td>3.871991</td>\n",
-       "      <td>3.763919</td>\n",
-       "      <td>15</td>\n",
-       "      <td>-0.028841</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>0x8dd0f0f64e575a356545d9ed096122a1887e64bf</td>\n",
-       "      <td>-0.117206</td>\n",
-       "      <td>3.871991</td>\n",
-       "      <td>3.763919</td>\n",
-       "      <td>15</td>\n",
-       "      <td>-0.028841</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>0xec97bdf61fcb901033a3b8fcbcde77a372927b61</td>\n",
-       "      <td>-0.826362</td>\n",
-       "      <td>1.876616</td>\n",
-       "      <td>2.551938</td>\n",
-       "      <td>10</td>\n",
-       "      <td>-0.300283</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>0xec97bdf61fcb901033a3b8fcbcde77a372927b61</td>\n",
-       "      <td>-0.826362</td>\n",
-       "      <td>1.876616</td>\n",
-       "      <td>2.551938</td>\n",
-       "      <td>10</td>\n",
-       "      <td>-0.300283</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>0x74d2b585a46279b4fa9feeae001efc972726c709</td>\n",
-       "      <td>0.324813</td>\n",
-       "      <td>1.558813</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.266240</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>0x74d2b585a46279b4fa9feeae001efc972726c709</td>\n",
-       "      <td>0.324813</td>\n",
-       "      <td>1.558813</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.266240</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe</td>\n",
-       "      <td>-0.062464</td>\n",
-       "      <td>0.461536</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>32</td>\n",
-       "      <td>-0.074362</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>21</th>\n",
-       "      <td>0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe</td>\n",
-       "      <td>-0.062464</td>\n",
-       "      <td>0.461536</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>32</td>\n",
-       "      <td>-0.074362</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>0x324267d9c6190f9bbcc126d10047eb9f761df540</td>\n",
-       "      <td>0.080695</td>\n",
-       "      <td>0.442695</td>\n",
-       "      <td>0.100000</td>\n",
-       "      <td>26</td>\n",
-       "      <td>0.130153</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>0x324267d9c6190f9bbcc126d10047eb9f761df540</td>\n",
-       "      <td>0.080695</td>\n",
-       "      <td>0.442695</td>\n",
-       "      <td>0.100000</td>\n",
-       "      <td>26</td>\n",
-       "      <td>0.130153</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b</td>\n",
-       "      <td>-0.424000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>22</td>\n",
-       "      <td>-0.662500</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b</td>\n",
-       "      <td>-0.424000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>22</td>\n",
-       "      <td>-0.662500</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>26</th>\n",
-       "      <td>0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9</td>\n",
-       "      <td>1.094601</td>\n",
-       "      <td>5.047547</td>\n",
-       "      <td>3.787202</td>\n",
-       "      <td>9</td>\n",
-       "      <td>0.275913</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9</td>\n",
-       "      <td>1.094601</td>\n",
-       "      <td>5.047547</td>\n",
-       "      <td>3.787202</td>\n",
-       "      <td>9</td>\n",
-       "      <td>0.275913</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9</td>\n",
-       "      <td>0.809649</td>\n",
-       "      <td>1.839649</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.793774</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9</td>\n",
-       "      <td>0.809649</td>\n",
-       "      <td>1.839649</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.793774</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>30</th>\n",
-       "      <td>0x1b9e28e7f817e1312636a485f31cca8a4be61fac</td>\n",
-       "      <td>-1.030000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1</td>\n",
-       "      <td>-1.009804</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>31</th>\n",
-       "      <td>0x1b9e28e7f817e1312636a485f31cca8a4be61fac</td>\n",
-       "      <td>-1.030000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1</td>\n",
-       "      <td>-1.009804</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32</th>\n",
-       "      <td>0xe0113a139f591efa8bf5e19308c7c27199682d77</td>\n",
-       "      <td>-2.080000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>4</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>33</th>\n",
-       "      <td>0xe0113a139f591efa8bf5e19308c7c27199682d77</td>\n",
-       "      <td>-2.080000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>4</td>\n",
-       "      <td>-1.000000</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>34</th>\n",
-       "      <td>0x9694c0fdb79a37d048ea19deb15e051482a690c4</td>\n",
-       "      <td>-0.344000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>14</td>\n",
-       "      <td>-0.716667</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>35</th>\n",
-       "      <td>0x9694c0fdb79a37d048ea19deb15e051482a690c4</td>\n",
-       "      <td>-0.344000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>14</td>\n",
-       "      <td>-0.716667</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>36</th>\n",
-       "      <td>0x66a022b113b41e08d90cfd9468b8b6565d6ea995</td>\n",
-       "      <td>3.673333</td>\n",
-       "      <td>13.883333</td>\n",
-       "      <td>10.000000</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.366600</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>37</th>\n",
-       "      <td>0x66a022b113b41e08d90cfd9468b8b6565d6ea995</td>\n",
-       "      <td>3.673333</td>\n",
-       "      <td>13.883333</td>\n",
-       "      <td>10.000000</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.366600</td>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                trader_address  net_earnings   earnings  \\\n",
-       "0   0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57     -0.723411   1.785135   \n",
-       "1   0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57     -0.723411   1.785135   \n",
-       "2   0xf089874165be0377680683fd5187a058dea82683      0.799649   1.839649   \n",
-       "3   0xf089874165be0377680683fd5187a058dea82683      0.799649   1.839649   \n",
-       "4   0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2     -1.007165   3.350264   \n",
-       "5   0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2     -1.007165   3.350264   \n",
-       "6   0xe283e408c6017447da9fe092d52c386753699680     -1.040000   0.000000   \n",
-       "7   0xe283e408c6017447da9fe092d52c386753699680     -1.040000   0.000000   \n",
-       "8   0x480e5b5abd27cd754745871116e79caf90468dd4     -0.367948   1.964669   \n",
-       "9   0x480e5b5abd27cd754745871116e79caf90468dd4     -0.367948   1.964669   \n",
-       "10  0x3c01b79bad670a37c8784bdf47b973b341064f10      0.513005   5.078853   \n",
-       "11  0x3c01b79bad670a37c8784bdf47b973b341064f10      0.513005   5.078853   \n",
-       "12  0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164     -0.749983   5.962404   \n",
-       "13  0x8cd3e072c8341cfe1a03dbe1d6c32b5177b06164     -0.749983   5.962404   \n",
-       "14  0x8dd0f0f64e575a356545d9ed096122a1887e64bf     -0.117206   3.871991   \n",
-       "15  0x8dd0f0f64e575a356545d9ed096122a1887e64bf     -0.117206   3.871991   \n",
-       "16  0xec97bdf61fcb901033a3b8fcbcde77a372927b61     -0.826362   1.876616   \n",
-       "17  0xec97bdf61fcb901033a3b8fcbcde77a372927b61     -0.826362   1.876616   \n",
-       "18  0x74d2b585a46279b4fa9feeae001efc972726c709      0.324813   1.558813   \n",
-       "19  0x74d2b585a46279b4fa9feeae001efc972726c709      0.324813   1.558813   \n",
-       "20  0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe     -0.062464   0.461536   \n",
-       "21  0x22335c348afa4eae4cc6d2158c1ac259aaaecdfe     -0.062464   0.461536   \n",
-       "22  0x324267d9c6190f9bbcc126d10047eb9f761df540      0.080695   0.442695   \n",
-       "23  0x324267d9c6190f9bbcc126d10047eb9f761df540      0.080695   0.442695   \n",
-       "24  0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b     -0.424000   0.000000   \n",
-       "25  0x6f99ccc54f239a9c0e7fe501e99c16b89785b96b     -0.424000   0.000000   \n",
-       "26  0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9      1.094601   5.047547   \n",
-       "27  0x593c4ca4c85f24145de87e2591b7ec5d2e01d5e9      1.094601   5.047547   \n",
-       "28  0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9      0.809649   1.839649   \n",
-       "29  0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9      0.809649   1.839649   \n",
-       "30  0x1b9e28e7f817e1312636a485f31cca8a4be61fac     -1.030000   0.000000   \n",
-       "31  0x1b9e28e7f817e1312636a485f31cca8a4be61fac     -1.030000   0.000000   \n",
-       "32  0xe0113a139f591efa8bf5e19308c7c27199682d77     -2.080000   0.000000   \n",
-       "33  0xe0113a139f591efa8bf5e19308c7c27199682d77     -2.080000   0.000000   \n",
-       "34  0x9694c0fdb79a37d048ea19deb15e051482a690c4     -0.344000   0.000000   \n",
-       "35  0x9694c0fdb79a37d048ea19deb15e051482a690c4     -0.344000   0.000000   \n",
-       "36  0x66a022b113b41e08d90cfd9468b8b6565d6ea995      3.673333  13.883333   \n",
-       "37  0x66a022b113b41e08d90cfd9468b8b6565d6ea995      3.673333  13.883333   \n",
-       "\n",
-       "    bet_amount  nr_mech_calls       roi month_year_week market_creator  \n",
-       "0     2.380927              8 -0.284704          Jul-21            all  \n",
-       "1     2.380927              8 -0.284704          Jul-21     quickstart  \n",
-       "2     1.000000              2  0.768893          Jul-21            all  \n",
-       "3     1.000000              2  0.768893          Jul-21     quickstart  \n",
-       "4     4.154342             12 -0.229196          Jul-21            all  \n",
-       "5     4.154342             12 -0.229196          Jul-21     quickstart  \n",
-       "6     1.000000              2 -1.000000          Jul-21            all  \n",
-       "7     1.000000              2 -1.000000          Jul-21          pearl  \n",
-       "8     2.247663              4 -0.158076          Jul-21            all  \n",
-       "9     2.247663              4 -0.158076          Jul-21     quickstart  \n",
-       "10    4.397890              8  0.112553          Jul-21            all  \n",
-       "11    4.397890              8  0.112553          Jul-21     quickstart  \n",
-       "12    6.345477             24 -0.109880          Jul-21            all  \n",
-       "13    6.345477             24 -0.109880          Jul-21     quickstart  \n",
-       "14    3.763919             15 -0.028841          Jul-21            all  \n",
-       "15    3.763919             15 -0.028841          Jul-21     quickstart  \n",
-       "16    2.551938             10 -0.300283          Jul-21            all  \n",
-       "17    2.551938             10 -0.300283          Jul-21     quickstart  \n",
-       "18    1.200000              1  0.266240          Jul-21            all  \n",
-       "19    1.200000              1  0.266240          Jul-21     quickstart  \n",
-       "20    0.200000             32 -0.074362          Jul-21            all  \n",
-       "21    0.200000             32 -0.074362          Jul-21     quickstart  \n",
-       "22    0.100000             26  0.130153          Jul-21            all  \n",
-       "23    0.100000             26  0.130153          Jul-21     quickstart  \n",
-       "24    0.200000             22 -0.662500          Jul-21            all  \n",
-       "25    0.200000             22 -0.662500          Jul-21     quickstart  \n",
-       "26    3.787202              9  0.275913          Jul-21            all  \n",
-       "27    3.787202              9  0.275913          Jul-21     quickstart  \n",
-       "28    1.000000              1  0.793774          Jul-21            all  \n",
-       "29    1.000000              1  0.793774          Jul-21          pearl  \n",
-       "30    1.000000              1 -1.009804          Jul-21            all  \n",
-       "31    1.000000              1 -1.009804          Jul-21          pearl  \n",
-       "32    2.000000              4 -1.000000          Jul-21            all  \n",
-       "33    2.000000              4 -1.000000          Jul-21          pearl  \n",
-       "34    0.200000             14 -0.716667          Jul-21            all  \n",
-       "35    0.200000             14 -0.716667          Jul-21     quickstart  \n",
-       "36   10.000000              1  0.366600          Jul-21            all  \n",
-       "37   10.000000              1  0.366600          Jul-21          pearl  "
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "compute_weekly_metrics_by_market_creator(trader_agent_metrics)"
    ]

notebooks/winning_perc.ipynb

@@ -2,11 +2,14 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas as pd"
+    "import pandas as pd\n",
+    "import sys\n",
+    "sys.path.append('..')\n",
+    "from scripts.metrics import compute_weekly_metrics_by_market_creator"
    ]
   },
   {
@@ -18,39 +21,6 @@
     "all_trades = pd.read_parquet('../data/all_trades_profitability.parquet')"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "all_trades[\"creation_date\"] = all_trades[\"creation_timestamp\"].dt.date"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/gp/02mb1d514ng739czlxw1lhh00000gn/T/ipykernel_38171/1825242321.py:6: 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 = all_trades.sort_values(\n",
-    "    by=\"creation_timestamp\", ascending=True\n",
-    ")\n",
-    "\n",
-    "all_trades[\"month_year_week\"] = (\n",
-    "    all_trades[\"creation_timestamp\"].dt.to_period(\"W\").dt.strftime(\"%b-%d\")\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -153,97 +123,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "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>month_year_week</th>\n",
-       "      <th>market_creator</th>\n",
-       "      <th>trader_address</th>\n",
-       "      <th>winning_trade</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "      <td>0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57</td>\n",
-       "      <td>33.333333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "      <td>0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57</td>\n",
-       "      <td>33.333333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "      <td>0xf089874165be0377680683fd5187a058dea82683</td>\n",
-       "      <td>100.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>all</td>\n",
-       "      <td>0xf089874165be0377680683fd5187a058dea82683</td>\n",
-       "      <td>100.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>quickstart</td>\n",
-       "      <td>0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2</td>\n",
-       "      <td>50.000000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "  month_year_week market_creator                              trader_address  \\\n",
-       "0          Jul-21            all  0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57   \n",
-       "1          Jul-21     quickstart  0x95ecc70d9f4feb162ed9f41c4432d990c36c8f57   \n",
-       "2          Jul-21     quickstart  0xf089874165be0377680683fd5187a058dea82683   \n",
-       "3          Jul-21            all  0xf089874165be0377680683fd5187a058dea82683   \n",
-       "4          Jul-21     quickstart  0x49f4e3d8edc85efda9b0a36d96e406a59b13fcc2   \n",
-       "\n",
-       "   winning_trade  \n",
-       "0      33.333333  \n",
-       "1      33.333333  \n",
-       "2     100.000000  \n",
-       "3     100.000000  \n",
-       "4      50.000000  "
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from tqdm import tqdm\n",
     "\n",
@@ -280,97 +162,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "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>month_year_week</th>\n",
-       "      <th>market_creator</th>\n",
-       "      <th>trader_address</th>\n",
-       "      <th>winning_trade</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "      <td>0xe283e408c6017447da9fe092d52c386753699680</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "      <td>0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9</td>\n",
-       "      <td>100.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>30</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "      <td>0x1b9e28e7f817e1312636a485f31cca8a4be61fac</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>33</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "      <td>0xe0113a139f591efa8bf5e19308c7c27199682d77</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>37</th>\n",
-       "      <td>Jul-21</td>\n",
-       "      <td>pearl</td>\n",
-       "      <td>0x66a022b113b41e08d90cfd9468b8b6565d6ea995</td>\n",
-       "      <td>100.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   month_year_week market_creator                              trader_address  \\\n",
-       "7           Jul-21          pearl  0xe283e408c6017447da9fe092d52c386753699680   \n",
-       "29          Jul-21          pearl  0x913dedfcfb335a49509b67acb3b1ab2612a5c0c9   \n",
-       "30          Jul-21          pearl  0x1b9e28e7f817e1312636a485f31cca8a4be61fac   \n",
-       "33          Jul-21          pearl  0xe0113a139f591efa8bf5e19308c7c27199682d77   \n",
-       "37          Jul-21          pearl  0x66a022b113b41e08d90cfd9468b8b6565d6ea995   \n",
-       "\n",
-       "    winning_trade  \n",
-       "7             0.0  \n",
-       "29          100.0  \n",
-       "30            0.0  \n",
-       "33            0.0  \n",
-       "37          100.0  "
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "winning_pearl.head()"
    ]

scripts/metrics.py

@@ -4,7 +4,9 @@ from tqdm import tqdm
 DEFAULT_MECH_FEE = 0.01  # xDAI
 
 
-def compute_metrics(trader_address: str, trader_data: pd.DataFrame) -> dict:
+def compute_metrics(
+    trader_address: str, trader_data: pd.DataFrame, live_metrics: bool = False
+) -> dict:
 
     if len(trader_data) == 0:
         # print("No data to compute metrics")
@@ -12,13 +14,16 @@ def compute_metrics(trader_address: str, trader_data: pd.DataFrame) -> dict:
 
     agg_metrics = {}
     agg_metrics["trader_address"] = trader_address
-    total_net_earnings = trader_data.net_earnings.sum()
     total_bet_amounts = trader_data.collateral_amount.sum()
     total_num_mech_calls = trader_data.num_mech_calls.sum()
-    agg_metrics["net_earnings"] = total_net_earnings
-    agg_metrics["earnings"] = trader_data.earnings.sum()
     agg_metrics["bet_amount"] = total_bet_amounts
     agg_metrics["nr_mech_calls"] = total_num_mech_calls
+    agg_metrics["staking"] = trader_data.iloc[0].staking
+    if live_metrics:
+        return agg_metrics
+    total_net_earnings = trader_data.net_earnings.sum()
+    agg_metrics["net_earnings"] = total_net_earnings
+    agg_metrics["earnings"] = trader_data.earnings.sum()
     agg_metrics["nr_trades"] = len(trader_data)
     total_fee_amounts = trader_data.mech_fee_amount.sum()
     total_costs = (
@@ -31,7 +36,10 @@ def compute_metrics(trader_address: str, trader_data: pd.DataFrame) -> dict:
 
 
 def compute_trader_metrics_by_market_creator(
-    trader_address: str, traders_data: pd.DataFrame, market_creator: str = "all"
+    trader_address: str,
+    traders_data: pd.DataFrame,
+    market_creator: str = "all",
+    live_metrics: bool = False,
 ) -> dict:
     """This function computes for a specific time window (week or day) the different metrics:
     roi, net_earnings, earnings, bet_amount, nr_mech_calls and nr_trades.
@@ -50,7 +58,7 @@ def compute_trader_metrics_by_market_creator(
             # tqdm.write(f"No data. Skipping market creator {market_creator}")
             return {}  # No Data
 
-    metrics = compute_metrics(trader_address, filtered_traders_data)
+    metrics = compute_metrics(trader_address, filtered_traders_data, live_metrics)
     return metrics
 
 
@@ -112,20 +120,21 @@ def merge_trader_weekly_metrics(
 
 
 def merge_trader_daily_metrics(
-    trader: str, daily_data: pd.DataFrame, day: str
+    trader: str, daily_data: pd.DataFrame, day: str, live_metrics: bool = False
 ) -> pd.DataFrame:
     trader_metrics = []
     # computation as specification 1 for all types of markets
     daily_metrics_all = compute_trader_metrics_by_market_creator(
-        trader, daily_data, market_creator="all"
+        trader, daily_data, market_creator="all", live_metrics=live_metrics
     )
     daily_metrics_all["creation_date"] = day
+    # staking label is at the trader level
     daily_metrics_all["market_creator"] = "all"
     trader_metrics.append(daily_metrics_all)
 
     # computation as specification 1 for quickstart markets
     daily_metrics_qs = compute_trader_metrics_by_market_creator(
-        trader, daily_data, market_creator="quickstart"
+        trader, daily_data, market_creator="quickstart", live_metrics=live_metrics
     )
     if len(daily_metrics_qs) > 0:
         daily_metrics_qs["creation_date"] = day
@@ -133,7 +142,7 @@ def merge_trader_daily_metrics(
         trader_metrics.append(daily_metrics_qs)
     # computation as specification 1 for pearl markets
     daily_metrics_pearl = compute_trader_metrics_by_market_creator(
-        trader, daily_data, market_creator="pearl"
+        trader, daily_data, market_creator="pearl", live_metrics=live_metrics
     )
     if len(daily_metrics_pearl) > 0:
         daily_metrics_pearl["creation_date"] = day
@@ -193,32 +202,35 @@ def compute_weekly_metrics_by_market_creator(
 
 
 def compute_daily_metrics_by_market_creator(
-    trader_agents_data: pd.DataFrame, trader_filter: str = None
+    trader_agents_data: pd.DataFrame,
+    trader_filter: str = None,
+    live_metrics: bool = False,
 ) -> pd.DataFrame:
     """Function to compute the metrics at the trader level per day
     and with different categories by market creator"""
     contents = []
-    # trader_agents_data is already sorted by timestamp, so last item is last week
-    last_week = trader_agents_data.iloc[-1].month_year_week
-    print(f"Computing daily metrics for week ={last_week} by market creator")
-    last_week_data = trader_agents_data.loc[
-        trader_agents_data["month_year_week"] == last_week
-    ]
-    all_days = list(last_week_data.creation_date.unique())
+
+    all_days = list(trader_agents_data.creation_date.unique())
     for day in all_days:
-        daily_data = last_week_data.loc[last_week_data["creation_date"] == day]
+        daily_data = trader_agents_data.loc[trader_agents_data["creation_date"] == day]
         print(f"Computing daily metrics for {day}")
         # traverse each trader agent
         traders = list(daily_data.trader_address.unique())
         for trader in tqdm(traders, desc=f"Trader' daily metrics", unit="metrics"):
             if trader_filter is None:
-                contents.append(merge_trader_daily_metrics(trader, daily_data, day))
+                contents.append(
+                    merge_trader_daily_metrics(trader, daily_data, day, live_metrics)
+                )
             elif trader_filter == "agentic":
                 filtered_data = daily_data.loc[daily_data["staking"] != "non_agent"]
-                contents.append(merge_trader_daily_metrics(trader, filtered_data, day))
+                contents.append(
+                    merge_trader_daily_metrics(trader, filtered_data, day, live_metrics)
+                )
             else:  # non_agent traders
                 filtered_data = daily_data.loc[daily_data["staking"] == "non_agent"]
-                contents.append(merge_trader_daily_metrics(trader, filtered_data, day))
+                contents.append(
+                    merge_trader_daily_metrics(trader, filtered_data, day, live_metrics)
+                )
     print("End computing all daily metrics by market creator")
     return pd.concat(contents, ignore_index=True)
 

tabs/daily_graphs.py

@@ -0,0 +1,217 @@
+import pandas as pd
+import gradio as gr
+import gc
+import plotly.express as px
+from plotly.subplots import make_subplots
+import plotly.graph_objects as go
+from datetime import datetime, timedelta
+from tqdm import tqdm
+
+
+def plot_daily_trades(trades_df: pd.DataFrame) -> gr.Plot:
+    # get daily trades
+    daily_trades_count = (
+        trades_df.groupby("month_year_week").size().reset_index(name="trades")
+    )
+    daily_trades_count.columns = daily_trades_count.columns.astype(str)
+    print("WIP")
+
+
+def get_current_week_data(trades_df: pd.DataFrame) -> pd.DataFrame:
+    # Get current date
+    now = datetime.now()
+
+    # Get start of the current week (Monday)
+    start_of_week = now - timedelta(days=now.weekday())
+    start_of_week = start_of_week.replace(hour=0, minute=0, second=0, microsecond=0)
+    print(f"start of the week = {start_of_week}")
+
+    # Get end of the current week (Sunday)
+    end_of_week = start_of_week + timedelta(days=6)
+    end_of_week = end_of_week.replace(hour=23, minute=59, second=59, microsecond=999999)
+    print(f"end of the week = {end_of_week}")
+    trades_df["creation_date"] = pd.to_datetime(trades_df["creation_date"])
+    # Filter the dataframe
+    return trades_df[
+        (trades_df["creation_date"] >= start_of_week)
+        & (trades_df["creation_date"] <= end_of_week)
+    ]
+
+
+def get_boxplot_daily_metrics(
+    column_name: str, trades_df: pd.DataFrame
+) -> pd.DataFrame:
+    trades_filtered = trades_df[
+        [
+            "creation_timestamp",
+            "creation_date",
+            "market_creator",
+            "trader_address",
+            "staking",
+            column_name,
+        ]
+    ]
+
+    # adding the total
+    trades_filtered_all = trades_filtered.copy(deep=True)
+    trades_filtered_all["market_creator"] = "all"
+
+    # merging both dataframes
+    all_filtered_trades = pd.concat(
+        [trades_filtered, trades_filtered_all], ignore_index=True
+    )
+    all_filtered_trades = all_filtered_trades.sort_values(
+        by="creation_timestamp", ascending=True
+    )
+    gc.collect()
+    return all_filtered_trades
+
+
+def plot_daily_metrics(
+    metric_name: str, trades_df: pd.DataFrame, trader_filter: str = None
+) -> gr.Plot:
+    """Plots the trade metrics."""
+
+    if metric_name == "mech calls":
+        metric_name = "mech_calls"
+        column_name = "num_mech_calls"
+        yaxis_title = "Nr of mech calls per trade"
+    elif metric_name == "ROI":
+        column_name = "roi"
+        yaxis_title = "ROI (net profit/cost)"
+    elif metric_name == "collateral amount":
+        metric_name = "bet_amount"
+        column_name = metric_name
+        yaxis_title = "Collateral amount per trade (xDAI)"
+    elif metric_name == "net earnings":
+        metric_name = "net_earnings"
+        column_name = metric_name
+        yaxis_title = "Net profit per trade (xDAI)"
+    else:  # earnings
+        column_name = metric_name
+        yaxis_title = "Gross profit per trade (xDAI)"
+
+    if trader_filter == "agent":
+        trades_filtered = trades_df.loc[trades_df["staking"] != "non_agent"]
+    elif trader_filter == "non_agent":
+        trades_filtered = trades_df.loc[trades_df["staking"] == "non_agent"]
+    else:
+        trades_filtered = trades_df
+    color_mapping = [
+        "darkviolet",
+        "purple",
+        "goldenrod",
+        "darkgoldenrod",
+        "green",
+        "darkgreen",
+    ]
+
+    # Create binary staking category
+    trades_filtered["trader_type"] = trades_filtered["staking"].apply(
+        lambda x: "non_agent" if x == "non_agent" else "agent"
+    )
+    trades_filtered["trader_market"] = trades_filtered.apply(
+        lambda x: (x["trader_type"], x["market_creator"]), axis=1
+    )
+    fig = px.box(
+        trades_filtered,
+        x="creation_date",
+        y=column_name,
+        color="trader_market",
+        color_discrete_sequence=color_mapping,
+        category_orders={
+            "market_creator": ["pearl", "quickstart", "all"],
+            "trader_market": [
+                ("agent", "pearl"),
+                ("non_agent", "pearl"),
+                ("agent", "quickstart"),
+                ("non_agent", "quickstart"),
+                ("agent", "all"),
+                ("non_agent", "all"),
+            ],
+        },
+        facet_col="market_creator",
+    )
+    fig.update_traces(boxmean=True)
+    fig.update_layout(
+        xaxis_title="Day",
+        yaxis_title=yaxis_title,
+        legend=dict(yanchor="top", y=0.5),
+    )
+    for axis in fig.layout:
+        if axis.startswith("xaxis"):
+            fig.layout[axis].update(title="Day")
+    fig.update_xaxes(tickformat="%b %d")
+    return gr.Plot(
+        value=fig,
+    )
+
+
+def plot_daily_metrics_v2(
+    metric_name: str, trades_df: pd.DataFrame, trader_filter: str = None
+) -> gr.Plot:
+    """Plots the trade metrics."""
+
+    if metric_name == "mech calls":
+        metric_name = "mech_calls"
+        column_name = "num_mech_calls"
+        yaxis_title = "Nr of mech calls per trade"
+    elif metric_name == "ROI":
+        column_name = "roi"
+        yaxis_title = "ROI (net profit/cost)"
+    elif metric_name == "collateral amount":
+        metric_name = "collateral_amount"
+        column_name = metric_name
+        yaxis_title = "Collateral amount per trade (xDAI)"
+    elif metric_name == "net earnings":
+        metric_name = "net_earnings"
+        column_name = metric_name
+        yaxis_title = "Net profit per trade (xDAI)"
+    else:  # earnings
+        column_name = metric_name
+        yaxis_title = "Gross profit per trade (xDAI)"
+
+    color_discrete = ["purple", "darkgoldenrod", "darkgreen"]
+    trades_filtered = get_boxplot_daily_metrics(column_name, trades_df)
+    fig = make_subplots(rows=1, cols=2, subplot_titles=("Agent", "Non-Agents"))
+
+    # Create first boxplot for staking=True
+    fig.add_trace(
+        go.Box(
+            x=trades_filtered[trades_filtered["staking"] != "non_agent"][
+                "creation_date"
+            ],
+            y=trades_filtered[trades_filtered["staking"] != "non_agent"][column_name],
+            name="Trades from agents",
+            marker_color=color_discrete[0],
+            legendgroup="staking_true",
+            showlegend=True,
+        ),
+        row=1,
+        col=1,
+    )
+
+    # Create second boxplot for staking=False
+    fig.add_trace(
+        go.Box(
+            x=trades_filtered[trades_filtered["staking"] == False]["creation_date"],
+            y=trades_filtered[trades_filtered["staking"] == False][column_name],
+            name="Staking False",
+            marker_color=color_discrete[1],
+            legendgroup="staking_false",
+            showlegend=True,
+        ),
+        row=1,
+        col=2,
+    )
+
+    # Update layout
+    fig.update_layout(
+        height=600,
+        width=1200,
+        title_text=f"Box Plot of {column_name} by Staking Status",
+        showlegend=True,
+    )
+
+    # Update y-axes to have the same range
+    fig.update_yaxes(matches="y")

tabs/trader_plots.py

@@ -12,6 +12,12 @@ trader_metric_choices = [
 ]
 default_trader_metric = "ROI"
 
+trade_daily_metric_choices = [
+    "mech calls",
+    "collateral amount",
+]
+default_daily_metric = "collateral amount"
+
 
 def get_metrics_text() -> gr.Markdown:
     metric_text = """