new labels for traders

app.py

@@ -77,14 +77,21 @@ def get_all_data():
     FROM read_parquet('./data/daily_info.parquet')
     """
     df3 = con.execute(query3).fetchdf()
+
+    # Query to fetch daily live data of unknown daily traders
+    query4 = f"""
+    SELECT *
+    FROM read_parquet('./data/unknown_traders.parquet')
+    """
+    df4 = con.execute(query4).fetchdf()
     con.close()
 
-    return df1, df2, df3
+    return df1, df2, df3, df4
 
 
 def prepare_data():
 
-    all_trades, closed_markets, daily_info = get_all_data()
+    all_trades, closed_markets, daily_info, unknown_traders = get_all_data()
 
     all_trades["creation_date"] = all_trades["creation_timestamp"].dt.date
 
@@ -99,6 +106,7 @@ def prepare_data():
         all_trades, volume_trades_per_trader_and_market, on=["trader_address", "title"]
     )
     daily_info["creation_date"] = daily_info["creation_timestamp"].dt.date
+    unknown_traders["creation_date"] = unknown_traders["creation_timestamp"].dt.date
     # adding the trader family column
     traders_data["trader_family"] = traders_data.apply(
         lambda x: get_traders_family(x), axis=1
@@ -106,29 +114,28 @@ def prepare_data():
     print(traders_data.head())
 
     traders_data = traders_data.sort_values(by="creation_timestamp", ascending=True)
-
+    unknown_traders = unknown_traders.sort_values(
+        by="creation_timestamp", ascending=True
+    )
     traders_data["month_year_week"] = (
         traders_data["creation_timestamp"].dt.to_period("W").dt.strftime("%b-%d")
     )
-
+    unknown_traders["month_year_week"] = (
+        unknown_traders["creation_timestamp"].dt.to_period("W").dt.strftime("%b-%d")
+    )
     closed_markets["month_year_week"] = (
         closed_markets["opening_datetime"].dt.to_period("W").dt.strftime("%b-%d")
     )
-    return traders_data, closed_markets, daily_info
+    return traders_data, closed_markets, daily_info, unknown_traders
 
 
-traders_data, closed_markets, daily_info = prepare_data()
+traders_data, closed_markets, daily_info, unknown_traders = 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(
     traders_data
 )
-print(
-    weekly_metrics_by_market_creator.loc[
-        weekly_metrics_by_market_creator["market_creator"] == "all"
-    ].roi_diff_perc.describe()
-)
 weekly_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
     traders_data, trader_filter="non_Olas"
 )
@@ -136,6 +143,10 @@ weekly_non_olas_metrics_by_market_creator = compute_weekly_metrics_by_market_cre
     traders_data, trader_filter="non_Olas"
 )
 
+weekly_unknown_trader_metrics_by_market_creator = (
+    compute_weekly_metrics_by_market_creator(unknown_traders)
+)
+
 weekly_winning_metrics = compute_winning_metrics_by_trader(traders_data=traders_data)
 weekly_non_olas_winning_metrics = compute_winning_metrics_by_trader(
     traders_data=traders_data, trader_filter="non_Olas"
@@ -191,7 +202,7 @@ with demo:
 
             with gr.Row():
                 with gr.Column(scale=3):
-                    a_trader_markets_plot = plot_trader_metrics_by_market_creator(
+                    o_trader_markets_plot = plot_trader_metrics_by_market_creator(
                         metric_name=default_trader_metric,
                         traders_df=weekly_metrics_by_market_creator,
                     )
@@ -207,14 +218,14 @@ with demo:
             trader_o_details_selector.change(
                 update_a_trader_details,
                 inputs=trader_o_details_selector,
-                outputs=a_trader_markets_plot,
+                outputs=o_trader_markets_plot,
             )
 
             # Non-Olas traders graph
             with gr.Row():
                 gr.Markdown("# Weekly metrics of Non-Olas traders")
             with gr.Row():
-                trader_na_details_selector = gr.Dropdown(
+                trader_no_details_selector = gr.Dropdown(
                     label="Select a weekly trader metric",
                     choices=trader_metric_choices,
                     value=default_trader_metric,
@@ -222,23 +233,53 @@ with demo:
 
             with gr.Row():
                 with gr.Column(scale=3):
-                    na_trader_markets_plot = plot_trader_metrics_by_market_creator(
+                    trader_no_markets_plot = plot_trader_metrics_by_market_creator(
                         metric_name=default_trader_metric,
                         traders_df=weekly_non_olas_metrics_by_market_creator,
                     )
                 with gr.Column(scale=1):
                     trade_details_text = get_metrics_text()
 
-            def update_na_trader_details(trader_detail):
+            def update_no_trader_details(trader_detail):
                 return plot_trader_metrics_by_market_creator(
                     metric_name=trader_detail,
                     traders_df=weekly_non_olas_metrics_by_market_creator,
                 )
 
-            trader_na_details_selector.change(
-                update_na_trader_details,
-                inputs=trader_na_details_selector,
-                outputs=na_trader_markets_plot,
+            trader_no_details_selector.change(
+                update_no_trader_details,
+                inputs=trader_no_details_selector,
+                outputs=trader_no_markets_plot,
+            )
+            # Unknown traders graph
+            with gr.Row():
+                gr.Markdown("# Weekly metrics of Unknown traders")
+            with gr.Row():
+                trader_u_details_selector = gr.Dropdown(
+                    label="Select a weekly trader metric",
+                    choices=trader_metric_choices,
+                    value=default_trader_metric,
+                )
+
+            with gr.Row():
+                with gr.Column(scale=3):
+                    trader_u_markets_plot = plot_trader_metrics_by_market_creator(
+                        metric_name=default_trader_metric,
+                        traders_df=weekly_unknown_trader_metrics_by_market_creator,
+                    )
+                with gr.Column(scale=1):
+                    trade_details_text = get_metrics_text()
+
+            def update_u_trader_details(trader_detail):
+                return plot_trader_metrics_by_market_creator(
+                    metric_name=trader_detail,
+                    traders_df=weekly_unknown_trader_metrics_by_market_creator,
+                )
+
+            trader_u_details_selector.change(
+                update_u_trader_details,
+                inputs=trader_u_details_selector,
+                outputs=trader_u_markets_plot,
             )
         with gr.TabItem("📅 Daily metrics"):
             current_week_trades = get_current_week_data(trades_df=traders_data)
@@ -283,11 +324,11 @@ with demo:
                 inputs=[trade_live_details_selector, trade_live_details_plot],
                 outputs=[trade_live_details_plot],
             )
-
+            # Olas traders
             with gr.Row():
                 gr.Markdown("# Daily live metrics for 🌊 Olas traders")
             with gr.Row():
-                a_trader_live_details_selector = gr.Dropdown(
+                o_trader_live_details_selector = gr.Dropdown(
                     label="Select a daily live metric",
                     choices=trader_daily_metric_choices,
                     value=default_daily_metric,
@@ -295,7 +336,7 @@ with demo:
 
             with gr.Row():
                 with gr.Column(scale=3):
-                    a_trader_live_details_plot = plot_daily_metrics(
+                    o_trader_live_details_plot = plot_daily_metrics(
                         metric_name=default_daily_metric,
                         trades_df=live_metrics_by_market_creator,
                         trader_filter="Olas",
@@ -304,22 +345,22 @@ with demo:
                     trade_details_text = get_metrics_text(daily=True)
 
             def update_a_trader_live_details(trade_detail, a_trader_live_details_plot):
-                a_trader_plot = plot_daily_metrics(
+                o_trader_plot = plot_daily_metrics(
                     metric_name=trade_detail,
                     trades_df=live_metrics_by_market_creator,
                     trader_filter="Olas",
                 )
-                return a_trader_plot
+                return o_trader_plot
 
-            a_trader_live_details_selector.change(
+            o_trader_live_details_selector.change(
                 update_a_trader_live_details,
-                inputs=[a_trader_live_details_selector, a_trader_live_details_plot],
-                outputs=[a_trader_live_details_plot],
+                inputs=[o_trader_live_details_selector, o_trader_live_details_plot],
+                outputs=[o_trader_live_details_plot],
             )
             with gr.Row():
                 gr.Markdown("# Daily live metrics for Non-Olas traders")
             with gr.Row():
-                na_trader_live_details_selector = gr.Dropdown(
+                no_trader_live_details_selector = gr.Dropdown(
                     label="Select a daily live metric",
                     choices=trader_daily_metric_choices,
                     value=default_daily_metric,
@@ -327,7 +368,7 @@ with demo:
 
             with gr.Row():
                 with gr.Column(scale=3):
-                    na_trader_live_details_plot = plot_daily_metrics(
+                    no_trader_live_details_plot = plot_daily_metrics(
                         metric_name=default_daily_metric,
                         trades_df=live_metrics_by_market_creator,
                         trader_filter="non_Olas",
@@ -336,19 +377,19 @@ with demo:
                     trade_details_text = get_metrics_text(daily=True)
 
             def update_na_trader_live_details(
-                trade_detail, na_trader_live_details_plot
+                trade_detail, no_trader_live_details_plot
             ):
-                na_trader_plot = plot_daily_metrics(
+                no_trader_plot = plot_daily_metrics(
                     metric_name=trade_detail,
                     trades_df=live_metrics_by_market_creator,
                     trader_filter="non_Olas",
                 )
-                return na_trader_plot
+                return no_trader_plot
 
-            na_trader_live_details_selector.change(
+            no_trader_live_details_selector.change(
                 update_na_trader_live_details,
-                inputs=[na_trader_live_details_selector, na_trader_live_details_plot],
-                outputs=[na_trader_live_details_plot],
+                inputs=[no_trader_live_details_selector, no_trader_live_details_plot],
+                outputs=[no_trader_live_details_plot],
             )
 
         with gr.TabItem("📉 Markets Kullback–Leibler divergence"):
@@ -381,7 +422,7 @@ with demo:
                     "# Weekly total bet amount per trader type for Pearl markets"
                 )
             with gr.Row():
-                a_trader_total_bet_amount = plot_total_bet_amount(
+                o_trader_total_bet_amount = plot_total_bet_amount(
                     traders_data, market_filter="pearl"
                 )
 
@@ -390,9 +431,10 @@ with demo:
                     "# Weekly total bet amount per trader type for Quickstart markets"
                 )
             with gr.Row():
-                na_trader_total_bet_amount = plot_total_bet_amount(
+                no_trader_total_bet_amount = plot_total_bet_amount(
                     traders_data, market_filter="quickstart"
                 )
+
         with gr.TabItem("💰 Money invested per market"):
             with gr.Row():
                 gr.Markdown("# Weekly bet amounts per market for all traders")
@@ -402,14 +444,14 @@ with demo:
             with gr.Row():
                 gr.Markdown("# Weekly bet amounts per market for 🌊 Olas traders")
             with gr.Row():
-                a_trader_bet_amounts = plot_total_bet_amount_per_trader_per_market(
+                o_trader_bet_amounts = plot_total_bet_amount_per_trader_per_market(
                     traders_data, trader_filter="Olas"
                 )
 
             with gr.Row():
                 gr.Markdown("# Weekly bet amounts per market for Non-Olas traders")
             with gr.Row():
-                na_trader_bet_amounts = plot_total_bet_amount_per_trader_per_market(
+                no_trader_bet_amounts = plot_total_bet_amount_per_trader_per_market(
                     traders_data, trader_filter="non_Olas"
                 )
 

data/daily_info.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9b9c7c71ea81900aac2a840315940801489e15aa383c46467b30b02f7e3baea2
-size 461471
+oid sha256:1786521d10be3b3c7ccff825d4f5d4e3c8ec7616e351f89bc56ae846f421f6bc
+size 884405

data/unknown_daily_traders.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7f75e649183ccbf7179b4a79315e8957971f13a4e03870852e5850da65fd8821
+size 48908

data/unknown_traders.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0ab41a7a35d8bf5c588b95849ec650e048578ddcbb18bc62df0e7a3c96902ea5
+size 368142

scripts/metrics.py

@@ -66,7 +66,7 @@ def compute_trader_metrics_by_market_creator(
 ) -> 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.
-    The global roi of the trader agent by computing the individual net profit and the individual costs values
+    The global roi of the trader by computing the individual net profit and the individual costs values
     achieved per market and dividing both.
     It is possible to filter by market creator: quickstart, pearl, all"""
     assert "market_creator" in traders_data.columns
@@ -182,7 +182,7 @@ def compute_weekly_metrics_by_market_creator(
         for trader in tqdm(traders, desc=f"Trader' metrics", unit="metrics"):
             if trader_filter is None:
                 contents.append(merge_trader_weekly_metrics(trader, weekly_data, week))
-            elif trader_filter == "agent":
+            elif trader_filter == "Olas":
                 filtered_data = weekly_data.loc[weekly_data["staking"] != "non_Olas"]
                 contents.append(
                     merge_trader_weekly_metrics(trader, filtered_data, week)
@@ -217,7 +217,7 @@ def compute_daily_metrics_by_market_creator(
                 contents.append(
                     merge_trader_daily_metrics(trader, daily_data, day, live_metrics)
                 )
-            elif trader_filter == "agentic":
+            elif trader_filter == "Olas":
                 filtered_data = daily_data.loc[daily_data["staking"] != "non_Olas"]
                 contents.append(
                     merge_trader_daily_metrics(trader, filtered_data, day, live_metrics)
@@ -243,7 +243,7 @@ def compute_winning_metrics_by_trader(
     final_traders = pd.concat([market_all, traders_data], ignore_index=True)
     final_traders = final_traders.sort_values(by="creation_timestamp", ascending=True)
 
-    if trader_filter == "agentic":
+    if trader_filter == "Olas":
         final_traders = final_traders.loc[final_traders["staking"] != "non_Olas"]
     else:  # non_Olas traders
         final_traders = final_traders.loc[final_traders["staking"] == "non_Olas"]

tabs/market_plots.py

@@ -111,17 +111,17 @@ def plot_total_bet_amount_per_trader_per_market(
 
     # Create binary staking category
     final_traders["trader_type"] = final_traders["staking"].apply(
-        lambda x: "non_agent" if x == "non_agent" else "agent"
+        lambda x: "non_Olas" if x == "non_Olas" else "Olas"
     )
     final_traders["trader_market"] = final_traders.apply(
         lambda x: (x["trader_type"], x["market_creator"]), axis=1
     )
     color_discrete_sequence = ["purple", "goldenrod", "darkgreen"]
-    if trader_filter == "agent":
+    if trader_filter == "Olas":
         color_discrete_sequence = ["darkviolet", "goldenrod", "green"]
-        final_traders = final_traders.loc[final_traders["trader_type"] == "agent"]
-    elif trader_filter == "non_agent":
-        final_traders = final_traders.loc[final_traders["trader_type"] != "agent"]
+        final_traders = final_traders.loc[final_traders["trader_type"] == "Olas"]
+    elif trader_filter == "non_Olas":
+        final_traders = final_traders.loc[final_traders["trader_type"] != "Olas"]
 
     total_bet_amount = (
         final_traders.groupby(
@@ -149,12 +149,12 @@ def plot_total_bet_amount_per_trader_per_market(
         category_orders={
             "market_creator": ["pearl", "quickstart", "all"],
             "trader_market": [
-                ("agent", "pearl"),
-                ("non_agent", "pearl"),
-                ("agent", "quickstart"),
-                ("non_agent", "quickstart"),
-                ("agent", "all"),
-                ("non_agent", "all"),
+                ("Olas", "pearl"),
+                ("non_Olas", "pearl"),
+                ("Olas", "quickstart"),
+                ("non_Olas", "quickstart"),
+                ("Olas", "all"),
+                ("non_Olas", "all"),
             ],
         },
         # facet_col="trader_type",
@@ -192,17 +192,17 @@ def plot_nr_trades_per_trader_per_market(
 
     # Create binary staking category
     final_traders["trader_type"] = final_traders["staking"].apply(
-        lambda x: "non_agent" if x == "non_agent" else "agent"
+        lambda x: "non_Olas" if x == "non_Olas" else "Olas"
     )
     final_traders["trader_market"] = final_traders.apply(
         lambda x: (x["trader_type"], x["market_creator"]), axis=1
     )
     color_discrete_sequence = ["purple", "goldenrod", "darkgreen"]
-    if trader_filter == "agent":
+    if trader_filter == "Olas":
         color_discrete_sequence = ["darkviolet", "goldenrod", "green"]
-        final_traders = final_traders.loc[final_traders["trader_type"] == "agent"]
-    elif trader_filter == "non_agent":
-        final_traders = final_traders.loc[final_traders["trader_type"] != "agent"]
+        final_traders = final_traders.loc[final_traders["trader_type"] == "Olas"]
+    elif trader_filter == "non_Olas":
+        final_traders = final_traders.loc[final_traders["trader_type"] != "Olas"]
 
     fig = px.box(
         final_traders,
@@ -213,12 +213,12 @@ def plot_nr_trades_per_trader_per_market(
         category_orders={
             "market_creator": ["pearl", "quickstart", "all"],
             "trader_market": [
-                ("agent", "pearl"),
-                ("non_agent", "pearl"),
-                ("agent", "quickstart"),
-                ("non_agent", "quickstart"),
-                ("agent", "all"),
-                ("non_agent", "all"),
+                ("Olas", "pearl"),
+                ("non_Olas", "pearl"),
+                ("Olas", "quickstart"),
+                ("non_Olas", "quickstart"),
+                ("Olas", "all"),
+                ("non_Olas", "all"),
             ],
         },
         # facet_col="trader_type",

tabs/trader_plots.py

@@ -199,7 +199,7 @@ def plot_total_bet_amount(
     final_traders = final_traders.sort_values(by="creation_date", ascending=True)
     # Create binary staking category
     final_traders["trader_type"] = final_traders["staking"].apply(
-        lambda x: "non_agent" if x == "non_agent" else "agent"
+        lambda x: "non_Olas" if x == "non_Olas" else "Olas"
     )
 
     total_bet_amount = (
@@ -245,12 +245,12 @@ def plot_total_bet_amount(
         category_orders={
             "market_creator": ["pearl", "quickstart", "all"],
             "trader_market": [
-                ("agent", "pearl"),
-                ("non_agent", "pearl"),
-                ("agent", "quickstart"),
-                ("non_agent", "quickstart"),
-                ("agent", "all"),
-                ("non_agent", "all"),
+                ("Olas", "pearl"),
+                ("non_Olas", "pearl"),
+                ("Olas", "quickstart"),
+                ("non_Olas", "quickstart"),
+                ("Olas", "all"),
+                ("non_Olas", "all"),
             ],
         },
         barmode="group",
@@ -261,9 +261,7 @@ def plot_total_bet_amount(
         yaxis_title="Weekly total bet amount per trader type",
         legend=dict(yanchor="top", y=0.5),
     )
-    # for axis in fig.layout:
-    #     if axis.startswith("xaxis"):
-    #         fig.layout[axis].update(title="Week")
+
     fig.update_xaxes(tickformat="%b %d")
     # Update layout to force x-axis category order (hotfix for a sorting issue)
     fig.update_layout(xaxis={"categoryorder": "array", "categoryarray": all_dates})