updated graphs after missing non_Olas group

app.py

@@ -101,15 +101,27 @@ def get_all_data():
     FROM read_parquet('./data/retention_activity.parquet')
     """
     df5 = con.execute(query5).fetchdf()
+
+    # Query to fetch active traders data
+    query6 = f"""
+    SELECT *
+    FROM read_parquet('./data/active_traders.parquet')
+    """
+    df6 = con.execute(query6).fetchdf()
     con.close()
-    return df1, df2, df3, df4, df5
+    return df1, df2, df3, df4, df5, df6
 
 
 def prepare_data():
 
-    all_trades, closed_markets, daily_info, unknown_traders, retention_df = (
-        get_all_data()
-    )
+    (
+        all_trades,
+        closed_markets,
+        daily_info,
+        unknown_traders,
+        retention_df,
+        active_traders,
+    ) = get_all_data()
 
     all_trades["creation_date"] = all_trades["creation_timestamp"].dt.date
 
@@ -150,12 +162,24 @@ def prepare_data():
         .dt.to_period("W")
         .dt.start_time.dt.strftime("%b-%d-%Y")
     )
-    return traders_data, closed_markets, daily_info, unknown_traders, retention_df
+    return (
+        traders_data,
+        closed_markets,
+        daily_info,
+        unknown_traders,
+        retention_df,
+        active_traders,
+    )
 
 
-traders_data, closed_markets, daily_info, unknown_traders, raw_retention_df = (
-    prepare_data()
-)
+(
+    traders_data,
+    closed_markets,
+    daily_info,
+    unknown_traders,
+    raw_retention_df,
+    active_traders,
+) = prepare_data()
 retention_df = prepare_retention_dataset(
     retention_df=raw_retention_df, unknown_df=unknown_traders
 )
@@ -170,9 +194,11 @@ weekly_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
 weekly_o_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
     traders_data, trader_filter="Olas"
 )
-weekly_non_olas_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
-    traders_data, trader_filter="non_Olas"
-)
+weekly_non_olas_metrics_by_market_creator = pd.DataFrame()
+if len(traders_data.loc[traders_data["staking"] == "non_Olas"]) > 0:
+    weekly_non_olas_metrics_by_market_creator = (
+        compute_weekly_metrics_by_market_creator(traders_data, trader_filter="non_Olas")
+    )
 weekly_unknown_trader_metrics_by_market_creator = None
 if len(unknown_traders) > 0:
     weekly_unknown_trader_metrics_by_market_creator = (
@@ -181,10 +207,18 @@ if len(unknown_traders) > 0:
         )
     )
 
-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"
+# just for all traders
+weekly_winning_metrics = compute_winning_metrics_by_trader(
+    traders_data=traders_data, unknown_info=unknown_traders
+)
+weekly_winning_metrics_olas = compute_winning_metrics_by_trader(
+    traders_data=traders_data, unknown_info=unknown_traders, trader_filter="Olas"
 )
+weekly_non_olas_winning_metrics = pd.DataFrame()
+if len(traders_data.loc[traders_data["staking"] == "non_Olas"]) > 0:
+    weekly_non_olas_winning_metrics = compute_winning_metrics_by_trader(
+        traders_data=traders_data, trader_filter="non_Olas"
+    )
 
 with demo:
     gr.HTML("<h1>Traders monitoring dashboard </h1>")
@@ -251,37 +285,37 @@ with demo:
                 inputs=trader_o_details_selector,
                 outputs=o_trader_markets_plot,
             )
+            if len(weekly_non_olas_metrics_by_market_creator) > 0:
+                # Non-Olas traders graph
+                with gr.Row():
+                    gr.Markdown("# Weekly metrics of Non-Olas traders")
+                with gr.Row():
+                    trader_no_details_selector = gr.Dropdown(
+                        label="Select a weekly trader metric",
+                        choices=trader_metric_choices,
+                        value=default_trader_metric,
+                    )
 
-            # Non-Olas traders graph
-            with gr.Row():
-                gr.Markdown("# Weekly metrics of Non-Olas traders")
-            with gr.Row():
-                trader_no_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_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(trader_type="non_Olas")
 
-            with gr.Row():
-                with gr.Column(scale=3):
-                    trader_no_markets_plot = plot_trader_metrics_by_market_creator(
-                        metric_name=default_trader_metric,
+                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,
                     )
-                with gr.Column(scale=1):
-                    trade_details_text = get_metrics_text(trader_type="non_Olas")
 
-            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_no_details_selector.change(
+                    update_no_trader_details,
+                    inputs=trader_no_details_selector,
+                    outputs=trader_no_markets_plot,
                 )
-
-            trader_no_details_selector.change(
-                update_no_trader_details,
-                inputs=trader_no_details_selector,
-                outputs=trader_no_markets_plot,
-            )
             # Unknown traders graph
             if weekly_unknown_trader_metrics_by_market_creator is not None:
                 with gr.Row():
@@ -453,7 +487,7 @@ with demo:
                     )
 
             with gr.Row():
-                gr.Markdown("# Cohort retention in pearl traders")
+                gr.Markdown("# Cohort retention graphs")
             with gr.Row():
                 gr.Markdown(
                     "The Cohort groups are organized by cohort weeks. A trader is part of a cohort group/week where it was detected the FIRST activity ever of that trader."
@@ -470,7 +504,8 @@ with demo:
                 )
             with gr.Row():
                 with gr.Column(scale=1):
-                    gr.Markdown("## Cohort retention of 🌊 Olas traders")
+                    gr.Markdown("## Cohort retention of pearl traders")
+                    gr.Markdown("### Cohort retention of 🌊 Olas traders")
                     cohort_retention_olas_pearl = calculate_cohort_retention(
                         df=retention_df, market_creator="pearl", trader_type="Olas"
                     )
@@ -478,34 +513,8 @@ with demo:
                         retention_matrix=cohort_retention_olas_pearl, cmap="Purples"
                     )
                 with gr.Column(scale=1):
-                    gr.Markdown("## Cohort retention of Non-Olas traders")
-                    # non_Olas
-                    cohort_retention_non_olas_pearl = calculate_cohort_retention(
-                        df=retention_df, market_creator="pearl", trader_type="non_Olas"
-                    )
-                    cohort_retention_plot2 = plot_cohort_retention_heatmap(
-                        retention_matrix=cohort_retention_non_olas_pearl,
-                        cmap=sns.color_palette("light:goldenrod", as_cmap=True),
-                    )
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.Markdown("## Cohort retention of unclassified traders")
-                    cohort_retention_unclassified_pearl = calculate_cohort_retention(
-                        df=retention_df,
-                        market_creator="pearl",
-                        trader_type="unclassified",
-                    )
-                    cohort_retention_plot3 = plot_cohort_retention_heatmap(
-                        retention_matrix=cohort_retention_unclassified_pearl,
-                        cmap="Greens",
-                    )
-                with gr.Column(scale=1):
-                    print("Adding explanatory text")
-            with gr.Row():
-                gr.Markdown("# Cohort retention in quickstart traders")
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.Markdown("## Cohort retention of 🌊 Olas traders")
+                    gr.Markdown("## Cohort retention of quickstart traders")
+                    gr.Markdown("### Cohort retention of 🌊 Olas traders")
                     cohort_retention_olas_qs = calculate_cohort_retention(
                         df=retention_df, market_creator="quickstart", trader_type="Olas"
                     )
@@ -513,43 +522,66 @@ with demo:
                         retention_matrix=cohort_retention_olas_qs,
                         cmap="Purples",
                     )
+                    # # non_Olas
+                    # cohort_retention_non_olas_pearl = calculate_cohort_retention(
+                    #     df=retention_df, market_creator="pearl", trader_type="non_Olas"
+                    # )
+                    # if len(cohort_retention_non_olas_pearl) > 0:
+                    #     gr.Markdown("## Cohort retention of Non-Olas traders")
+                    #     cohort_retention_plot2 = plot_cohort_retention_heatmap(
+                    #         retention_matrix=cohort_retention_non_olas_pearl,
+                    #         cmap=sns.color_palette("light:goldenrod", as_cmap=True),
+                    #     )
+            with gr.Row():
                 with gr.Column(scale=1):
-                    gr.Markdown("## Cohort retention of Non-Olas traders")
-                    # non_Olas
-                    cohort_retention_non_olas_qs = calculate_cohort_retention(
+                    gr.Markdown("## Cohort retention of pearl traders")
+                    cohort_retention_unclassified_pearl = calculate_cohort_retention(
                         df=retention_df,
-                        market_creator="quickstart",
-                        trader_type="non_Olas",
-                    )
-                    cohort_retention_plot5 = plot_cohort_retention_heatmap(
-                        retention_matrix=cohort_retention_non_olas_qs,
-                        cmap=sns.color_palette("light:goldenrod", as_cmap=True),
+                        market_creator="pearl",
+                        trader_type="unclassified",
                     )
-            with gr.Row():
+                    if len(cohort_retention_unclassified_pearl) > 0:
+                        gr.Markdown("### Cohort retention of unclassified traders")
+                        cohort_retention_plot3 = plot_cohort_retention_heatmap(
+                            retention_matrix=cohort_retention_unclassified_pearl,
+                            cmap="Greens",
+                        )
                 with gr.Column(scale=1):
-                    gr.Markdown("## Cohort retention of unclassified traders")
+                    gr.Markdown("## Cohort retention in quickstart traders")
                     cohort_retention_unclassified_qs = calculate_cohort_retention(
                         df=retention_df,
                         market_creator="quickstart",
                         trader_type="unclassified",
                     )
-                    cohort_retention_plot6 = plot_cohort_retention_heatmap(
-                        retention_matrix=cohort_retention_unclassified_qs,
-                        cmap="Greens",
-                    )
-                with gr.Column(scale=1):
-                    print("Adding explanatory text")
+                    if len(cohort_retention_unclassified_qs) > 0:
+                        gr.Markdown("### Cohort retention of unclassified traders")
+                        cohort_retention_plot6 = plot_cohort_retention_heatmap(
+                            retention_matrix=cohort_retention_unclassified_qs,
+                            cmap="Greens",
+                        )
+                    # # non_Olas
+                    # cohort_retention_non_olas_qs = calculate_cohort_retention(
+                    #     df=retention_df,
+                    #     market_creator="quickstart",
+                    #     trader_type="non_Olas",
+                    # )
+                    # if len(cohort_retention_non_olas_qs) > 0:
+                    #     gr.Markdown("## Cohort retention of Non-Olas traders")
+                    #     cohort_retention_plot5 = plot_cohort_retention_heatmap(
+                    #         retention_matrix=cohort_retention_non_olas_qs,
+                    #         cmap=sns.color_palette("light:goldenrod", as_cmap=True),
+                    #     )
         with gr.TabItem("⚙️ Active traders"):
             with gr.Row():
                 gr.Markdown("# Active traders for all markets by trader categories")
             with gr.Row():
-                active_traders_plot = plot_active_traders(traders_data, unknown_traders)
+                active_traders_plot = plot_active_traders(active_traders)
 
             with gr.Row():
                 gr.Markdown("# Active traders for Pearl markets by trader categories")
             with gr.Row():
-                active_traders_plot = plot_active_traders(
-                    traders_data, unknown_traders, market_creator="pearl"
+                active_traders_plot_pearl = plot_active_traders(
+                    active_traders, market_creator="pearl"
                 )
 
             with gr.Row():
@@ -557,8 +589,8 @@ with demo:
                     "# Active traders for Quickstart markets by trader categories"
                 )
             with gr.Row():
-                active_traders_plot = plot_active_traders(
-                    traders_data, unknown_traders, market_creator="quickstart"
+                active_traders_plot_qs = plot_active_traders(
+                    active_traders, market_creator="quickstart"
                 )
 
         with gr.TabItem("📉 Markets Kullback–Leibler divergence"):
@@ -581,6 +613,7 @@ with demo:
         with gr.TabItem("💰 Money invested per trader type"):
             with gr.Row():
                 gr.Markdown("# Weekly total bet amount per trader type for all markets")
+                gr.Markdown("## Computed only for trader agents using the mech service")
             with gr.Row():
                 total_bet_amount = plot_total_bet_amount(
                     traders_data, market_filter="all"
@@ -607,6 +640,7 @@ with demo:
         with gr.TabItem("💰 Money invested per market"):
             with gr.Row():
                 gr.Markdown("# Weekly bet amounts per market for all traders")
+                gr.Markdown("## Computed only for trader agents using the mech service")
             with gr.Row():
                 bet_amounts = plot_total_bet_amount_per_trader_per_market(traders_data)
 
@@ -637,16 +671,21 @@ with demo:
             with gr.Row():
                 metrics_text = get_metrics_text()
             with gr.Row():
-                winning_metric = plot_winning_metric_per_trader(weekly_winning_metrics)
-
-            # non_Olasic traders
-            with gr.Row():
-                gr.Markdown("# Weekly winning trades percentage from Non-Olas traders")
-            with gr.Row():
-                metrics_text = get_metrics_text()
-            with gr.Row():
-                winning_metric = plot_winning_metric_per_trader(
-                    weekly_non_olas_winning_metrics
+                winning_metric_olas = plot_winning_metric_per_trader(
+                    weekly_winning_metrics_olas
                 )
 
+            # # non_Olas traders
+            # if len(weekly_non_olas_winning_metrics) > 0:
+            #     with gr.Row():
+            #         gr.Markdown(
+            #             "# Weekly winning trades percentage from Non-Olas traders"
+            #         )
+            #     with gr.Row():
+            #         metrics_text = get_metrics_text()
+            #     with gr.Row():
+            #         winning_metric = plot_winning_metric_per_trader(
+            #             weekly_non_olas_winning_metrics
+            #         )
+
 demo.queue(default_concurrency_limit=40).launch()