Adding graph for trader type

app.py

@@ -95,9 +95,9 @@ weekly_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
 print("weekly metrics by market creator")
 print(weekly_metrics_by_market_creator.head())
 # get weekly metrics by trader type: multibet, singlebet or all.
-# weekly_metrics_by_market_strategy = compute_weekly_metrics_by_trader_type(
-#     trader_agents_data
-# )
+weekly_metrics_by_trader_type = compute_weekly_metrics_by_trader_type(
+    trader_agents_data
+)
 with demo:
     gr.HTML("<h1>Trader agents monitoring dashboard </h1>")
     gr.Markdown(
@@ -106,7 +106,6 @@ with demo:
 
     with gr.Tabs():
         with gr.TabItem("🔥Trader Agents Dashboard"):
-            # TODO Implement metrics showing market creator
             with gr.Row():
                 gr.Markdown("# Weekly metrics of trader agents by market creator")
             with gr.Row():
@@ -137,36 +136,36 @@ with demo:
                 outputs=trader_markets_plot,
             )
 
-            # with gr.Row():
-            #     gr.Markdown(
-            #         "# Weekly metrics for trader agents by trader type (multibet or singlebet)"
-            #     )
-            # with gr.Row():
-            #     trade_details_selector = gr.Dropdown(
-            #         label="Select a trader metric",
-            #         choices=trader_metric_choices,
-            #         value=default_trader_metric,
-            #     )
-
-            # with gr.Row():
-            #     with gr.Column(scale=3):
-            #         trader_type_plot = plot_trader_metrics_by_trader_type(
-            #             metric_name=default_trader_metric,
-            #             trades_df=trades_df,
-            #         )
-            #     with gr.Column(scale=1):
-            #         trade_details_text = get_trader_metrics_text()
-
-            # def update_trader_details(trader_detail):
-            #     return plot_trader_metrics_by_trader_type(
-            #         metric_name=trader_detail,
-            #         trades_df=trades_df,
-            #     )
-
-            # trader_details_selector.change(
-            #     update_trader_details,
-            #     inputs=trade_details_selector,
-            #     outputs=trader_details_plot,
-            # )
+            with gr.Row():
+                gr.Markdown(
+                    "# Weekly metrics for trader agents by trader type (multibet or singlebet)"
+                )
+            with gr.Row():
+                trader_metric_selector = gr.Dropdown(
+                    label="Select a trader metric",
+                    choices=trader_metric_choices,
+                    value=default_trader_metric,
+                )
+
+            with gr.Row():
+                with gr.Column(scale=3):
+                    trader_type_plot = plot_trader_metrics_by_trader_type(
+                        metric_name=default_trader_metric,
+                        traders_df=weekly_metrics_by_trader_type,
+                    )
+                with gr.Column(scale=1):
+                    trader_metrics_text = get_trader_metrics_text()
+
+            def update_trader_metric(trader_metric):
+                return plot_trader_metrics_by_trader_type(
+                    metric_name=trader_metric,
+                    traders_df=weekly_metrics_by_trader_type,
+                )
+
+            trader_metric_selector.change(
+                update_trader_metric,
+                inputs=trader_metric_selector,
+                outputs=trader_type_plot,
+            )
 
 demo.queue(default_concurrency_limit=40).launch()

scripts/metrics.py

@@ -105,7 +105,41 @@ def merge_trader_metrics(
         weekly_metrics_pearl["market_creator"] = "pearl"
         trader_metrics.append(weekly_metrics_pearl)
     result = pd.DataFrame.from_dict(trader_metrics, orient="columns")
-    tqdm.write(f"Total length of all trader metrics for this week = {len(result)}")
+    # tqdm.write(f"Total length of all trader metrics for this week = {len(result)}")
+    return result
+
+
+def merge_trader_metrics_by_type(
+    trader: str, weekly_data: pd.DataFrame, week: str
+) -> pd.DataFrame:
+    trader_metrics = []
+    # computation as specification 1 for all types of traders
+    weekly_metrics_all = compute_trader_metrics_by_trader_type(
+        trader, weekly_data, trader_type="all"
+    )
+    weekly_metrics_all["month_year_week"] = week
+    weekly_metrics_all["trader_type"] = "all"
+    trader_metrics.append(weekly_metrics_all)
+
+    # computation as specification 1 for multibet traders
+    weekly_metrics_mb = compute_trader_metrics_by_trader_type(
+        trader, weekly_data, trader_type="multibet"
+    )
+    if len(weekly_metrics_mb) > 0:
+        weekly_metrics_mb["month_year_week"] = week
+        weekly_metrics_mb["trader_type"] = "multibet"
+        trader_metrics.append(weekly_metrics_mb)
+
+    # computation as specification 1 for singlebet traders
+    weekly_metrics_sb = compute_trader_metrics_by_trader_type(
+        trader, weekly_data, trader_type="singlebet"
+    )
+    if len(weekly_metrics_sb) > 0:
+        weekly_metrics_sb["month_year_week"] = week
+        weekly_metrics_sb["trader_type"] = "singlebet"
+        trader_metrics.append(weekly_metrics_sb)
+    result = pd.DataFrame.from_dict(trader_metrics, orient="columns")
+    # tqdm.write(f"Total length of all trader metrics for this week = {len(result)}")
     return result
 
 
@@ -142,30 +176,6 @@ def compute_weekly_metrics_by_trader_type(
         # traverse each trader agent
         traders = list(weekly_data.trader_address.unique())
         for trader in tqdm(traders, desc=f"Trader' metrics", unit="metrics"):
-            # computation as specification 1 for all types of traders
-            weekly_metrics = compute_trader_metrics_by_trader_type(
-                trader, weekly_data, trader_type="all"
-            )
-            weekly_metrics["month_year_week"] = week
-            weekly_metrics["trader_type"] = "all"
-            contents.append(weekly_metrics)
-
-            # computation as specification 1 for multibet traders
-            weekly_metrics = compute_trader_metrics_by_trader_type(
-                trader, weekly_data, trader_type="multibet"
-            )
-            if len(weekly_metrics) > 0:
-                weekly_metrics["month_year_week"] = week
-                weekly_metrics["trader_type"] = "multibet"
-                contents.append(weekly_metrics)
-
-            # computation as specification 1 for singlebet traders
-            weekly_metrics = compute_trader_metrics_by_trader_type(
-                trader, weekly_data, trader_type="singlebet"
-            )
-            if len(weekly_metrics) > 0:
-                weekly_metrics["month_year_week"] = week
-                weekly_metrics["trader_type"] = "singlebet"
-                contents.append(weekly_metrics)
+            contents.append(merge_trader_metrics_by_type(trader, weekly_data, week))
     print("End computing all weekly metrics by trader types")
     return pd.concat(contents, ignore_index=True)

tabs/trader_plots.py

@@ -71,5 +71,46 @@ def plot_trader_metrics_by_market_creator(
     )
 
 
-def plot_trader_metrics_by_trader_type():
-    print("WIP")
+def plot_trader_metrics_by_trader_type(metric_name: str, traders_df: pd.DataFrame):
+    """Plots the weekly trader metrics."""
+
+    if metric_name == "mech calls":
+        metric_name = "mech_calls"
+        column_name = "nr_mech_calls"
+        yaxis_title = "Total nr of mech calls per trader"
+    elif metric_name == "ROI":
+        column_name = "roi"
+        yaxis_title = "Total ROI (net profit/cost)"
+    elif metric_name == "bet amount":
+        metric_name = "bet_amount"
+        column_name = metric_name
+        yaxis_title = "Total bet amount per trader (xDAI)"
+    elif metric_name == "net earnings":
+        metric_name = "net_earnings"
+        column_name = metric_name
+        yaxis_title = "Total net profit per trader (xDAI)"
+    else:  # earnings
+        column_name = metric_name
+        yaxis_title = "Total gross profit per trader (xDAI)"
+
+    traders_filtered = traders_df[["month_year_week", "trader_type", column_name]]
+
+    fig = px.box(
+        traders_filtered,
+        x="month_year_week",
+        y=column_name,
+        color="trader_type",
+        color_discrete_sequence=["gray", "orange", "darkblue"],
+        category_orders={"trader_type": ["singlebet", "multibet", "all"]},
+    )
+    fig.update_traces(boxmean=True)
+    fig.update_layout(
+        xaxis_title="Week",
+        yaxis_title=yaxis_title,
+        legend=dict(yanchor="top", y=0.5),
+    )
+    fig.update_xaxes(tickformat="%b %d\n%Y")
+
+    return gr.Plot(
+        value=fig,
+    )