new graph about trades volume at the market level

app.py

@@ -21,6 +21,7 @@ from tabs.trader_plots import (
 )
 
 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 (
     plot_kl_div_per_market,
 )
@@ -76,7 +77,7 @@ def prepare_data():
 
     all_trades["creation_date"] = all_trades["creation_timestamp"].dt.date
 
-    # adding multi-bet variables
+    # nr-trades variable
     volume_trades_per_trader_and_market = (
         all_trades.groupby(["trader_address", "title"])["roi"].count().reset_index()
     )
@@ -89,10 +90,10 @@ def prepare_data():
     )
 
     # adding the trader family column
-    # trader_agents_data["trader_family"] = trader_agents_data.apply(
-    #     lambda x: get_traders_family(x), axis=1
-    # )
-    # print(trader_agents_data.trader_family.value_counts())
+    trader_agents_data["trader_family"] = trader_agents_data.apply(
+        lambda x: get_traders_family(x), axis=1
+    )
+    print(trader_agents_data.trader_family.value_counts())
 
     trader_agents_data = trader_agents_data.sort_values(
         by="creation_timestamp", ascending=True
@@ -286,6 +287,16 @@ with demo:
                 with gr.Column(scale=1):
                     interpretation = get_interpretation_text()
 
+            with gr.Row():
+                gr.Markdown(
+                    "# Weekly volume of trades at each market per trader family"
+                )
+
+            with gr.Row():
+                trades_volume_plot = plot_weekly_trades_volume_by_trader_family(
+                    trader_agents_data
+                )
+
         with gr.TabItem("🎖️Weekly winning trades % per trader"):
             with gr.Row():
                 gr.Markdown("# Weekly winning trades percentage from all traders")

scripts/trades_volume_per_market.py

@@ -0,0 +1,38 @@
+import pandas as pd
+import gradio as gr
+import plotly.express as px
+
+
+def plot_weekly_trades_volume_by_trader_family(
+    trader_agents_data: pd.DataFrame,
+) -> gr.Plot:
+    """Function to compute the metrics at the trader level per week
+    and with different categories by market creator"""
+
+    weekly_trades_volume = (
+        trader_agents_data.groupby(
+            ["month_year_week", "title", "trader_family"], sort=False
+        )["trader_address"]
+        .size()
+        .reset_index(name="trades")
+    )
+
+    fig = px.box(
+        weekly_trades_volume,
+        x="month_year_week",
+        y="trades",
+        color="trader_family",
+        color_discrete_sequence=["darkviolet", "goldenrod", "gray"],
+        category_orders={
+            "trader_family": ["pearl_agent", "quickstart_agent", "non_agent"]
+        },
+    )
+
+    fig.update_layout(
+        xaxis_title="Week",
+        yaxis_title="Weekly trades volume in each market per trader family type",
+        legend=dict(yanchor="top", y=0.5),
+    )
+    # fig.update_layout(width=WIDTH, height=HEIGHT)
+    fig.update_xaxes(tickformat="%b %d\n%Y")
+    return gr.Plot(value=fig)