new graph with non agents

app.py

@@ -10,6 +10,7 @@ from tabs.trades import (
     get_overall_winning_trades,
     get_overall_winning_by_market_trades,
     integrated_plot_trades_per_market_by_week,
+    integrated_plot_trades_per_market_by_week_v2,
     integrated_plot_winning_trades_per_market_by_week,
 )
 from tabs.staking import plot_staking_trades_per_market_by_week

tabs/staking.py

@@ -35,10 +35,11 @@ def plot_staking_trades_per_market_by_week(
     all_filtered_trades = all_filtered_trades.sort_values(
         by="creation_timestamp", ascending=True
     )
-
+    print(f"filtering by market creator = {market_creator}")
     all_filtered_trades = all_filtered_trades.loc[
         all_filtered_trades["market_creator"] == market_creator
     ]
+    print(all_filtered_trades.market_creator.value_counts())
     if market_creator != "all":
         all_filtered_trades["staking"] = all_filtered_trades["staking"].replace(
             {market_creator: "staking_traders", "non_agent": "non_agent_traders"}

tabs/trades.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import pandas as pd
 import plotly.express as px
+import plotly.graph_objects as go
 
 
 HEIGHT = 400
@@ -124,6 +125,85 @@ def integrated_plot_trades_per_market_by_week(trades_df: pd.DataFrame) -> gr.Plo
     return gr.Plot(value=fig)
 
 
+def integrated_plot_trades_per_market_by_week_v2(trades_df: pd.DataFrame) -> gr.Plot:
+    # adding the total
+    trades_all = trades_df.copy(deep=True)
+    trades_all["market_creator"] = "all"
+
+    # merging both dataframes
+    all_filtered_trades = pd.concat([trades_df, trades_all], ignore_index=True)
+    all_filtered_trades = all_filtered_trades.sort_values(
+        by="creation_timestamp", ascending=True
+    )
+
+    # Create binary staking category
+    all_filtered_trades["staking_type"] = all_filtered_trades["staking"].apply(
+        lambda x: "non_agent" if x == "non_agent" else "agent"
+    )
+
+    # Group by week, market_creator and staking_type
+    trades = (
+        all_filtered_trades.groupby(
+            ["month_year_week", "market_creator", "staking_type"], sort=False
+        )
+        .size()
+        .reset_index(name="trades")
+    )
+
+    # category_orders={"market_creator": ["pearl", "quickstart", "all"]},
+
+    # Combine the traces
+    final_traces = []
+    market_colors = {"pearl": "purple", "quickstart": "goldenrod", "all": "darkgreen"}
+    # First add 'agent' traces
+    for market in ["pearl", "quickstart", "all"]:
+        market_data = trades[trades["market_creator"] == market]
+        agent_data = market_data[market_data["staking_type"] == "agent"]
+
+        trace = go.Bar(
+            x=agent_data["month_year_week"],
+            y=agent_data["trades"],
+            name=f"{market}-agent",
+            marker_color=market_colors[market],
+            offsetgroup=market,
+            showlegend=True,
+        )
+        final_traces.append(trace)
+
+    # Then add 'non_agent' traces
+    for market in ["pearl", "quickstart", "all"]:
+        market_data = trades[trades["market_creator"] == market]
+        non_agent_data = market_data[market_data["staking_type"] == "non_agent"]
+
+        trace = go.Bar(
+            x=non_agent_data["month_year_week"],
+            y=non_agent_data["trades"],
+            name=f"{market}-non_agent",
+            marker_color="black",
+            offsetgroup=market,
+            showlegend=True,
+        )
+        final_traces.append(trace)
+
+    # Create new figure with the combined traces
+    fig = go.Figure(data=final_traces)
+
+    # Update layout
+    fig.update_layout(
+        xaxis_title="Week",
+        yaxis_title="Weekly nr of trades",
+        legend=dict(yanchor="top", y=0.5),
+        width=WIDTH,
+        height=HEIGHT,
+        barmode="group",
+    )
+
+    # Update x-axis format
+    fig.update_xaxes(tickformat="%b %d\n%Y")
+
+    return gr.Plot(value=fig)
+
+
 def integrated_plot_winning_trades_per_market_by_week(
     trades_df: pd.DataFrame,
 ) -> gr.Plot: