removing monthly roi graph and adding 4 weeks avg roi

app.py

@@ -27,7 +27,7 @@ from tabs.trader_plots import (
     plot_total_bet_amount,
     plot_active_traders,
     plot_rolling_average,
-    plot_avg_monthly_ROI,
+    plot_rolling_average_roi,
 )
 from tabs.daily_graphs import (
     get_current_week_data,
@@ -264,14 +264,6 @@ with demo:
     gr.Markdown("This app shows the weekly performance of the traders in Olas Predict.")
 
     with gr.Tabs():
-        with gr.TabItem("📊 Monthly metrics"):
-            with gr.Row():
-                gr.Markdown("# Monthly average ROI of Pearl traders")
-            with gr.Row():
-                avrg_monthly_roi = plot_avg_monthly_ROI(
-                    traders_data, market_creator="pearl"
-                )
-
         with gr.TabItem("🔥 Weekly metrics"):
             with gr.Row():
                 gr.Markdown("# Weekly metrics of all traders")
@@ -396,6 +388,13 @@ with demo:
                     inputs=trader_u_details_selector,
                     outputs=trader_u_markets_plot,
                 )
+            with gr.Row():
+                gr.Markdown("# 4-weeks rolling average ROI for Pearl traders")
+            with gr.Row():
+                pearl_rolling_avg_plot = plot_rolling_average_roi(
+                    weekly_roi_df=weekly_metrics_by_market_creator,
+                    market_creator="pearl",
+                )
         with gr.TabItem("📅 Daily metrics"):
             live_trades_current_week = get_current_week_data(trades_df=daily_info)
             if len(live_trades_current_week) > 0:

tabs/trader_plots.py

@@ -396,6 +396,56 @@ def get_sevenday_rolling_average_by_market_creator(
     return combined_rolling_avg
 
 
+def get_fourweeks_rolling_average_roi(weekly_roi_df: pd.DataFrame) -> pd.DataFrame:
+    """Function to get the 4-week rolling average of the ROI by market_creator and total"""
+    # Create a local copy of the dataframe
+    local_df = weekly_roi_df.copy()
+
+    # Convert string dates to datetime
+    local_df["month_year_week"] = pd.to_datetime(
+        local_df["month_year_week"], format="%b-%d-%Y"
+    )
+    # Sort the dataframe by date
+    local_df = local_df.sort_values(by="month_year_week").set_index("month_year_week")
+
+    # Group by market_creator and calculate rolling average of unique trader_address
+    trader_rolling_avg_roi = (
+        local_df.resample("W")["roi"].mean().rolling(window=4).mean().reset_index()
+    )
+    trader_rolling_avg_roi.rename(columns={"roi": "rolling_avg_roi"}, inplace=True)
+    return trader_rolling_avg_roi
+
+
+def plot_rolling_average_roi(
+    weekly_roi_df: pd.DataFrame, market_creator: str
+) -> gr.Plot:
+    """Function to plot the rolling average of ROI for traders in a given market"""
+    if market_creator != "all":
+        filtered_roi_df = weekly_roi_df.loc[
+            weekly_roi_df["market_creator"] == market_creator
+        ]
+        rolling_avg_roi_df = get_fourweeks_rolling_average_roi(filtered_roi_df)
+    else:
+        rolling_avg_roi_df = get_fourweeks_rolling_average_roi(weekly_roi_df)
+    print(rolling_avg_roi_df.head())
+    # Ensure 'month_year_week' is a column, not an index
+    if "month_year_week" not in rolling_avg_roi_df.columns:
+        rolling_avg_roi_df = rolling_avg_roi_df.reset_index()
+    fig = px.bar(
+        rolling_avg_roi_df,
+        x="month_year_week",
+        y="rolling_avg_roi",
+    )
+    fig.update_layout(
+        xaxis_title="Week",
+        yaxis_title="4-week rolling average of ROI at the trader level",
+    )
+
+    return gr.Plot(
+        value=fig,
+    )
+
+
 def get_sevenday_rolling_average(active_traders_df: pd.DataFrame) -> pd.DataFrame:
     """Function to get the 7-day rolling average of the number of unique trader_address by market_creator and total"""
     # Create a local copy of the dataframe
@@ -444,16 +494,10 @@ def plot_rolling_average(
         rolling_avg_df,
         x="creation_date",
         y="rolling_avg_traders",
-        # color="market_creator",
-        # color_discrete_sequence=color_mapping,
-        # category_orders={
-        #     "market_creator": ["pearl", "quickstart", "all"],
-        # },
     )
     fig.update_layout(
         xaxis_title="Date",
         yaxis_title="7-day rolling average of active traders",
-        legend=dict(yanchor="top", y=0.5),
     )
 
     return gr.Plot(