updating graphs of trades tab

app.py

@@ -12,9 +12,9 @@ from tabs.trades import (
     get_overall_winning_trades,
     get_overall_winning_by_market_trades,
     plot_trades_by_week,
-    plot_trades_per_market_by_week2,
+    plot_trades_per_market_by_week,
     plot_winning_trades_by_week,
-    plot_winning_trades_per_market_by_week2,
+    plot_winning_trades_per_market_by_week,
     plot_trade_details,
 )
 from tabs.tool_win import (
@@ -172,7 +172,8 @@ winning_rate_df = get_tool_winning_rate(tools_df=tools_df, inc_tools=INC_TOOLS)
 winning_rate_overall_df = get_overall_winning_rate(wins_df=winning_rate_df)
 trades_count_df = get_overall_trades(trades_df=trades_df)
 trades_winning_rate_df = get_overall_winning_trades(trades_df=trades_df)
-
+trades_by_market = get_overall_by_market_trades(trades_df=trades_df)
+winning_trades_by_market = get_overall_winning_by_market_trades(trades_df=trades_df)
 with demo:
     gr.HTML("<h1>Olas Predict Actual Performance</h1>")
     gr.Markdown(
@@ -182,17 +183,40 @@ with demo:
     with gr.Tabs():
         with gr.TabItem("🔥Trades Dashboard"):
             with gr.Row():
-                gr.Markdown("# Number of trades per week")
+                gr.Markdown("# Trend of weekly trades")
             with gr.Row():
-                trades_by_week_plot = plot_trades_by_week(trades_df=trades_count_df)
+                with gr.Column(min_width=350):
+                    qs_trades_by_week = plot_trades_per_market_by_week(
+                        trades_df=trades_by_market, market_type="quickstart"
+                    )
+                with gr.Column(min_width=350):
+                    pearl_trades_by_week = plot_trades_per_market_by_week(
+                        trades_df=trades_by_market, market_type="pearl"
+                    )
+                with gr.Column(min_width=350):
+                    all_trades_by_week = plot_trades_per_market_by_week(
+                        trades_df=trades_by_market, market_type="all"
+                    )
+
             with gr.Row():
                 gr.Markdown("# Percentage of winning trades per week")
             with gr.Row():
-                winning_trades_by_week_plot = plot_winning_trades_by_week(
-                    trades_df=trades_winning_rate_df
-                )
+                with gr.Column(min_width=350):
+                    qs_wtrades_by_week = plot_winning_trades_per_market_by_week(
+                        trades_df=winning_trades_by_market, market_type="quickstart"
+                    )
+                with gr.Column(min_width=350):
+                    # gr.Markdown("# From Pearl market creator")
+                    pearl_wtrades_by_week = plot_winning_trades_per_market_by_week(
+                        trades_df=winning_trades_by_market, market_type="pearl"
+                    )
+                with gr.Column(min_width=350):
+                    all_wtrades_by_week = plot_winning_trades_per_market_by_week(
+                        trades_df=trades_winning_rate_df, market_type="all"
+                    )
+
             with gr.Row():
-                gr.Markdown("# Trading metrics")
+                gr.Markdown("# ⚖️ Trading metrics")
             with gr.Row():
                 trade_details_selector = gr.Dropdown(
                     label="Select a trade metric",
@@ -225,20 +249,7 @@ with demo:
                 trade_details_selector
             with gr.Row():
                 trade_details_plot
-        with gr.TabItem("⚖️Trades per market Dashboard"):
-            with gr.Row():
-                gr.Markdown("# Number of trades split by market type per week")
-            with gr.Row():
-                trades_by_week_plot = plot_trades_per_market_by_week2(
-                    trades_df=get_overall_by_market_trades(trades_df=trades_df)
-                )
-            with gr.Row():
-                gr.Markdown("# Percentage of winning trades per week")
-            with gr.Row():
-                winning_trades_by_week_plot = plot_winning_trades_per_market_by_week2(
-                    trades_df=get_overall_winning_by_market_trades(trades_df=trades_df)
-                )
-            # TODO add average ROI value per market
+
         with gr.TabItem("🚀 Tool Winning Dashboard"):
             with gr.Row():
                 gr.Markdown("# All tools winning performance")

tabs/trades.py

@@ -17,14 +17,14 @@ def prepare_trades(trades_df: pd.DataFrame) -> pd.DataFrame:
         trades_df["creation_timestamp"].dt.to_period("M").astype(str)
     )
     trades_df["month_year_week"] = (
-        trades_df["creation_timestamp"].dt.to_period("W").astype(str)
+        trades_df["creation_timestamp"].dt.to_period("W").dt.strftime("%b-%d")
     )
     trades_df["winning_trade"] = trades_df["winning_trade"].astype(int)
     return trades_df
 
 
 def get_overall_trades(trades_df: pd.DataFrame) -> pd.DataFrame:
-    """Gets the overall trades data for the given tools and calculates the winning percentage."""
+    """Gets the overall trades data"""
     trades_count = trades_df.groupby("month_year_week").size().reset_index()
     trades_count.columns = trades_count.columns.astype(str)
     trades_count.rename(columns={"0": "trades"}, inplace=True)
@@ -32,7 +32,7 @@ def get_overall_trades(trades_df: pd.DataFrame) -> pd.DataFrame:
 
 
 def get_overall_by_market_trades(trades_df: pd.DataFrame) -> pd.DataFrame:
-    """Gets the overall trades data for the given tools and calculates the winning percentage."""
+    """Gets the overall trades data"""
     trades_count = (
         trades_df.groupby(["market_creator", "month_year_week"]).size().reset_index()
     )
@@ -68,6 +68,7 @@ def get_overall_winning_by_market_trades(trades_df: pd.DataFrame) -> pd.DataFram
     winning_trades = winning_trades.reset_index()
     winning_trades.columns = winning_trades.columns.astype(str)
     winning_trades.columns = ["market_creator", "month_year_week", "winning_trade"]
+    print(winning_trades.head())
     return winning_trades
 
 
@@ -281,36 +282,35 @@ def plot_trades_by_week(trades_df: pd.DataFrame) -> gr.BarPlot:
     )
 
 
-def plot_trades_per_market_by_week(trades_df: pd.DataFrame) -> gr.BarPlot:
+def plot_trades_per_market_by_week(
+    trades_df: pd.DataFrame, market_type: str
+) -> gr.Plot:
     """Plots the trades data for the given tools and calculates the winning percentage."""
     assert "market_creator" in trades_df.columns
-    return gr.BarPlot(
-        value=trades_df,
-        x="month_year_week",
-        y="trades",
-        color="market_creator",
-        show_label=True,
-        interactive=True,
-        show_actions_button=True,
-        tooltip=["month_year_week", "market_creator", "trades"],
-        height=HEIGHT,
-        width=WIDTH,
-    )
-
+    # if market_type is "all then no filter is applied"
+    if market_type == "quickstart":
+        trades = trades_df.loc[trades_df["market_creator"] == "quickstart"]
+        color_sequence = ["goldenrod"]
+
+    elif market_type == "pearl":
+        trades = trades_df.loc[trades_df["market_creator"] == "pearl"]
+        color_sequence = ["purple"]
+    else:
+        trades = trades_df
+        color_sequence = ["darkgreen"]
 
-def plot_trades_per_market_by_week2(trades_df: pd.DataFrame) -> gr.Plot:
-    """Plots the trades data for the given tools and calculates the winning percentage."""
-    assert "market_creator" in trades_df.columns
     fig = px.bar(
-        trades_df,
+        trades,
         x="month_year_week",
         y="trades",
-        color="market_creator",
-        color_discrete_sequence=["purple", "goldenrod"],
-        width=1000,
-        height=600,
+        color_discrete_sequence=color_sequence,
+        title=market_type + " trades",
+    )
+    fig.update_layout(
+        xaxis_title="Week",
+        yaxis_title="Weekly nr of trades",
     )
-    fig.update_layout(legend=dict(yanchor="top", y=0.99, xanchor="right", x=0.99))
+    fig.update_xaxes(tickformat="%b %d\n%Y")
     return gr.Plot(
         value=fig,
     )
@@ -331,35 +331,35 @@ def plot_winning_trades_by_week(trades_df: pd.DataFrame) -> gr.BarPlot:
     )
 
 
-def plot_winning_trades_per_market_by_week(trades_df: pd.DataFrame) -> gr.BarPlot:
+def plot_winning_trades_per_market_by_week(
+    trades_df: pd.DataFrame, market_type: str
+) -> gr.Plot:
     """Plots the winning trades data for the given tools and calculates the winning percentage."""
-    assert "market_creator" in trades_df.columns
-    return gr.BarPlot(
-        value=trades_df,
-        x="month_year_week",
-        y="winning_trade",
-        color="market_creator",
-        show_label=True,
-        interactive=True,
-        show_actions_button=True,
-        tooltip=["month_year_week", "market_creator", "winning_trade"],
-        height=HEIGHT,
-        width=WIDTH,
-    )
+    # if market_type is "all then no filter is applied"
+    if market_type == "quickstart":
+        trades = trades_df.loc[trades_df["market_creator"] == "quickstart"]
+        color_sequence = ["goldenrod"]
+
+    elif market_type == "pearl":
+        trades = trades_df.loc[trades_df["market_creator"] == "pearl"]
+        color_sequence = ["purple"]
+    else:
+        trades = trades_df
+        color_sequence = ["darkgreen"]
 
-
-def plot_winning_trades_per_market_by_week2(trades_df: pd.DataFrame) -> gr.BarPlot:
-    """Plots the winning trades data for the given tools and calculates the winning percentage."""
     fig = px.bar(
-        trades_df,
+        trades,
         x="month_year_week",
         y="winning_trade",
-        color="market_creator",
-        color_discrete_sequence=["purple", "goldenrod"],
-        width=1000,
-        height=600,
+        color_discrete_sequence=color_sequence,
+        title=market_type + " winning trades",
+    )
+    fig.update_layout(
+        xaxis_title="Week",
+        yaxis_title="Weekly % of winning trades",
+        # yaxis_tickformat="%",
     )
-    fig.update_layout(legend=dict(yanchor="top", y=0.99, xanchor="right", x=0.99))
+    fig.update_xaxes(tickformat="%b %d\n%Y")
     return gr.Plot(
         value=fig,
     )