Updated plot summary

examples/plot_season_summary.py

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+"""
+Season Summary Visualization
+==================================
+This example demonstrates how to summarize the season by visualizing
+race results, points progression, and other key statistics.
+.. codeauthor:: Vandana
+"""
+
+import numpy as np
+import pandas as pd
+import plotly.graph_objects as go
+from plotly.io import show
+from plotly.subplots import make_subplots
+
+from fastf1.ergast import Ergast
+
+
+# Initialize Ergast API
+ergast = Ergast()
+
+# Fetch the event schedule
+schedules = ergast.get_race_schedule(2022)
+races = pd.DataFrame(schedules)
+
+standings = []
+
+for _, race in races.iterrows():
+    race_name = race["raceName"]
+    round_number = race["round"]
+
+    # Fetch the race session
+    session = ergast.get_race_results(2022, round_number)  # Race session
+
+    sprint_session = None
+
+    try:
+        sprint_session = ergast.get_sprint_results(2022, round_number)
+    except Exception:
+        pass
+
+    # Fetch race data
+    race_results = session.content
+    race_results = pd.DataFrame(race_results[0])
+    for driver in race_results["driverCode"]:
+        driver_result = race_results[race_results["driverCode"] == driver]
+        points = driver_result["points"]
+        position = driver_result["position"]
+
+        # Add sprint race points if applicable
+        if sprint_session.content:
+            sprint_results = sprint_session.content
+            sprint_results = pd.DataFrame(sprint_results[0])
+            if driver in sprint_results["driverCode"].values:
+                sprint_points = int(
+                    sprint_results[sprint_results["driverCode"] == driver][
+                        "points"
+                    ].iloc[0]
+                )
+            else:
+                sprint_points = 0
+        else:
+            sprint_points = 0
+
+        standings.append(
+            {
+                "Race": race_name,
+                "RoundNumber": round_number,
+                "Driver": driver,
+                "Points": int(points.iloc[0]) + sprint_points,
+                "Position": int(position.iloc[0]),
+            }
+        )
+
+
+df = pd.DataFrame(standings)
+
+# Prepare heatmap data
+heatmap_data = df.pivot(
+    index="Driver", columns="RoundNumber", values="Points"
+).fillna(0)
+heatmap_data["Total Points"] = heatmap_data.sum(axis=1)
+heatmap_data = heatmap_data.sort_values(by="Total Points", ascending=True)
+
+# Prepare position data
+position_data = df.pivot(
+    index="Driver", columns="RoundNumber", values="Position"
+).fillna("N/A")
+
+# Map race names
+race_name_mapping = dict(zip(races["round"], races["raceName"]))
+
+# Simplify x-axis labels
+heatmap_data_rounds = heatmap_data.iloc[:, :-1]
+x_labels_rounds = [str(race) for race in heatmap_data.columns[:-1]]
+x_labels_total = ["Total Points"]
+
+# Custom colorscales
+colorscale_rounds = [[0, "#aee2fb"], [0.433, "#69bce8"], [1, "#3085be"]]
+colorscale_total = [[0, "#ffcccc"], [0.433, "#ff6666"], [1, "#cc0000"]]
+
+# Prepare custom_data for hover information (only for rounds)
+custom_data = np.array(
+    [
+        [
+            {
+                "position": position_data.at[driver, race]
+                if race in position_data.columns
+                else "N/A",
+                "race_name": race_name_mapping.get(race, "Unknown"),
+            }
+            for race in heatmap_data.columns[:-1]
+        ]
+        for driver in heatmap_data.index
+    ]
+)
+
+custom_data_rounds = custom_data[:, :-1]
+
+# Get max values for normalization
+max_points_rounds = heatmap_data_rounds.values.max()
+max_points_total = heatmap_data.iloc[:, -1:].values.max()
+
+# Create subplots for two heatmaps
+fig = make_subplots(
+    rows=1,
+    cols=2,
+    column_widths=[0.85, 0.15],
+    horizontal_spacing=0.05,
+    subplot_titles=("F1 2022 Season Rounds", "Total Points"),
+)
+
+# Heatmap for individual rounds
+fig.add_trace(
+    go.Heatmap(
+        z=heatmap_data_rounds.values,
+        x=x_labels_rounds,
+        y=heatmap_data_rounds.index,
+        customdata=custom_data,
+        text=heatmap_data_rounds.values,
+        texttemplate="%{text}",
+        textfont={"size": 12},
+        colorscale=colorscale_rounds,
+        showscale=False,
+        zmin=0,
+        zmax=max_points_rounds,
+        hovertemplate=(
+            "Driver: %{y}<br>"
+            "Round: %{x}<br>"
+            "Race Name: %{customdata.race_name}<br>"
+            "Points: %{z}<br>"
+            "Position: %{customdata.position}<extra></extra>"
+        ),
+    ),
+    row=1,
+    col=1,
+)
+
+# Heatmap for total points
+fig.add_trace(
+    go.Heatmap(
+        z=heatmap_data.iloc[:, -1:].values,
+        x=x_labels_total,
+        y=heatmap_data.index,
+        text=heatmap_data.iloc[:, -1:].values,
+        texttemplate="%{text}",
+        textfont={"size": 12},
+        colorscale=colorscale_total,
+        showscale=False,
+        hoverinfo="none",
+        zmin=0,
+        zmax=max_points_total,
+    ),
+    row=1,
+    col=2,
+)
+
+# Update layout
+fig.update_xaxes(title_text="Rounds", row=1, col=1)
+fig.update_yaxes(title_text="Drivers", row=1, col=1)
+fig.update_layout(title="F1 Results Tracker Heatmap")
+
+# Plot the updated heatmap
+show(fig)