DOC: add lap times distribution example (#377)

examples/plot_laptimes_distribution.py

@@ -0,0 +1,84 @@
+"""Driver Laptimes Distribution Visualization
+=============================================
+Visualizae different drivers' laptime distributions.
+"""
+
+import fastf1
+import fastf1.plotting
+import seaborn as sns
+from matplotlib import pyplot as plt
+
+# enabling misc_mpl_mods will turn on minor grid lines that clutters the plot
+fastf1.plotting.setup_mpl(mpl_timedelta_support=False, misc_mpl_mods=False)
+
+###############################################################################
+# Load the race session
+
+race = fastf1.get_session(2023, "Azerbaijan", 'R')
+race.load()
+
+###############################################################################
+# Get all the laps for the point finishers only.
+# Filter out slow laps (yellow flag, VSC, pitstops etc.)
+# as they distort the graph axis.
+point_finishers = race.drivers[:10]
+print(point_finishers)
+driver_laps = race.laps.pick_drivers(point_finishers).pick_quicklaps()
+driver_laps = driver_laps.reset_index()
+
+###############################################################################
+# To plot the drivers by finishing order,
+# we need to get their three-letter abbreviations in the finishing order.
+finishing_order = [race.get_driver(i)["Abbreviation"] for i in point_finishers]
+print(finishing_order)
+
+###############################################################################
+# We need to modify the DRIVER_COLORS palette.
+# Its keys are the driver's full names but we need the keys to be the drivers'
+# three-letter abbreviations.
+# We can do this with the DRIVER_TRANSLATE mapping.
+driver_colors = {abv: fastf1.plotting.DRIVER_COLORS[driver] for abv,
+                 driver in fastf1.plotting.DRIVER_TRANSLATE.items()}
+print(driver_colors)
+
+###############################################################################
+# First create the violin plots to show the distributions.
+# Then use the swarm plot to show the actual laptimes.
+
+# create the figure
+fig, ax = plt.subplots(figsize=(10, 5))
+
+# Seaborn doesn't have proper timedelta support
+# so we have to convert timedelta to float (in seconds)
+driver_laps["LapTime(s)"] = driver_laps["LapTime"].dt.total_seconds()
+
+sns.violinplot(data=driver_laps,
+               x="Driver",
+               y="LapTime(s)",
+               inner=None,
+               scale="area",
+               order=finishing_order,
+               palette=driver_colors
+               )
+
+sns.swarmplot(data=driver_laps,
+              x="Driver",
+              y="LapTime(s)",
+              order=finishing_order,
+              hue="Compound",
+              palette=fastf1.plotting.COMPOUND_COLORS,
+              hue_order=["SOFT", "MEDIUM", "HARD"],
+              linewidth=0,
+              size=5,
+              )
+# sphinx_gallery_defer_figures
+
+###############################################################################
+# Make the plot more aesthetic
+ax.set_xlabel("Driver")
+ax.set_ylabel("Lap Time (s)")
+plt.suptitle("2023 Azerbaijan Grand Prix Lap Time Distributions")
+sns.despine(left=True, bottom=True)
+
+plt.tight_layout()
+plt.show()

requirements-dev.txt

@@ -13,5 +13,6 @@ xdoctest
 pre-commit
 requests>=2.28.1
 websockets>=10.3
+seaborn
 plotly
 kaleido