Interactive graph example

examples/example_fastf1_interactive_graph.py

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+"""
+Interactive graph for laptimes
+=================================
+
+Plot an interactive graph showing laptimes for each driver lap by lap.
+"""
+
+import fastf1
+import fastf1.plotting
+import plotly.graph_objects as go
+from plotly.io import show
+
+# SETTING UP THE DATA #########################################################
+# load a session
+race = fastf1.get_session(2023, 'Abu Dhabi', 'R')
+race.load(weather=False, telemetry=False)
+
+# Get the list of drivers
+driver_list = list(fastf1.plotting.DRIVER_TRANSLATE.keys())
+
+# Set the colors for the graph: for drivers, we use the combination of both
+# DRIVER_TRANSLATE and DRIVER_COLORS to associate colors with driver's initials
+driver_colors = {
+    key: fastf1.plotting.DRIVER_COLORS[value]
+    for key, value in fastf1.plotting.DRIVER_TRANSLATE.items()
+    }
+
+# Set the colors of each tyre
+compound_colors = fastf1.plotting.COMPOUND_COLORS
+
+# Set titles and labels of the graph
+title = "2023 Abu Dhabi Grand Prix Laptime Evolution"
+xaxis_title = "Lap Number"
+yaxis_title = "Lap Time (s)"
+legend_title = "Driver"
+###############################################################################
+
+
+# DEFINING THE LIMITS OF THE GRAPH#############################################
+# Define the limits of the graph:
+# As we are going to show a representation of the whole race, there are
+# some laps that are considerably slower than the average. We want to keep them
+# in the graph but we don't need to see them, so we're focusing our view in the
+# relevant ones. For this reason, we're picking the fastest lap and the
+# slowest lap of the quick laps and we're defining a margin of 0'5s for the
+# limits of the graph.
+quicklaps = race.laps.pick_quicklaps()
+quicklaps['LapTime(s)'] = quicklaps['LapTime'].dt.total_seconds()
+
+fastest_lap = quicklaps['LapTime(s)'].min()
+min_range_y = fastest_lap - 0.5  # Fastest lap -0'5s
+
+slowest_quicklap = quicklaps['LapTime(s)'].max()
+max_range_y = slowest_quicklap + 0.5  # Slowest lap of the quickest + 0'5s
+
+# Also, we have to define the number of laps for getting a nice x axis.
+# We're picking 0 for start and last lap number + 1
+howmany_laps = race.laps['LapNumber'].max()
+max_range_x = howmany_laps + 1
+###############################################################################
+
+
+# PLOTING THE GRAPH ###########################################################
+fig = go.Figure()
+
+# As we're plotting every driver laptime, is better
+# to use a dynamic method to plot each graph.
+# We use the driver list we got before.
+for driver in driver_list:
+    driver_laps = race.laps.pick_drivers(driver)  # pick all laps
+    driver_laps = driver_laps.reset_index()  # clean index from race.laps
+    # convert to number each laptime
+    driver_laps['LapTime(s)'] = driver_laps['LapTime'].dt.total_seconds()
+    scatter = go.Scatter(
+        x=driver_laps['LapNumber'],
+        y=driver_laps['LapTime(s)'],
+        mode='lines+markers',  # use lines and scatters for each driver
+        name=driver,
+        # use compound colors for scatters
+        marker=dict(color=driver_laps['Compound'].map(compound_colors)),
+        line=dict(color=driver_colors[driver]),  # use driver assigned colors
+        visible='legendonly'
+    )
+    # We set every driver hidden, but for the first view we want to show
+    # two of them. In this case, Verstappen and Leclerc.
+    if (driver == 'VER') | (driver == 'LEC'):
+        scatter.update(visible=True)
+    fig.add_trace(scatter)  # show the trace
+###############################################################################
+
+
+# APPLYING A NICE LAYOUT ######################################################
+# After building the graph, apply the template to the graph
+# We use 'plotly_dark' as default. It coud be possible to define a custom one.
+# We fix the height in 600 to fit all the legeng in the graph.
+fig.update_layout(template='plotly_dark',
+                  height=600)
+
+# Apply titles and labels
+fig.update_layout(dict(
+    title=title,
+    xaxis_title=xaxis_title,
+    yaxis_title=yaxis_title,
+    legend_title=legend_title
+    ))
+
+# Fit the graph to a nice view
+fig.update_yaxes(range=[min_range_y, max_range_y],
+                 griddash='dot')
+fig.update_xaxes(range=[0, max_range_x],
+                 showgrid=False,
+                 showline=False)
+###############################################################################
+
+
+fig
+show(fig)