import plotly.figure_factory as ff
import pandas as pd
import numpy as np
# Mock GeoDataFrame with latitude, longitude, and value columns
np.random.seed(0)
num_points = 1000
data = {
 'lat': np.random.uniform(40, 45, num_points),
 'lon': np.random.uniform(-75, -70, num_points),
 'value': np.random.uniform(0, 1, num_points)
}
df = pd.DataFrame(data)
df

fig = ff.create_hexbin_mapbox(
 data_frame=df, lat="lat", lon="lon",
 nx_hexagon=50, # Decrease the size of hexagons
 opacity=0.5, labels={"color": "value"},
 color_continuous_scale="Viridis",
 agg_func=np.min, # or np.max aggregation
 show_original_data=True,
 original_data_marker=dict(size=1.1, opacity=0.6, color="deeppink")
)
# Extract the hexbin data
hexbin_data = fig.data[0]
# Check the hexbin values
print("Hexbin values (z):", hexbin_data.z)
# Update the text of each hexagon to display the maximum value
hexbin_data.hovertemplate = 'Value: %{z}<extra></extra>'
# Update the layout to use OSM tiles
fig.update_layout(
 mapbox_style="open-street-map",
 height=800 # Set the desired height
)
fig.show()