Chloropleth cluster points with same lat and lon values

📊 Plotly Python
1

I created a chloropleth plot as follows

    fig = px.choropleth(
        filtered,
        geojson=ward_geojson,
        locations="wardname",
        featureidkey="properties.wardname",
        color="num_health_workers",
        hover_data=["population", "num_health_workers"],
        projection="mercator",
        color_continuous_scale="Greens",  # ✅ Use Greens
        range_color=(
            filtered["num_health_workers"].min(),
            filtered["num_health_workers"].max(),
        ),  # Optional: set min/max scale
        color_continuous_midpoint=filtered[
            "num_health_workers"
        ].median(),  # Optional: midpoint tweak
    )

    # Add custom hovertemplate for the choropleth map
    fig.update_traces(
        hovertemplate="<b>Ward:</b> %{location}<br>"
        "<b>Population:</b> %{customdata[0]:,}<br>"
        "<b>Health Workers:</b> %{customdata[1]:,}<extra></extra>",
        customdata=filtered[["population", "num_health_workers"]].values,
    )

    fig.update_geos(fitbounds="locations", visible=False)
    fig.update_layout(
        geo=dict(
            scope="africa",
            showland=True,
            landcolor="whitesmoke",
            showcountries=True,
        ),
        margin={"r": 0, "t": 0, "l": 0, "b": 0},
    )

    # Facilities
    facility_df = (
        facility_locations[
            facility_locations["facility_stationed"].isin(selected_facilities)
        ]
        if selected_facilities
        else pd.DataFrame()
    )

    if not facility_df.empty:
        # Create a list to store the scatter traces for facilities
        facility_traces = []
        for index, row in facility_df.iterrows():
            scatter_trace = (
                px.scatter_geo(
                    pd.DataFrame([row]),  # Create a DataFrame with the current facility
                    lat="lat",
                    lon="lon",
                    hover_name="facility_stationed",
                )
                .update_traces(
                    mode="markers",
                    marker=dict(size=10, color="black"),
                    hovertemplate="<b>%{hovertext}</b><extra></extra>",
                )
                .data[0]
            )
            facility_traces.append(scatter_trace)

        # Add all facility traces to the figure at once
        for trace in facility_traces:
            fig.add_trace(trace)

The facilities are multiple, using the same central point, making each of the numerous selected facilities replace the other as a single point. I need to modify the plot to add points for each selected facility as a separate point in a cluster. Any suggestions?