Creating a Folium map

gistfile1.txt

def createRentalMap(df, fixed_radius, nbd_or_grp):

    # Initialize a Folium map. Center it to the mean of latitude and longitude of the entire dataset
    this_map = folium.Map(
        location=[df["latitude"].mean(), df["longitude"].mean()],
        tiles="CartoDB positron",
        zoom_start=13,
    )

    def plotDot(point_row, fixed_radius, nbd_or_grp):
        if fixed_radius:
            radius = 30
        else:
            radius = point_row["nbd_count_normalized"]

        if nbd_or_grp == "neighbourhood":
            text = f'{point_row["neighbourhood_cleansed"]}'
        else:
            text = f'{point_row["neighbourhood_group_cleansed"]}'

        folium.CircleMarker(
            location=[point_row["latitude"], point_row["longitude"]],
            radius=radius,
            weight=3,
            color=point_row["glow_marker_color"],
            fill_color=point_row["glow_marker_color"],
            fill_opacity=0.7,
        ).add_child(folium.Tooltip(f"{point_row.name}: {text}")).add_to(this_map)

        # Add text of count within circle
        folium.map.Marker(
            [point_row["latitude"], point_row["longitude"]],
            icon=DivIcon(
                icon_size=(150, 36),
                icon_anchor=(0, 0),
                html='<div style="font-size: 9pt font-weight:bold">%s</div>' % text,
            ),
        ).add_to(this_map)
        return

    # Create circle markers for every listing by applying the plotDot function
    if nbd_or_grp == "neighbourhood":
        df[
            [
                "latitude",
                "longitude",
                "glow_marker_color",
                "nbd_count_normalized",
                "neighbourhood_cleansed",
            ]
        ].apply(plotDot, args=(fixed_radius, nbd_or_grp), axis=1)
    else:
        df[
            [
                "latitude",
                "longitude",
                "glow_marker_color",
                "nbd_count_normalized",
                "neighbourhood_group_cleansed",
            ]
        ].apply(plotDot, args=(fixed_radius, nbd_or_grp), axis=1)
    return this_map