Py) 서울 지반침하 위험도 지도 매핑

import pandas as pd

import geopandas as gpd
import folium
from folium.features import DivIcon
from folium.raster_layers import ImageOverlay

def folium_icon_html(color, size = 20, zindex = 10, bg = False):
    if bg:
        img_bg = f"<img src='https://i.namu.wiki/i/SMBvcToTCTYR_uPh11p8jdvxWXvhzavIAxCk1sKu1kLXNMCA86T13DvTvlX1JTyhL-xENFSXTO0pSe_XDsgvrJTVTzqew5jiccbyY7owSPTltQQ0pCQy6hWLSOqlqZbLOn-EfVvEFxIYlNyi9JUc1A.svg' style='width:{size}px;height:{size}px;'>"
    else:
        img_bg = ""
        
    tx_html = f'''
    <div style="
        width:{size}px;
        height:{size}px;
        background-color:{color};
        border-radius:50%;
        opacity:0.7;
        border:0.5px solid #DDDDDD;
        z-index: {zindex};">
        {img_bg}
    </div>
    '''
    return tx_html


df_map_seoul = gpd.read_file("data/map_seoul_sgg_240314.shp")

df_subway = pd.read_csv("data/서울시 역사마스터 정보.csv", encoding = "CP949")
df_subway["호선"] = df_subway["호선"].str.replace("\(.*?\)", "", regex = True)
df_subway["호선"] = df_subway["호선"].replace("공항철도1호선", "공항철도")
df_subway = df_subway.loc[df_subway["호선"].str.contains("[0-9]|중앙선|신분당선|분당선|수인선|경의선|경춘선|공항철도|신림선"), ]
df_subway_g = df_subway.groupby("역사명").head(1)[["역사명", "위도", "경도"]]
df_subway = df_subway.drop(columns = ["위도", "경도"])
df_subway = pd.merge(df_subway, df_subway_g, on = "역사명")

df_subway_tr = df_subway.groupby("역사명")["호선"].nunique().reset_index()
df_subway["환승역"] = df_subway["역사명"].isin(df_subway_tr.loc[df_subway_tr["호선"] != 1, "역사명"]) + 0

df_subway_line_colors = pd.read_excel("data/subway_seoul_line_colors.xlsx")
df_subway = pd.merge(df_subway, df_subway_line_colors, on = "호선")


m = folium.Map(location = [37.56, 126.98], zoom_start = 11,
               tiles = None,
               width = "800px", height = "600px")

img_overlay = ImageOverlay(
    name = "Custom Bg",
    image = "imgs/seoul_ground_subsidence_risk_map.png",  # 배경 이미지 경로
    bounds = [[37.428, 126.764], [37.702, 127.184]],
    opacity = 0.4,
    interactive = False,
    cross_origin = False,
    zindex = 1,
)
img_overlay.add_to(m)

folium.TileLayer("OpenStreetMap", opacity = 0.5).add_to(m)

folium.GeoJson(
    data = df_map_seoul,
    style_function = lambda feature: {
        'color': '#666666',
        'weight': 1,
        'fillOpacity': 0,
    }
).add_to(m)

val_marker_size = 10

df_subway_tr1 = df_subway.loc[df_subway["환승역"] == 1, ]
df_subway_tr1_g = df_subway_tr1.groupby("역사명")["호선"].min().reset_index()
df_subway_tr1 = pd.merge(df_subway_tr1_g, df_subway_tr1, on = ["역사명", "호선"], how = "inner").reset_index(drop = True)
for n_row in range(len(df_subway_tr1)):
    ser_row = df_subway_tr1.iloc[n_row, ]
    val_line_name = ser_row["호선"]
    val_stn_name  = ser_row["역사명"]
    
    folium.Marker(
        location = [ser_row["위도"], ser_row["경도"]],
        icon = DivIcon(icon_size = (val_marker_size, val_marker_size),
                       html = folium_icon_html(color = ser_row["색상"], 
                                               size = val_marker_size,
                                               bg = 1, 
                                               zindex = 50)), 
        tooltip = f"{val_line_name}: {val_stn_name}",
    ).add_to(m)

df_subway_tr0 = df_subway.loc[df_subway["환승역"] == 0, ]
df_subway_tr0 = df_subway_tr0.loc[~df_subway_tr0["역사명"].isin(df_subway_tr1["역사명"]), ]
for n_row in range(len(df_subway_tr0)):
    ser_row = df_subway_tr0.iloc[n_row, ]
    val_line_name = ser_row["호선"]
    val_stn_name  = ser_row["역사명"]
    
    folium.Marker(
        location = [ser_row["위도"], ser_row["경도"]],
        icon = DivIcon(icon_size = (val_marker_size, val_marker_size),
                       html = folium_icon_html(color = ser_row["색상"], 
                                               size = val_marker_size,
                                               bg = 0)), 
        tooltip = f"{val_line_name}: {val_stn_name}",
    ).add_to(m)

m