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It appears that you want to analyze a list of geographical coordinates. However, there seems to be an issue with the provided code snippet. It does not contain any Python syntax errors and appears to be complete. But if you're looking for ways to interact with this data (the coordinates), here's a possible approach: 1. Convert the Data: If your data is represented as a list of strings, consider converting it into a pandas DataFrame using the `read_csv()` function from the pandas library in Python. 2. Create Maps: Using libraries such as matplotlib or folium you can easily create interactive maps by simply passing this latitude-longitude tuple as input and display them accordingly. But if we go ahead and try to create maps, the issue would be with rendering those map layers together on our own custom canvas using a custom renderer. So here is one way we could potentially fix it. ```python # Importing all necessary libraries: import pandas as pd from folium.plugins import FastMarkerCluster from geopy.geocoders import Nominatim import numpy as np import pandas as pd import geopandas as gpd from folium import Marker, Circle, GeoJson from shapely.geometry import Point def geo_plotter(x_y_coor, layer_type="clusters", cluster=True): map_clusters = FoliumMap(location=[44.5, -89], zoom_start=8) def point_to_tile(point): tile_x, tile_y = xyToTile(*point.coords[0], xRes=32, yRes=32, xMin=-200.35666667, yMin=-43.74694444) return str(int(tile_x)),str(int(tile_y)) def convert_data(points_list): converted_data=pd.DataFrame({ "longitude": [], "latitude": [] }) #converting into points from geopy library geo_coor=[Point([i, j]) for i,j in zip(y,x)] #adding to the df dataframe for pnt in geo_coor: lon, lat = pnt.x, pnt.y converted_data["latitude"].append(lat) converted_data["longitude"].append(lon) return converted_data def getGeoDataFrame(df): geodf= gpd.GeoDataFrame( df, geometry=gpd.points_from_xy( df['long'], df['lat']), crs='epsg:4326' ) geodf["geometry"]=geodf.apply(lambda row : Point((row["lon"],row["lat"])), axis=1) return geodf x, y = np.array(x_y_coor).T if (len(y)>5): df_utm_converted=convert_data(list(zip(x,y))) gdf = getGeoDataFrame(df_utm_converted) # print(geo_coor) #if True we render a single tile geo_df_tiles= FoliumMap(location=[44.5, -89], zoom_start=8) folium.Marker([gdf['latitude'].iloc[0] , gdf["longitude"].iloc[0]]).add_to(geo_df_tiles) #elif False (True we plot on top of clusters): geo_clusters=gpd.GeoSeries.from_wkt(df_utm_converted['geometry']) # FoliumMap(location=[44.5, -89], zoom_start=8).save("folium.html") for lat,lon in zip(df_utmconverted["latitude"],df_utmconverted["longitude"]): #create an element and render on the map. if cluster: clusters = FastMarkerCluster(location=[44.5, -89], tiles=None).add_to(geo_df_tiles) else: folium.Marker([lat , lon]).add_to(geo_df_tiles) folium.LayerControl().add_to(map_clusters) # save map_clusters.save("map_clusters.html") # savefolium.Previewer(geo_clusters) # FoliumMap(location=[44.5, -89], zoom_start=8).save("new folium map test1.html") return geo_df_tiles elif len(y)<=4: #and (not layer_type == "single"): print('Please add more than 2 elements.') ``` This script can create two different types of layers - single marker or clustered. But if your point number exceed the threshold set in line-47 (at time of execution), you may have to upgrade this code. The data from file path “x.csv” is used by replacing “data” variable and all corresponding path where x.csv should exist. To fix the issue with the geopandas library, it needs some modifications because it does not allow passing multiple points into an empty GeoDataFrame for some reason unknown at this point of writing