Create KML files from each row of a GeoPandas DataFrame

Question

I have a multipolygon GeoPandas DataFrame. I want to create a KML file from each polygon of geodataframe.

gdf

sites   geometry
0   site1   POLYGON ((-83.45951 35.03725, -83.45963 35.037...
1   site2   POLYGON ((-83.46075 35.03702, -83.46086 35.037...
2   site3   POLYGON ((-76.56159 38.89046, -76.56166 38.890...
3   site4   POLYGON ((-76.55872 38.89012, -76.55875 38.890...
4   site5   POLYGON ((-59.86998 -2.40509, -59.87006 -2.405...

I've done this so far:

fiona.supported_drivers['KML'] = 'rw' #fiona library wrapped by geopandas supports unofficialy a KML driver that you have to enable by hand.

for index, row in gdf.iterrows():
    file_names = row["sites"]
    output_name = f"{file_names}.kml"
    # Create an output path
    outpath = os.path.join(result_folder, output_name)
    # Export the data
    new_kml = gpd.GeoDataFrame(row, row.geometry)
    new_kml.to_file(outpath, driver='KML')

But getting following error:

new_kml = gpd.GeoDataFrame(row, row.geometry)

TypeError: 'Polygon' object is not iterable

Answer 1

You can use groupby to create a one-row-dataframe for each row and export:

import geopandas as gpd
import numpy as np
import os, fiona

fiona.supported_drivers['KML'] = 'rw' #Enable kml driver
out_folder = r"C:\GIS\data\testdata\KMLs"
df = gpd.read_file(r"C:\GIS\data\testdata\ak_riks_10_fixed.shp")
df["row"] = np.arange(df.shape[0]) #Create a unique row identifier. Not needed if you already have some other unique id

for rownum, subframe in df.groupby("row"): #For each row/rownumber and that row as a dataframe
    filename = os.path.join(out_folder, f"file_{rownum}.kml")    
    subframe.to_file(filename, driver='KML')