fio-l1-vienna-shapefile-recovery

Rerun

import geopandas as gpd
import pandas as pd
import json

def main():
    # Load the column map
    # The file seems to have some leading whitespace and is comma separated
    # Looking at the content: "     1\ttruncated,original"
    # Actually it looks like it might be tab separated for the first part or just spaces.
    # Let's try reading it with pandas.
    
    column_map_df = pd.read_csv('column_map.csv', sep=',', skipinitialspace=True)
    # Based on the Read output, the first column is index, then 'truncated', then 'original'
    # But the first line is "     1\ttruncated,original". 
    # Let's inspect the column names of the dataframe.
    
    # Since the column map is provided, let's clean it up.
    # It looks like it might be a bit messy. Let's read it manually if needed.
    
    # Let's try to load the shapefile first to see the current column names.
    gdf = gpd.read_file('parcels.shp')
    print("Original columns:", gdf.columns.tolist())
    print("Original data preview:\n", gdf.head(1))

    # Load column map and create a mapping dictionary
    # Mapping: truncated_name -> original_name
    mapping = {}
    # The Read output shows:
    #      1	truncated,original
    #      2	KATASTRALG,KATASTRALGEMEINDE_NAME
    # ...
    # It looks like the columns are actually: [Unnamed: 0, truncated, original]
    # where 'truncated' is the old name in the shp and 'original' is the new name.
    
    # Re-reading column_map.csv more carefully.
    # It's comma separated, but the first "column" might contain the index and the 'truncated' name separated by tab/space?
    # Let's just parse it line by line to be safe.
    
    mapping = {}
    with open('column_map.csv', 'r', encoding='utf-8') as f:
        lines = f.readlines()
        # Skip header
        for line in lines[1:]:
            if ',' in line:
                parts = line.strip().split(',')
                if len(parts) == 2:
                    # The first part is 'index\ttruncated'
                    # Or something similar. Let's split by whitespace/tabs.
                    first_part = parts[0].split()
                    if len(first_part) >= 2:
                        truncated = first_part[-1]
                        original = parts[1]
                        mapping[truncated] = original

    print("Mapping dictionary:", mapping)

    # Rename columns
    # We only want to rename columns that exist in the gdf and are in our mapping
    rename_dict = {k: v for k, v in mapping.items() if k in gdf.columns}
    gdf = gdf.rename(columns=rename_dict)

    # Ensure geometry is Polygon or MultiPolygon (geopandas does this by default for shp)
    # We will check it just in case.
    if not any(gdf.geometry.type.isin(['Polygon', 'MultiPolygon'])):
        print("Warning: No Polygon or MultiPolygon geometries found!")
    
    # Save to GeoJSON
    # GeoJSON requires UTF-8, which is standard for geopandas to write.
    gdf.to_file('parcels.geojson', driver='GeoJSON')
    print("Successfully saved parcels.geojson")

if __name__ == "__main__":
    main()

import geopandas as gpd
import pandas as pd

def main():
    # Load the column map
    mapping = {}
    with open('column_map.csv', 'r', encoding='utf-8') as f:
        lines = f.readlines()
        # Skip header
        for line in lines[1:]:
            line = line.strip()
            if not line:
                continue
            if ',' in line:
                # Split by the first comma
                parts = line.split(',', 1)
                if len(parts) == 2:
                    # parts[0] might be "1\tKATASTRALG"
                    # parts[1] is "KATASTRALGEMEINDE_NAME"
                    # Let's use split() to get the last word of the first part
                    left_side_words = parts[0].split()
                    if left_side_words:
                        truncated = left_side_words[-1]
                        original = parts[1].strip()
                        mapping[truncated] = original

    print("Mapping dictionary created:", mapping)

    # Load the shapefile
    gdf = gpd.read_file('parcels.shp')
    print("Original columns:", gdf.columns.tolist())

    # Rename columns based on the mapping
    # We use the mapping to rename columns in gdf
    # Note: gdf.rename expects a dict of {old_name: new_name}
    gdf = gdf.rename(columns=mapping)
    
    print("Renamed columns:", gdf.columns.tolist())

    # Save to GeoJSON
    # GeoJSON driver handles UTF-8 and geometry types automatically.
    gdf.to_file('parcels.geojson', driver='GeoJSON')
    print("Successfully saved parcels.geojson")

if __name__ == "__main__":
    main()