Reading multiple shapefiles and getting error 'A LinearRing must have at least 3 coordinate tuples'

Question

I am reading multiple shapefiles (around 14) using the function below:

def import_shapes_list(path_to_data:str,shapes_folder:str,crs:str) ->gpd.GeoDataFrame:
    """
    """
    files = glob.iglob(path_to_data+shapes_folder+'*.shp')    
   
    gdfs = [gpd.read_file(file).to_crs(crs) for file in files]
    
    for gdf in gdfs:        
        gdf.columns = map(str.lower, gdf.columns)
    geomap = gpd.GeoDataFrame( pd.concat( gdfs, ignore_index=True) )   
    
    return geomap 

 geomap = import_shapes_list(path_to_data=xxx,shapes_folder=xxx,crs='EPSG:4326')

The error A LinearRing must have at least 3 coordinate tuples tells me that a polygon must have at least three points.

I tried to fix this by introducing try and except

try:
    # xxx
except ValueError:
    # xxx

As follows:

try:    
   gdfs = [gpd.read_file(file).to_crs(crs) for file in files]

except:
     print(e)
return gdfs

but I am still getting the same error. I also have no idea where that polygon with error is as I have 14 shapefiles.

Any idea on how to tackle this?

Answer 1

This approach worked for me:

#Check Geometry
def isvalid(geom)-> int:
    try:
        shape(geom)
        return 1
    except:
        return 0
    
def read_gdf(file:str)->gpd.GeoDataFrame:
    #Read data
    collection = list(fiona.open(file,'r'))
    df1 = pd.DataFrame(collection)

    
    df1['isvalid'] = df1['geometry'].apply(lambda x: isvalid(x))
    df1 = df1[df1['isvalid'] == 1]
    collection = json.loads(df1.to_json(orient='records'))

    #Convert to geodataframe
    return gpd.GeoDataFrame.from_features(collection)

def import_shapes_list(path_to_data:str,shapes_folder:str,crs:str) ->gpd.GeoDataFrame:
    """
    """
    files = glob.iglob(pathxxxxx+'*.shp')
    
    gdfs = []
    for file in files:
        print(file)
        #gdf = gpd.read_file(file).to_crs(crs)
        gdf = read_gdf(file)
        gdf.columns = map(str.lower, gdf.columns)
        gdfs.append(gdf)
        
   
    geomap = gpd.GeoDataFrame( pd.concat( gdfs, ignore_index=True) )   
    
    return geomap