Exercise 2 hints

Converting Pandas DataFrame into a GeoDataFrame

Quite often you are in a situation where you have read data e.g. from text file into a Pandas DataFrame where you have latitude and longitude columns representing the location of a record.

  • Let’s continue with the previous example and consider that we have a column where we have stored the shapely geometries:
>>> print(data)
    value  lat  lon     geometry
0      0    2    4  POINT (4 2)
1      5    1    6  POINT (6 1)
2      2    6    1  POINT (1 6)
3      6    6    3  POINT (3 6)
4      5    5    1  POINT (1 5)
  • Notice that now our data is still a Pandas DataFrame, not a GeoDataFrame:
>>> type(data)
  • We need to convert the DataFrame into a GeoDataFrame, so that we can e.g. save it into a Shapefile. It is easily done by passing the DataFrame into a GeoDataFrame object. We need to determine
which column contains the geometry information (needs to be always a column called ‘geometry’), and optionally we can also determine the coordinate reference system when creating the GeoDataFrame:
# Convert DataFrame into a GeoDataFrame
geo = gpd.GeoDataFrame(data, geometry='geometry', crs=from_epsg(4326))

>>> type(geo)

>>> geo.crs
{'init': 'epsg:4326', 'no_defs': True}

Now we have converted Pandas DataFrame into a proper GeoDataFrame that we can export into a Shapefile for instance.