To ensure that a table (address data from OpenAddresses in this case) with latitude and longitude columns is imported as a geospatial dataset, we have to use the Shapely library's Point class. Each Point geometry is generated from the LON and LAT fields of the address dataset which has been imported:

import geopandas as gdp
import cartoframes
import pandas as pd
from shapely.geometry import Point
APIKEY = "{API KEY}"
cc = cartoframes.CartoContext(base_url='https://{username}.carto.com/',
                              api_key=APIKEY)
address_df = pd.read_csv(r'data/city_of_juneau.csv')
geometry = [Point(xy) for xy in zip(address_df.LON, address_df.LAT)]
address_df = address_df.drop(['LON', 'LAT'], axis=1)
crs = {'init': 'epsg:4326'}
geo_df = gdp.GeoDataFrame(address_df, crs=crs, geometry=geometry)
cc.write(geo_df, 'juneau_addresses')