Challenge: I'm trying to create a new dictionary from my geojson dictionary that is filtered for only the countries of interest because the raw geojson file is too large for visualization.
I have a geojson file with the below form, which I've created an empty dictionary to replicate:
newData = {'features': {},
'properties':{'ADMIN':"",
'ISO_A3':"",
},
'geometry':{'type':"",
'coordinates':""
},
'id':""
}
Below is an example of one of the elements from the geojson file:
data['features'][3]
{'type': 'Feature',
'properties': {'ADMIN': 'Aruba', 'ISO_A3': 'ABW'},
'geometry': {'type': 'Polygon',
'coordinates': [[[-69.99693762899992, 12.577582098000036],
[-69.93639075399994, 12.53172435100005],
[-69.92467200399994, 12.519232489000046],
[-69.91576087099992, 12.497015692000076],
[-69.88019771999984, 12.453558661000045],
[-69.87682044199994, 12.427394924000097],
[-69.88809160099993, 12.417669989000046],
[-69.90880286399994, 12.417792059000107],
[-69.93053137899989, 12.425970770000035],
[-69.94513912699992, 12.44037506700009],
[-69.92467200399994, 12.44037506700009],
[-69.92467200399994, 12.447211005000014],
[-69.95856686099992, 12.463202216000099],
[-70.02765865799992, 12.522935289000088],
[-70.04808508999989, 12.53115469000008],
[-70.05809485599988, 12.537176825000088],
[-70.06240800699987, 12.546820380000057],
[-70.06037350199995, 12.556952216000113],
[-70.0510961579999, 12.574042059000064],
[-70.04873613199993, 12.583726304000024],
[-70.05264238199993, 12.600002346000053],
[-70.05964107999992, 12.614243882000054],
[-70.06110592399997, 12.625392971000068],
[-70.04873613199993, 12.632147528000104],
[-70.00715084499987, 12.5855166690001],
[-69.99693762899992, 12.577582098000036]]]},
'id': 'ABW'}
I also have a data frame object of the countries that I'm actually interested in analyzing:
df_Country.head()
2 Italy
3 Spain
4 Portugal
5 United Arab Emirates
6 Egypt
This file has a number of countries that are unnecessary for the analysis I'm performing so I'd like to filter them out. I believe that this is similar to filtering a nested dictionary. To do this I've tried to create an empty dictionary and loop through it adding in the values of the geo_data whenever I have a match to df_Countries. Below is what I've attempted:
for i in range(len(data['features'])):
if data['features'][i]['properties']['ADMIN'] in df_Country:
newData['properties']['ADMIN'] = data['features'][i]['properties']['ADMIN']
newData['properties']['ISO_A3'] = data['features'][i]['properties']['ISO_A3']
newData['geometry']['type'] = data['features'][i]['geometry']['type']
newData['geometry']['coordinates'] = data['features'][i]['geometry']['coordinates']
newData['id'] = data['features'][i]['id']
At the end of this, my newData dictionary is still empty. Any thoughts? Thank you in advance!
You were really close! You can do a one-liner list comprehension like this:
# example data
geo_json = [
{'type': 'Feature',
'properties': {'ADMIN': 'Italy', 'ISO_A3': 'ABW'},
'geometry': {'type': 'Polygon',
'coordinates': [[[-69.99693762899992, 12.577582098000036],
[-69.99693762899992, 12.577582098000036]]]},
'id': 'ABW'},
{'type': 'Feature',
'properties': {'ADMIN': 'Aruba', 'ISO_A3': 'ABW'},
'geometry': {'type': 'Polygon',
'coordinates': [[[-69.99693762899992, 12.577582098000036],
[-69.99693762899992, 12.577582098000036]]]},
'id': 'ABW'},
{'type': 'Feature',
'properties': {'ADMIN': 'Spain', 'ISO_A3': 'ABW'},
'geometry': {'type': 'Polygon',
'coordinates': [[[-69.99693762899992, 12.577582098000036],
[-69.99693762899992, 12.577582098000036]]]},
'id': 'ABW'},
]
# countries you want
countries = ['Italy', 'Spain']
# new list of geo_json but only ones with ['properties']['ADMIN'] in countries
filtered = [geo for geo in geo_json if geo['properties']['ADMIN'] in countries]
# pretty print the results
from pprint import pprint
pprint(filtered)
The comparable for loop to that comprehension would look like:
filtered = []
for geo in geo_json:
if geo['properties']['ADMIN'] in countries:
filtered.append(geo)
Output (just Spain and Italy, there were 3 in geo_json):
[{'geometry': {'coordinates': [[[-69.99693762899992, 12.577582098000036],
[-69.99693762899992, 12.577582098000036]]],
'type': 'Polygon'},
'id': 'ABW',
'properties': {'ADMIN': 'Italy', 'ISO_A3': 'ABW'},
'type': 'Feature'},
{'geometry': {'coordinates': [[[-69.99693762899992, 12.577582098000036],
[-69.99693762899992, 12.577582098000036]]],
'type': 'Polygon'},
'id': 'ABW',
'properties': {'ADMIN': 'Spain', 'ISO_A3': 'ABW'},
'type': 'Feature'}]