I am using Python and I am trying to access the result of function PlacesAPI where I can see supermarkets around me and create a dataframe with few parts of each dictionary inside the main dictionary using a for loop, however I am getting the same information for different rows.
Can you please help me to put each different parts of dictionary in a different row?
Here is my code and the result (now reproducible):
from herepy import PlacesApi
import pandas as pd
def dataframe():
a = {'items': [{'title': 'Marcos Francisco dos Santos Padaria e Mercearia',
'id': 'here:pds:place:07675crc-dfd72cbf57bd45cc9277ed8530ffd61b',
'ontologyId': 'here:cm:ontology:supermarket',
'resultType': 'place',
'address': {'label': 'Marcos Francisco dos Santos Padaria e Mercearia, Rua Oswero Carmo Vilaça, 33, Petrópolis - RJ, 25635-101, Brazil',
'countryCode': 'BRA',
'countryName': 'Brazil',
'stateCode': 'RJ',
'state': 'Rio de Janeiro',
'city': 'Petrópolis',
'district': 'Petrópolis',
'street': 'Rua Oswero Carmo Vilaça',
'postalCode': '25635-101',
'houseNumber': '33'},
'position': {'lat': -22.5315, 'lng': -43.16904},
'access': [{'lat': -22.5314, 'lng': -43.16914}],
'distance': 134,
'categories': [{'id': '600-6300-0066', 'name': 'Grocery', 'primary': True},
{'id': '600-6300-0244', 'name': 'Bakery & Baked Goods Store'}],
'contacts': [{'phone': [{'value': '+552422312493'}]}]},
{'title': 'Mr. Frango',
'id': 'here:pds:place:076jx7ps-7c214f50052f0c23c9e5422ebde7d3cd',
'ontologyId': 'here:cm:ontology:supermarket',
'resultType': 'place',
'address': {'label': 'Mr. Frango, Rua Teresa, Petrópolis - RJ, 25635-530, Brazil',
'countryCode': 'BRA',
'countryName': 'Brazil',
'stateCode': 'RJ',
'state': 'Rio de Janeiro',
'city': 'Petrópolis',
'district': 'Petrópolis',
'street': 'Rua Teresa',
'postalCode': '25635-530'},
'position': {'lat': -22.52924, 'lng': -43.17222},
'access': [{'lat': -22.52925, 'lng': -43.1722}],
'distance': 545,
'categories': [{'id': '600-6300-0066', 'name': 'Grocery', 'primary': True},
{'id': '600-6000-0061', 'name': 'Convenience Store'}],
'references': [{'supplier': {'id': 'core'}, 'id': '1159487213'}],
'contacts': [{'phone': [{'value': '+552422201010'},
{'value': '+552422315720', 'categories': [{'id': '600-6000-0061'}]}]}]},
{'title': 'Mercadinho Flor de Petrópolis',
'id': 'here:pds:place:07675crc-6b03dfbac65a45c0bfc52ab9a3f04556',
'ontologyId': 'here:cm:ontology:supermarket',
'resultType': 'place',
'address': {'label': 'Mercadinho Flor de Petrópolis, Rua Teresa, 2060, Petrópolis - RJ, 25635-530, Brazil',
'countryCode': 'BRA',
'countryName': 'Brazil',
'stateCode': 'RJ',
'state': 'Rio de Janeiro',
'city': 'Petrópolis',
'district': 'Petrópolis',
'street': 'Rua Teresa',
'postalCode': '25635-530',
'houseNumber': '2060'},
'position': {'lat': -22.52895, 'lng': -43.17233},
'access': [{'lat': -22.52895, 'lng': -43.17219}],
'distance': 574,
'categories': [{'id': '600-6300-0066',
'name': 'Grocery',
'primary': True}]}]}
value = []
address = []
latlong = []
teste = pd.DataFrame(columns = ['nome','endereco','rua','numero',
'cidade','estado','cep','lat','long','raio'])
teste['nome'] = []
teste['endereco'] = []
teste['rua'] = []
teste['numero'] =[]
teste['cidade'] = []
teste['estado'] = []
teste['cep'] = []
teste['lat'] = []
teste['long'] = []
teste['raio'] = []
g = pd.DataFrame.from_dict(a.values())
h =[]
for i in range(3):
v = g[i].values[0]
h = v.items()
for k, l in h:
value.append(l)
for c, d in value[4].items():
address.append(d)
for la, lo in value[5].items():
latlong.append(lo)
novo_concorrente = {'nome': value[0], 'endereco':address[0],
'rua':address[7], 'numero':address[9],
'cidade':address[5], 'estado':address[3],
'cep':address[8],'lat':latlong[0],
'long':latlong[1],'raio':value[7]}
teste = teste.append(novo_concorrente, ignore_index=True)
return teste
You should focus on your for
loop. I would suggest you to create a dictionary for each row you want to define in your final DataFrame, and then create a list to append those dictionaries to.
In example:
rows = []
for item in a["items"]:
row = {
"Latitude": item["position"]["lat"],
"Postal code": item["address"]["postalCode"],
}
rows.append(row)
result = DataFrame(rows)
result
Hope it helps as a starting point.