Python extract elements from Json string

Question

I have a Json string from which I\'m able to extract few components like formatted_address,lat,lng, but I\'m unable to extract feature(val

Answer 1

I would go for json_normalize, thought of one line answer but I dont think its possible i.e (Here I did only for px_val and py_val you can do similar things for other columns)

from pandas.io.json import json_normalize

import pandas as pd
import json

with open('dat.json') as f:
    data = json.load(f)

result = json_normalize(data,'results')

result['px_val'] = result['geometry'].apply(json_normalize).apply(lambda x : x['location.lat'])
result['py_val'] = result['geometry'].apply(json_normalize).apply(lambda x : x['location.lng'])

print(result[['formatted_address','px_val','py_val']])

                              formatted_address        px_val      py_val
0  Satya Niwas, Kanti Nagar, J B Nagar, Andheri E...  19.109659  72.867471
1  82, Bamanpuri, Ajit Nagar, J B Nagar, Andheri ...  19.109749  72.867249
2  Todi Building, Sheth Bhavanidas Benani Marg, K...  19.109827  72.867789
3  KASI APARTMENTS, Shriniwas Bagarka Rd, Bamanpu...  19.109334  72.867052
4  Silver Line Apts., Bamanpuri, J.B. Nagar, J B ...  19.109108  72.867078
5  Gokul panch chs, 81-B, 81-B, Sheth Bhavanidas ...  19.109871  72.867057
6  Ajit Nagar, J B Nagar, Andheri East, Mumbai, M...  19.110316  72.868073
7  Bamanpuri, J B Nagar, Andheri East, Mumbai, Ma...  19.108435  72.865749
8  J B Nagar, Andheri East, Mumbai, Maharashtra 4...  19.111062  72.865592
9           Andheri East, Mumbai, Maharashtra, India  19.115491  72.872695

I try to parse political certainly not proud of this solution i.e

pol = []
for i in result['address_components'].apply(json_normalize):
     pol.append(','.join(i.apply(lambda x : x['long_name'] if 'political' in x['types'] else np.nan,1).dropna()))

result['political'] = pol

Output result['political']

0    Kanti Nagar,J B Nagar,Andheri East,Mumbai,Mumb...
1    Bamanpuri,Ajit Nagar,J B Nagar,Andheri East,Mu...
2    Kanti Nagar,J B Nagar,Andheri East,Mumbai,Mumb...
3    Bamanpuri,Kanti Nagar,J B Nagar,Andheri East,M...
4    Bamanpuri,J.B. Nagar,J B Nagar,Andheri East,Mu...
5    Bamanpuri,Ajit Nagar,J B Nagar,Andheri East,Mu...
6    Ajit Nagar,J B Nagar,Andheri East,Mumbai,Mumba...
7    Bamanpuri,J B Nagar,Andheri East,Mumbai,Mumbai...
8    J B Nagar,Andheri East,Mumbai,Mumbai Suburban,...
9    Andheri East,Mumbai,Mumbai Suburban,Maharashtr...
Name: political, dtype: object

To convert it to a method we can do

def get_cols(st):
    pol = []
    for i in result['address_components'].apply(json_normalize):
         pol.append(','.join(i.apply(lambda x : x['long_name'] if st in x['types'] else np.nan,1).dropna()))

   return  pol

result['political'] = get_cols('political') 
# This will assign the new column political with data.