From your code, it looks like you're loading a JSON file which has JSON data on each separate line. read_json supports a lines argument for data like this:

data_df = pd.read_json('C:/Users/Alberto/nutrients.json', lines=True)

Note
Remove lines=True if you have a single JSON object instead of individual JSON objects on each line.

I found a quick and easy solution to what I wanted using json_normalize() included in pandas 1.01.

from urllib2 import Request, urlopen
import json

import pandas as pd    

path1 = '42.974049,-81.205203|42.974298,-81.195755'
request=Request('http://maps.googleapis.com/maps/api/elevation/json?locations='+path1+'&sensor=false')
response = urlopen(request)
elevations = response.read()
data = json.loads(elevations)
df = pd.json_normalize(data['results'])

This gives a nice flattened dataframe with the json data that I got from the Google Maps API.