JSON to pandas DataFrame

Question

What I am trying to do is extract elevation data from a google maps API along a path specified by latitude and longitude coordinates as follows:

from urllib2 import Request, urlopen
import json

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()

This gives me a data that looks like this:

elevations.splitlines()

['{',
 '   "results" : [',
 '      {',
 '         "elevation" : 243.3462677001953,',
 '         "location" : {',
 '            "lat" : 42.974049,',
 '            "lng" : -81.205203',
 '         },',
 '         "resolution" : 19.08790397644043',
 '      },',
 '      {',
 '         "elevation" : 244.1318664550781,',
 '         "location" : {',
 '            "lat" : 42.974298,',
 '            "lng" : -81.19575500000001',
 '         },',
 '         "resolution" : 19.08790397644043',
 '      }',
 '   ],',
 '   "status" : "OK"',
 '}']

when putting into as DataFrame here is what I get:

pd.read_json(elevations)

and here is what I want:

I'm not sure if this is possible, but mainly what I am looking for is a way to be able to put the elevation, latitude and longitude data together in a pandas dataframe (doesn't have to have fancy mutiline headers).

If any one can help or give some advice on working with this data that would be great! If you can't tell I haven't worked much with json data before...

EDIT:

This method isn't all that attractive but seems to work:

data = json.loads(elevations)
lat,lng,el = [],[],[]
for result in data['results']:
    lat.append(result[u'location'][u'lat'])
    lng.append(result[u'location'][u'lng'])
    el.append(result[u'elevation'])
df = pd.DataFrame([lat,lng,el]).T

ends up dataframe having columns latitude, longitude, elevation

Answer 1

Check this snip out.

# reading the JSON data using json.load()
file = 'data.json'
with open(file) as train_file:
    dict_train = json.load(train_file)

# converting json dataset from dictionary to dataframe
train = pd.DataFrame.from_dict(dict_train, orient='index')
train.reset_index(level=0, inplace=True)

Hope it helps :)

Answer 2

The problem is that you have several columns in the data frame that contain dicts with smaller dicts inside them. Useful Json is often heavily nested. I have been writing small functions that pull the info I want out into a new column. That way I have it in the format that I want to use.

for row in range(len(data)):
    #First I load the dict (one at a time)
    n = data.loc[row,'dict_column']
    #Now I make a new column that pulls out the data that I want.
    data.loc[row,'new_column'] = n.get('key')

Answer 3

You could first import your json data in a Python dictionnary :

data = json.loads(elevations)

Then modify data on the fly :

for result in data['results']:
    result[u'lat']=result[u'location'][u'lat']
    result[u'lng']=result[u'location'][u'lng']
    del result[u'location']

Rebuild json string :

elevations = json.dumps(data)

Finally :

pd.read_json(elevations)

You can, also, probably avoid to dump data back to a string, I assume Panda can directly create a DataFrame from a dictionnary (I haven't used it since a long time :p)

Answer 4

I found a quick and easy solution to what I wanted using json_normalize function included in the latest release of pandas 0.13.

from urllib2 import Request, urlopen
import json
from pandas.io.json import json_normalize

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)
json_normalize(data['results'])

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

Answer 5

billmanH's solution helped me but didn't work until i switched from:

n = data.loc[row,'json_column']

to:

n = data.iloc[[row]]['json_column']

here's the rest of it, converting to a dictionary is helpful for working with json data.

import json

for row in range(len(data)):
    n = data.iloc[[row]]['json_column'].item()
    jsonDict = json.loads(n)
    if ('mykey' in jsonDict):
        display(jsonDict['mykey'])