Extracting data from list of dictionaries from Tone Analyser's JSON response

Question

I am analysing text using IBM Watson's Tone analyser and I am trying to extract all information relating to the sentence tone (e.g; sentence_id, text, tones, tone_id, tone_name, score) and add that to a dataframe (with columns; sentence_id, text, tones, tone_id, score and tone_name). This is a sample of the output I have:

> [{'document_tone': {'tones': [{'score': 0.551743,
     'tone_id': 'analytical',
     'tone_name': 'Analytical'}]},
  'sentences_tone': [{'sentence_id': 0,
    'text': '@jozee25 race is the basis on which quotas are implemented.',
    'tones': []},
   {'sentence_id': 1, 'text': 'helloooooo', 'tones': []}]},
 {'document_tone': {'tones': []}},
 {'document_tone': {'tones': [{'score': 0.802429,
     'tone_id': 'analytical',
     'tone_name': 'Analytical'},
    {'score': 0.60167, 'tone_id': 'confident', 'tone_name': 'Confident'}]},
  'sentences_tone': [{'sentence_id': 0,
    'text': '@growawaysa @cricketandre i have the answer on top yard from dpw:it is not currently "surplus to govt requirements".it is still being used for garaging until a new facility is ready in maitland.the',
    'tones': [{'score': 0.631014,
      'tone_id': 'analytical',
      'tone_name': 'Analytical'}]},
   {'sentence_id': 1,
    'text': 'cost of the housing options will of course depend on prospects for cross subsidisation.',
    'tones': [{'score': 0.589295,
      'tone_id': 'analytical',
      'tone_name': 'Analytical'},
     {'score': 0.509368, 'tone_id': 'confident', 'tone_name': 'Confident'}]}]},
 {'document_tone': {'tones': [{'score': 0.58393,
     'tone_id': 'tentative',
     'tone_name': 'Tentative'},
    {'score': 0.641954, 'tone_id': 'analytical', 'tone_name': 'Analytical'}]}},
 {'document_tone': {'tones': [{'score': 0.817073,
     'tone_id': 'joy',
     'tone_name': 'Joy'},
    {'score': 0.920556, 'tone_id': 'analytical', 'tone_name': 'Analytical'},
    {'score': 0.808202, 'tone_id': 'tentative', 'tone_name': 'Tentative'}]},
  'sentences_tone': [{'sentence_id': 0,
    'text': 'thanks @khayadlangaand colleagues for the fascinating tour yesterday.really',
    'tones': [{'score': 0.771305, 'tone_id': 'joy', 'tone_name': 'Joy'},
     {'score': 0.724236, 'tone_id': 'analytical', 'tone_name': 'Analytical'}]},
   {'sentence_id': 1,
    'text': 'eyeopening and i learnt a lot.',
    'tones': [{'score': 0.572756, 'tone_id': 'joy', 'tone_name': 'Joy'},
     {'score': 0.842108, 'tone_id': 'analytical', 'tone_name': 'Analytical'},
     {'score': 0.75152, 'tone_id': 'tentative', 'tone_name': 'Tentative'}]}]},

This is the code I have wrote to get this output:

result =[]
for i in helen['Tweets']:
   tone_analysis = tone_analyzer.tone(
       {'text': i},
       'application/json'
   ).get_result()
   result.append(tone_analysis)

Answer 1

First of all, as your JSON is not well-formed, I am using the JSON from the Tone analyzer API reference available here

Using the JSON from the API reference and Pandas json_normalize, here's the code I came up with

from pandas.io.json import json_normalize

jsonfile = {
  "document_tone": {
    "tones": [
      {
        "score": 0.6165,
        "tone_id": "sadness",
        "tone_name": "Sadness"
      },
      {
        "score": 0.829888,
        "tone_id": "analytical",
        "tone_name": "Analytical"
      }
    ]
  },
  "sentences_tone": [
    {
      "sentence_id": 0,
      "text": "Team, I know that times are tough!",
      "tones": [
        {
          "score": 0.801827,
          "tone_id": "analytical",
          "tone_name": "Analytical"
        }
      ]
    },
    {
      "sentence_id": 1,
      "text": "Product sales have been disappointing for the past three quarters.",
      "tones": [
        {
          "score": 0.771241,
          "tone_id": "sadness",
          "tone_name": "Sadness"
        },
        {
          "score": 0.687768,
          "tone_id": "analytical",
          "tone_name": "Analytical"
        }
      ]
    },
    {
      "sentence_id": 2,
      "text": "We have a competitive product, but we need to do a better job of selling it!",
      "tones": [
        {
          "score": 0.506763,
          "tone_id": "analytical",
          "tone_name": "Analytical"
        }
      ]
    }
  ]
}

mydata = json_normalize(jsonfile['sentences_tone'])
mydata.head(3)
print(mydata)

tones_data = json_normalize(data=jsonfile['sentences_tone'], record_path='tones')
tones_data.head(3)
print(tones_data)

The output dataframe will be

   sentence_id                        ...                                            tones
0            0                        ...[{'score': 0.801827, 'tone_id': 'analytical', ...
1            1                        ...[{'score': 0.771241, 'tone_id': 'sadness', 'to...
2            2                        ...[{'score': 0.506763, 'tone_id': 'analytical', ...

[3 rows x 3 columns]
      score     tone_id   tone_name
0  0.801827  analytical  Analytical
1  0.771241     sadness     Sadness
2  0.687768  analytical  Analytical
3  0.506763  analytical  Analytical

Also, I have created REPL for you to change the input and run the code on the browser - https://repl.it/@aficionado/DarkturquoiseUnnaturalDistributeddatabase

Refer this Kaggle link to understand more about flattening JSON in Python using Pandas