Prepare JSON data from sentiment analysis to perform Logistic Regression I'm new to this field, so very sorry for this basic question.
I'm working on a text analysis project using Google's NLP API along with some other APIS. After performing the sentiment analysis I have its results in JSON format and now I need to apply the Logistic regression, I have no idea how can I prepare my JSON data to perform Logistic regress.

Here's a sample of my data:

{  
   'documentSentiment':{  
      'polarity':-0.3,
      'magnitude':0,
      'score':0
   },
   'language':'en',
   'sentences':[  
      {  
         'text':{  
            'content':'{\\rtf1\\ansi\\ansicpg1252\\cocoartf1639\\cocoasubrtf100\n{\\fonttbl\\f0\\fswiss\\fcharset0 Helvetica;}\n{\\colortbl;\\red255\\green255\\blue255;}\n{\\*\\expandedcolortbl;;}\n\\paperw11900\\paperh16840\\margl1440\\margr1440\\vieww10800\\viewh8400\\viewkind0\n\\pard\\tx566\\tx1133\\tx1700\\tx2267\\tx2834\\tx3401\\tx3968\\tx4535\\tx5102\\tx5669\\tx6236\\tx6803\\pardirnatural\\partightenfactor0',
            'beginOffset':-1
         },
         'sentiment':{  
            'polarity':-1,
            'magnitude':0,
            'score':0
         }
      },
      {  
         'text':{  
            'content':'\\f0\\fs24 \\cf0 This is the first text file.}',
            'beginOffset':-1
         },
         'sentiment':{  
            'polarity':1,
            'magnitude':0,
            'score':0
         }
      }
   ]
}


How can I prepare this data to perform Logistic Regression?
I will use Pandas, Numpy and Sckikit-learn.

Help me, please!

Thanks in advance!
Reputation barrier hence mentioning this as an answer, instead of a comment. This article should lead you the right way, as author has used Twitch API and Python to create his dataset. You shall get a feel of entire data flow.

EDIT: This is a nice tutorial on understanding (basically read/write) JSON files using Python.