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!