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Analysis of N-gram in a set of messages

Project description

Take NGram

TakeNGram is a tool to provide analysis of n-grams in a dataset of messages.

The recommendation usage is with the InsightExtractor Cloud CSV output.

The analysis consists in creation of a dictionary with the n-grams of all messages and their respective frequency. Besides the creation of word cloud of the n-grams.

All analysis can be made in a group of sentences of a subject (most useful with the Insight Extractor output).

Overview

Installation

The take_ngram package cab be installed from PyPI.

pip install take_ngram

Usage

For usage the file must have to be a CSV file.

All the examples are based on the Insight Extractor output.

  1. Creating a BiGram of the sentences and get the WordCloud.
from take_ngram import NGram
bigram = NGram('file.csv',
               'Structured Message')
bigram.get_word_cloud()
  1. Creating a BiGram of the sentences and saving the WordCloud.
from take_ngram import NGram
bigram = NGram('teste.csv', 
               'Structured Message')
bigram.get_word_cloud(file_path='image.png')
  1. Adding stop words
from take_ngram import NGram
bigram = NGram('file.csv', 
               'Structured Message',
                stop_words = ['segunda'])
bigram.get_word_cloud(file_path='image.png')
  1. Removing prepositions from stop words
  • By default prepositions are added to the stop words
from take_ngram import NGram
bigram = NGram('file.csv', 
               'Structured Message', 
               remove_prepositions=False)
bigram.get_word_cloud(file_path='image.png')
  1. Making n-grams for some specific subjects.
from take_ngram import NGram
bigram = NGram('file.csv', 
                'Structured Message', 
                subject_column = 'Groups', 
                subject_list = ['fatura','plano'])
bigram.get_word_cloud(file_path='image.png')

Author

Take Blip Data&Analytics Research

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