Metadata-Version: 2.1
Name: take-ngram
Version: 0.1.0
Summary: Analysis of N-gram in a set of messages
Home-page: UNKNOWN
Author: Data & Analytics Research
Author-email: analytics.dar@take.net
Maintainer: daresearch
Maintainer-email: anaytics.dar@take.net
License: MIT License
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](#installation)
        * [Usage](#usage)
        
        ## Installation
        The `take_ngram` package cab be installed from PyPI.
        
        ```bash
        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.
        ```python
        from take_ngram import NGram
        bigram = NGram('file.csv',
                       'Structured Message')
        bigram.get_word_cloud()
        ```
        
        2. Creating a BiGram of the sentences and saving the WordCloud.
        ```python
        from take_ngram import NGram
        bigram = NGram('file.csv', 
                       'Structured Message')
        bigram.get_word_cloud(file_path='image.png')
        ```
        
        3. Adding stop words
        ```python
        from take_ngram import NGram
        bigram = NGram('file.csv', 
                       'Structured Message',
                        stop_words = ['segunda'])
        bigram.get_word_cloud(file_path='image.png')
        ```
        
        4. Removing prepositions from stop words
        - By default prepositions are added to the stop words
        ```python
        from take_ngram import NGram
        bigram = NGram('file.csv', 
                       'Structured Message', 
                       remove_prepositions=False)
        bigram.get_word_cloud(file_path='image.png')
        ```
        
        5. Making n-grams for some specific subjects.
        ```python
        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
        
Keywords: ngram,chatbot
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
