semvec/pypi-packages huggingface dataset:
take-ngram 0.1.1
Analysis of N-gram in a set of messages
License: MIT License
Keywords: ngram,chatbot

# 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('teste.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