BRWording - Text Analytics for Portuguese Wordings

Create an easy Text Analytics in One-Line-Code

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Main Features:

• Load Excel, CSV and TXT file types
• Stemming
• Lemmatization
• Stopwords
• TD-IDF
• Sentimental Analysis
• Graphical interpretation
• Word Cloud

The TF-IDF was calculated by:

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How to Install

pip install BRWording
pip install pdfminer-six

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How to use

sintax:

from brwording.brwording import wording

w = brwording.wording()

w.load_file('data/example.txt',type='txt')
w.build_tf_idf(lemmatizer=True,stopwords=True)

w.tfidf

The fields to load_file are: 3. file: the file path 3. type: file type, can be txt csv or excel 3. header: if you are reading a csv file, so you must tell if this file has a header or not (False or True) 0. sep: if you are reading a csv file, you must tell what kind field separator you want 0. column: if you read a csv or excelfile, you must tell what column you want to parse

The method build_tf_idf has a default Trueoption for both parameters.

Output

If want to see the sentimental Graphical interpretation

sintax:

w.sentimental_graf()

You can rotate the graph if you pass rotate=True in argument

output

You can print the same information as a table using the follow command:

sintax:

w.sentimental_table()

if you want to create a wordcloud, just strike the folowing command, but if you want to create a cloud with your own mask, just pass you image address as picture

sintax:

w.word_cloud(picture='none')

output

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Looking for a word into colection

if you want to see what files on your colection has a word, run look3word

sintax:

w.look3word('bonito')

New features are incoming.

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enjoi!