My Aspect Library
Overview
My Aspect Library is a Python package designed for performing aspect-based sentiment analysis with integrated translation capabilities. This library allows you to easily translate text, extract aspects, and analyze sentiment, making it a powerful tool for natural language processing tasks.
Features
- Translation: Automatically translate text in your dataset to the target language before analysis.
- Aspect Extraction: Extract aspect terms from text using state-of-the-art models.
- Sentiment Analysis: Analyze sentiment associated with extracted aspects.
- Data Processing: Clean and process text data for analysis, including stopword removal and text normalization.
- Pivot Table Generation: Create pivot tables to summarize sentiment analysis results.
Installation
To install the package, you can simply clone the repository and use setup.py to install it:
git clone https://github.com/yourusername/my_aspect_library.git
cd my_aspect_library
pip install .
Alternatively, if you want to install it in editable mode:
pip install -e .
Usage
Here’s a quick example of how to use the library:
import pandas as pd
from my_aspect_library import AspectExtractor, translate_aspects, create_pivot_table, concatenate_results
df = pd.read_excel('path_to_your_file.xlsx')
aspect_extractor = AspectExtractor()
result_df = aspect_extractor.extract(df, column_name='Customer Comments', target_language='en')
translated_aspects = translate_aspects(result_df)
pivot_table = create_pivot_table(translated_aspects)
Dependencies
pandas
deep_translator
unlimited_machine_translator
pyabsa
nltk
These dependencies are automatically installed when you install the package.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Contributing
If you want to contribute to this project, feel free to fork the repository and submit a pull request.
Acknowledgments
Special thanks to all the contributors and maintainers of the libraries that this project depends on.