NLPFreq is a robust Command-Line Interface (CLI) tool designed for semantic profiling. It facilitates the analysis of raw text, files, or websites, offering enhanced data visualization, exploration, and integration capabilities.
Note: NLPFreq has not been tested on Windows-based systems yet.
Ensure you meet the following requirements before installation:
pip install -r requirements.txt- Data Loading: Load text data from various sources, including raw input, files, and websites, with interactive prompts for user input.
- Text Preprocessing: Tokenize and clean the text data, removing punctuation and converting words to lowercase.
- Metrics Generation: Calculate and display key metrics, including character count with and without spaces, sentence count, word count, and paragraph count.
- Morphological Analysis: Generate a detailed table of word morphology, including word rank, original form, lemmatized form, part-of-speech (POS) tag, percentage occurrence, and count.
- Export Functionality: Optionally export the generated metrics, frequency tables, and visualizations to files.
- Word Cloud Visualization: Create and display a word cloud visualization of the processed text data.
- Word Frequency Chart: Generate and visualize the frequency of the top 20 words in the text.
- Interactive Commands: Utilize command-line interface commands to perform actions such as displaying metrics, limiting results, searching for specific words, and generating visualizations.
You can install the nlpfreq package directly from PyPI using the following command:
pip install nlpfreq- Clone the project:
git clone <repository_url>
cd NLPFreq- Build the package:
python3 setup.py sdist bdist_wheel- Install the package:
pip install dist/*.tar.gz- Run the simulation:
nlpfreqDisplay metrics generated from the loaded data:
nlpfreq show-metrics --export--export: Save metrics to files.
Limit the analysis to the top n highest occurring words:
nlpfreq limit --n <n>--n: Specify the number of top words to display.
Search for a specific word in the morphological data:
nlpfreq search-word --word <word>--word: Specify the word to search for.
Generate and display a word cloud visualization:
nlpfreq generate-wordcloud --export--export: Save the word cloud image.
Generate and display a word frequency plot:
nlpfreq generate-wordfreq-plot --export--export: Save the word frequency plot.
A: NLPFreq is a tool designed for in-depth analysis of textual data, focusing on extracting meaning and linguistic insights. It provides features like word frequency, morphology, and metrics generation, enhancing data exploration and visualization.
A: NLPFreq was created for the ADSA subject in the fifth semester of college. The goal was to offer a versatile NLP tool, empowering users to analyze and profile text efficiently. The tool's features aim to deepen understanding and exploration of linguistic aspects within textual data.
A: Originally conceived as a word frequency counter, NLPFreq's development took a different direction. The decision to expand its capabilities was driven by the desire to create a more comprehensive tool for natural language processing. The project evolved to encompass semantic profiling, offering a richer set of features such as morphology analysis, metrics generation, and enhanced data visualization. This shift aimed to provide users with a more powerful and versatile solution for exploring and understanding textual data beyond simple word frequency analysis.
[Acknowledge contributors, libraries used, or any other relevant acknowledgments here.]