linguistify 0.1.0

A unified toolkit for advanced text processing and linguistic analysis. This package offers a comprehensive set of functions to clean, preprocess, and analyze text data, applying sophisticated linguistic techniques to enhance your text analytics workflow. Whether you're looking to clean raw text or extract detailed linguistic features, Linguistify provides the tools to transform and enrich your text data efficiently.

linguistify

A unified toolkit for advanced text processing and linguistic analysis. linguistify offers a comprehensive set of functions to clean, preprocess, and analyze text data, applying sophisticated linguistic techniques to enhance your text analytics workflow.

The purpose of the linguistify package is to provide tools that simplify and enhance the process of text cleaning and analysis. It aims to:

• Clean Text Data: Remove unwanted elements from text, such as punctuation, URLs, and special characters, and normalize text for consistent processing.
• Feature Extraction: Extract meaningful features from text data, including text length, stop words, and part-of-speech tags, to support various text analysis tasks.
• Preprocess Text: Prepare text data for further analysis or modeling by transforming it into a suitable format.
• Analyze Text: Apply linguistic techniques to derive insights from text, such as identifying key terms, sentiment analysis, and more.

Getting Started

To get started with linguistify, you need to install it. The package is available on PyPI and can be installed using pip. Open your terminal and run the following command:

Installation

pip install linguistify

Usage

Here’s a basic example to get you started:

import pandas as pd
from linguistify.cleaning import clean_text
from linguistify.feature_extraction import add_features_to_dataframe

# Sample text data
data = {
    'text': [
        "Check out our new product launch at https://example.com! We are excited to share it with you. Follow us @CompanyName #ProductLaunch :)"
    ]
}

df = pd.DataFrame(data)

# Clean the text
df['cleaned_text'] = df['text'].apply(clean_text)

# Extract features
df_with_features = add_features_to_dataframe(df, 'cleaned_text')

Examples:

Here is an example of a DataFrame processed by the linguistify package:

text	cleaned_text	length_of_text	num_stop_words	num_digits	num_spaces	num_exclamations	num_questions	num_periods	num_adjectives	num_nouns	num_pronouns	num_verbs	num_adverbs
Check out our new product launch at https://example.com! We are excited to share it with you. Follow us @CompanyName #ProductLaunch :)	check out our new product launch at url we are excit to share it with you follow us mention companynam hashtag productlaunch happi	130	9	0	22	0	0	0	4	6	5	4	0

API

Contribution

Contributions are welcome! If you notice a bug or have suggestions for improvements, please let us know.

Author

• Main Maintainer: Jawaher Alghamdi