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-# TextualEvaluator
+# 📝 ProText-Analyzer
+
+**Objective**:  
+The **ProText-Analyzer** project extracts article content from provided URLs and performs various text analysis tasks like sentiment scoring, readability measurement, and more. The results are structured in a clean and organized format, ready for review and further use.
+
+## Project Overview
+
+The goal of **ProText-Analyzer** is to:
+1. **Extract Textual Data**: Fetch the article content from URLs provided in the `Input.xlsx` file.
+2. **Perform Textual Analysis**: Calculate the following metrics:
+   - Sentiment scores (positive, negative, polarity, subjectivity)
+   - Readability scores (Fog Index, Avg. Sentence Length)
+   - Word count, syllable count, and other word statistics
+
+---
+
+## Technologies Used
+
+- **Python** 🐍
+   - Libraries:
+     - `TextBlob` for sentiment analysis
+     - `spaCy` for text processing tasks (tokenization, POS tagging, etc.)
+     - `Syllapy` for syllable counting
+     - `BeautifulSoup` for HTML parsing during data extraction
+     - `Requests` for handling HTTP requests
+- **Pandas** for data management
+- **Excel/CSV** for input/output handling
+
+---
+
+## Installation
+
+1. Clone the repository to your local machine:
+   ```bash
+   git clone https://github.com/rubydamodar/ProText-Analyzer.git
+   cd ProText-Analyzer
+   ```
+
+2. Install the required Python libraries:
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+---
+
+## Data Extraction Process
+
+The **ProText-Analyzer** extracts the article title and body from each URL listed in the `Input.xlsx` file and stores the text for further analysis.
+
+### Process Overview:
+1. **Read Input File**: Load the URLs and their associated IDs from `Input.xlsx`.
+2. **Extract Article Content**:
+   - Fetch HTML content using `requests`.
+   - Parse the HTML using `BeautifulSoup` to extract the article's title and body.
+   - Save the extracted content into text files named after the `URL_ID`.
+
+### File Management:
+- Each article's content is saved in text files, facilitating a clean process for further analysis.
+- Error handling ensures proper management of file I/O and network issues.
+
+---
+
+## Text Analysis Process
+
+The extracted text undergoes several analysis steps to compute the following variables:
+
+1. **Sentiment Analysis**:
+   - Implemented using `TextBlob` to compute **Positive Score**, **Negative Score**, **Polarity Score**, and **Subjectivity Score**.
+   - Text is cleaned by removing stop words and irrelevant characters.
+
+2. **Readability Analysis**:
+   - Calculated using the Gunning Fog Index.
+   - Additional metrics: **Average Sentence Length**, **Percentage of Complex Words**, and **Fog Index**.
+
+3. **Word-Level Metrics**:
+   - **Word Count**, **Complex Word Count**, **Syllable Count per Word** (via `syllapy`), **Personal Pronouns Count** (using regex), and **Average Word Length**.
+
+---
+
+## Output Structure
+
+The results are saved in **Excel/CSV** format as per the structure outlined in `Output Data Structure.xlsx`. The following variables are included:
+- Positive Score
+- Negative Score
+- Polarity Score
+- Subjectivity Score
+- Average Sentence Length
+- Complex Word Count
+- Word Count
+- Syllable Count
+- Personal Pronouns Count
+- Average Word Length
+
+---
+
+## How to Run
+
+1. **Data Extraction**:
+   Run the script to extract article data from the URLs:
+   ```bash
+   python data_extraction.py
+   ```
+
+2. **Text Analysis**:
+   Run the text analysis script to process the extracted articles:
+   ```bash
+   python text_analysis.py
+   ```
+
+The results will be saved in the output directory in `.csv` or `.xlsx` format.
+
+---
+
+## Challenges and Solutions
+
+- **Error Handling**: Implemented robust error handling to manage potential network and file-related issues.
+- **Text Processing**: Utilized advanced tools like `spaCy` for precise text tokenization and POS tagging, and `syllapy` for syllable counting.
+- **Personal Pronouns**: Regex was used to accurately capture pronouns without including words like "US" mistakenly.
+
+---
+
+## Contributing
+
+We welcome contributions to enhance **ProText-Analyzer**! To contribute:
+1. Fork the repository.
+2. Create a new branch for your changes.
+3. Submit a pull request with a detailed description of your changes.
+
+---
+
+## License
+
+This project is licensed under the [MIT License](LICENSE).
+
+---
+
+### Project Maintainer
+Ruby Poddar  
+Email: rubypoddarr@gmail.com 
+
+