PDF Text Analysis Tool

The PDF Text Analysis Tool is a Python application that extracts and analyzes text from PDF files, focusing on extracting LOD (Limit of Detection) values and associated units, as well as Sensitivity values and DOIs (Digital Object Identifiers). It provides functionalities to clean and process the extracted data, generating a cleaned and normalized output for further analysis.

Features

• Extracts text from PDF files
• Normalizes text for consistent processing
• Identifies LOD values and associated units
• Identifies Sensitivity values
• Extracts DOIs from PDF text
• Cleans and processes extracted data
• Generates cleaned and normalized output in CSV format

Installation

1. Clone the repository:

git clone https://github.com/chris-cozy/pdf-interpreter.git

2. Install the required dependencies:

pip install PyPDF2 pandas

3. Run the program:

python main.py

Usage

1. Place your PDF files in the pdfs directory.
2. Run the application using the installation instructions above.
3. The application will extract text from the PDFs, analyze the text for LOD and sensitivity values, LOD units, and DOIs, and generate both raw data CSV files (raw_lod_table.csv) (raw_sensitivity_table.csv) and cleaned/normalized CSV files (cleaned_lod_table.csv) (cleaned_sensitivity_table.csv).

Sample Output (LOD)

DOI,Value,Units,Count
10.1016/j.snb.2018.11.055,0.04,μm,2
10.1016/j.snb.2018.11.055,0.08,μm,2
10.1016/j.bios.2014.09.042,22.2,mg/dl,3
10.1039/d1an00283j,0.01,mm,2
10.1021/acs.analchem.5b00012,1.07,μm,1

Sample Output (Sensitivity)

DOI,Value,Count
10.1016/j.snb.2018.11.055,0.0,1
10.1016/j.bios.2014.09.042,0.0033,1
10.1021/acs.analchem.5b00012,6.1,1

Contributing

Contributions are welcome! If you have ideas for improvements or new features, please open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.