Form Information Extractor

Overview

Form Information Extractor is a Python-based backend script designed to run on Google Colab. This script extracts specific information from employee forms and saves the extracted data into an Excel file. The information extracted includes:

• Name
• Birthdate
• Email
• Phone Number
• School
• College
• Year of Graduation

Features

• Extracts and processes form data efficiently.
• Saves the extracted data into a structured Excel file for further use.
• Filters specific fields such as name, email, phone number, etc.

Getting Started

Prerequisites

To use this project, you need:

• A Google account for accessing Google Colab.
• Basic knowledge of Python.
• Required Python libraries installed (detailed below).

Installation

1. Clone this repository:

   git clone https://github.com/umr-se/form-information-extractor
   cd form-information-extractor

2. Open the script in Google Colab:

   • Upload the form_extractor.ipynb file to Google Colab.

3. Install the necessary Python libraries:

   !pip install pandas openpyxl

Running the Script

1. Upload the form files (e.g., scanned forms, images, or text files) to the Colab environment.
2. Run the notebook cells step-by-step.
3. The script will:
   • Extract the filtered information from the forms.
   • Save the extracted data to an Excel file named extracted_data.xlsx.
4. Download the extracted_data.xlsx file from the Colab environment to your local system.

Example Usage

# Import required libraries
import pandas as pd

# Example extracted data
data = {
    "Name": ["John Doe"],
    "Birthdate": ["1995-06-15"],
    "Email": ["john.doe@example.com"],
    "Phone Number": ["+123456789"],
    "School": ["ABC High School"],
    "College": ["XYZ University"],
    "Year of Graduation": ["2018"]
}

# Save data to Excel
df = pd.DataFrame(data)
df.to_excel("extracted_data.xlsx", index=False)

Folder Structure

form-information-extractor/
├── form_extractor.ipynb  # Google Colab notebook containing the script
├── sample_forms/         # Folder to upload your form files (optional)
├── extracted_data.xlsx   # Output Excel file (generated after running the script)

Libraries Used

• pandas: For data manipulation and saving to Excel.
• openpyxl: For working with Excel files.

Contributing

Feel free to fork this repository, create a new branch, and submit a pull request with improvements or additional features.

Author

• Muhammad Umer Saleem
  Software Engineer specializing in Python backend development.

For any questions or suggestions, feel free to reach out!