ows-master/examengegevens template generator/readme.md

Project Name: Examination Data Processing

Overview

This project is designed to process examination data from an Excel file and generate filtered output and communication messages for teaching staff. It's developed using Python and pandas, and it provides functionalities such as filtering records, converting time formats, and generating message columns.

Features

• Read Excel File: Reads examination data from an Excel file into a Pandas DataFrame.
• Filter Data: Filters records based on specific criteria in 'Studiegidsnummer' and 'Opmerkingen' columns.
• Convert Time Format: Converts time columns to 'HH:MM' format.
• Generate Messages: Creates message and subject columns for email communication.
• Save to Excel: Saves the processed data to a new Excel file.

Prerequisites

• Python 3.12.5
• Pandas
• openpyxl

Installation

1. Clone the repository:

   git clone https://github.com/username/examination-data-processing.git
   cd examination-data-processing
   

2. Install the required Python packages:

   pip install -r requirements.txt
   

   Ensure the requirements.txt file should contain:

   pandas
   openpyxl
   

Usage

1. Place the input Excel file: Ensure that the Excel file (examengegevens2425.xlsx) is placed in the root directory of the project.

2. Run the script:

   python script.py
   

3. Output: The filtered and processed data will be saved in an output Excel file (filtered_examengegevens2425.xlsx).

Functions

read_excel_file(file_path)

• Parameters: file_path (str) - Path to the Excel file.
• Returns: DataFrame or None

filter_studiegidsnummer(df)

• Parameters: df (DataFrame) - Input DataFrame.
• Returns: Filtered DataFrame or empty DataFrame

filter_opmerkingen(df)

• Parameters: df (DataFrame) - Input DataFrame.
• Returns: Filtered DataFrame or empty DataFrame

create_message_column(df)

• Parameters: df (DataFrame) - Input DataFrame.
• Returns: DataFrame with 'Message' and 'subject' columns

save_to_excel(df, output_file_path)

• Parameters:
  • df (DataFrame) - DataFrame to save.
  • output_file_path (str) - Path to save the Excel file.
• Returns: None

convert_time_format(time_str)

• Parameters: time_str (str) - Time string to convert.
• Returns: Formatted time string

apply_time_format_conversion(df, columns)

• Parameters:
  • df (DataFrame) - DataFrame with time columns.
  • columns (list of str) - List of column names to format.
• Returns: DataFrame with formatted time columns

main()

• Main function to execute the entire process: reading the Excel file, filtering data, converting time formats, creating message columns, and saving to Excel.

Example

if __name__ == "__main__":
    main()

Contributing

1. Fork the repository.
2. Create a new branch: git checkout -b feature-branch.
3. Make your changes and commit: git commit -m 'Add new feature'.
4. Push to the branch: git push origin feature-branch.
5. Submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

Acknowledgements

• Pandas Documentation
• Openpyxl Documentation

Author

• AI Assistant (Your Name or Contributors)

For additional information or support, please contact your-email@example.com.