https://github.com/jpcurada/neusoftmnl-attendance-system

Built with Streamlit, this system expedites the processing of Neusoft employee attendance data. It converts DingTalk's raw output into easy-to-understand, downloadable formats.
https://github.com/jpcurada/neusoftmnl-attendance-system

Last synced: 2 months ago
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Built with Streamlit, this system expedites the processing of Neusoft employee attendance data. It converts DingTalk's raw output into easy-to-understand, downloadable formats.

• Host: GitHub
• URL: https://github.com/jpcurada/neusoftmnl-attendance-system
• Owner: JpCurada
• Created: 2024-02-21T06:09:10.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-25T11:32:45.000Z (6 months ago)
• Last Synced: 2025-02-10T03:17:26.921Z (4 months ago)
• Language: Python
• Homepage: https://neusoft-mnl-attendance.streamlit.app/
• Size: 533 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

# Neusoft MNL Attendance Management System

The Neusoft MNL Attendance Management System is a comprehensive Streamlit web application designed to automate the management and organization of attendance data for Neusoft employees. Utilizing data produced by DingTalk, this application transforms raw attendance data into a clear, understandable, and downloadable format. The system simplifies the attendance data management process, making it more efficient and less prone to human error.

![image](https://github.com/user-attachments/assets/bb06533a-5e7f-4151-8c34-774f98943060)

## Features

- Data Transformation: Converts raw attendance data into an easily understandable and manageable format.

- Master List Integration: Merges attendance data with the master employee list for comprehensive management.

- Schedule Processing: Incorporates employee schedules to accurately apply attendance codes.

- Custom Filters: Offers customizable filters for employee name, LOB, shift, site, leader, and employer for targeted data analysis.

- Data Visualization: Visualizes multiple logs and missed punches with progress columns for easy understanding.

- Downloadable Reports: Allows for the downloading of processed attendance data in Excel format, complete with styled cells for better readability.

## User Guide

- Upload Files: Upload the required Excel files for attendance raw data, master list, and schedule through the provided file uploaders.

- Data Processing: Once all files are uploaded, the application processes the data, merging the attendance with the master list and applying the necessary codes based on the employee schedule.

- Customization: Use the sidebar to filter the displayed data according to specific criteria such as employee name, LOB, shift, among others.

- Visualization: Analyze the processed data through the visualization of multiple logs and missed punches. The application uses progress columns for a clear representation of the data.

- Download: Finally, download the processed and styled attendance data in Excel format for offline analysis or record-keeping.

## Feedback

If you have any feedback, please reach out to John Paul Curada.

[![linkedin](https://img.shields.io/badge/linkedin-0A66C2?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/jpcurada/)