Enhancing Data Collection and Display with PyShinyDataTable
Authors: Abdulrahaman A Musa(Data Scientist/ML engineer/ Monitoring and Evaluation Officer at Nigerian Red Cross)
Full Description:
This project, the PyShinyDataTable app, revolutionises data collection and display in healthcare settings like hospitals or clinics. This Shiny-Express app empowers users to collect patient data in Excel files efficiently, store it in an SQLite database, and effortlessly display the records in a dynamic Data Table using the iTables JavaScript python library.
Data Upload: The app allows users to upload Excel files to the SQLite database. Users can choose the file, specify headers, and load the data with a single click. The uploaded data is instantly displayed in an interactive Data Table for easy access.
Duplicate Record Handling: To maintain data integrity, the app includes logic to prevent duplication of records. The app filters out duplicate entries by checking for existing hospital numbers in the database, ensuring a clean and accurate data repository.
Interactive Data Table: The Data Table powered by the iTables package offers advanced functionalities such as conditional formatting, data filtering, and export options. Users can seamlessly filter data based on conditions, copy data to CSV or Excel formats, and even print the data directly from the table interface.
Table Type: interactive-Shiny
Submission Type: Single Table Example
Table: A-musa Data-solution - Enhancing Data Collection and Display with PyShinyDataTable
Code: GitHub - AbdulrahamanMusa/PyshinyDataTable: Enhancing Data Collection and Display with PyShinyDataTable
Language:
Industries: This Shiny-Express app empowers users to collect patient data in Excel files efficiently, store it in an SQLite database, and effortlessly display the records in a dynamic Data Table .
Packages: shiny, shiny.express, shinyswatch, itables, sqlite3, pandas
