This repository contains an interactive dashboard for analyzing Total Sheets data using Python, Pandas, and Panel with Plotly visualizations. The dashboard allows users to filter data dynamically, view key performance indicators (KPIs), and explore data through various charts.
- Interactive Filters: Filter data by registration numbers, years, and total sheets.
- Dynamic Visualizations: Includes scatter plots, bar charts, line charts, histograms, box plots, heatmaps, and cumulative charts.
- Theme Toggle: Switch between light and dark mode for enhanced viewing experience.
- Reset Filters: Quickly reset all filters to start fresh.
- Real-Time KPIs: Displays metrics like total registrations, total sheets, average sheets per registration, and more.
- Clone the repository:
git clone https://github.com/sabdulrazzaque/Project_Tuna_Fisheries_Digitization.git cd Project_Tuna_Fisheries_Digitization
Install the required Python packages:
bash Copy code pip install -r requirements.txt Ensure the data file is accessible at the specified path or adjust the file_path in the code:
python Copy code file_path = r'D:\Project_Tuna_Fisheries_Data_Entry\Data\Python\TFDF File Main database_09-12-2024.xlsx' Run the dashboard:
bash Copy code panel serve Dashboard_v2.ipynb
Dependencies Python: 3.8 or later Panel: For interactive UI components Plotly: For dynamic visualizations Pandas: For data manipulation OpenPyXL: For working with Excel files Install all dependencies using the command:
bash Copy code pip install panel plotly pandas openpyxl
How to Use Launch the dashboard using panel serve. Use the provided filters to narrow down the dataset. Explore KPIs and visualizations in real time. Toggle between light and dark themes for your preference. Reset filters if needed to start fresh.
Dashboard Overview
Filters: Select specific registration numbers, years, or total sheets to filter data. KPIs: Displays: Total Registrations Total Sheets Average Sheets per Registration Median Sheets per Registration Maximum Sheets by a Registration Standard Deviation of Sheets
Charts:
Scatter Plot Histogram Bar Chart Line Chart Box Plot Heatmap Cumulative Chart
Data Requirements
The data file should be an Excel sheet with at least the following columns:
Reg No.: Unique registration number. Year: Year of data entry. Total sheets: Number of total sheets. If any required columns are missing, the program will raise an error.
Error Handling If the specified file is not found or is invalid, a sample dataset is used for demonstration purposes. Missing or invalid columns in the dataset will raise an appropriate error. An empty dataset after filtering prompts the user to reset filters or adjust their selections.
Acknowledgments This project leverages the power of Python's data manipulation and visualization libraries to create an interactive and insightful dashboard for data analysis.
Screenshots
