PyDash Analytics Dashboard
PyDash Analytics Dashboard: Visualize revenue, customers, and products sold with area and circular bar charts. Includes a customizable table for detailed data analysis.
Description:
PyDash Analytics Dashboard is a data visualization tool built using Python that provides insights into revenue, customer metrics, and product sales. The dashboard utilizes various libraries such as Tkinter, Matplotlib, and Pandas for efficient data handling, visualization, and user interface development.
Import Libraries:
Tkinter: For creating the graphical user interface (GUI).
Matplotlib: Used to generate area charts and circular bar charts for data visualization.
Pandas: Facilitates data manipulation and analysis.
Pathlib: Helps in handling file paths.
Data: Custom module containing sample data.
Virtualenv:
A virtual environment (virtualenv) is utilized to isolate the project's dependencies from the system-wide Python installation. This ensures that the project's dependencies are managed separately, preventing conflicts with other projects or system packages.
Figma for Design:
The user interface design for the PyDash Analytics Dashboard was prototyped using Figma. Figma allows for collaborative design and prototyping of user interfaces, enabling efficient communication between designers and developers. The design was then implemented using Tkinter to create an intuitive and visually appealing dashboard interface.
Code:
The provided code initializes the PyDash Analytics Dashboard interface using Tkinter. It incorporates various GUI elements such as text, images, and charts to display key metrics related to revenue, customers, and products sold. Matplotlib is used to create area and circular bar charts based on sample data provided in the 'data' module.
Output:
The output of the PyDash Analytics Dashboard includes:
Visualization of revenue, customers, and products sold through area and circular bar charts.
Display of key metrics such as revenue amount, customer count, and product sales.
Customizable table showcasing detailed data analysis.
Intuitive user interface designed for ease of navigation and interaction.
