Data Preprocessing and Visualization App
Develop a specialized app that simplifies data loading, cleaning, and visualization. With a user-friendly interface, users can effortlessly load data, apply predefined cleaning rules, and generate insightful visualizations. The app empowers users to leverage data analysis and visualization for informed decision-making and deeper understanding of their datasets.
The goal of this project is to develop a specialized app that facilitates the loading, cleaning, and visualization of data. The app offers a user-friendly interface where users can easily load their data, apply data cleaning operations based on predefined rules, and generate visualizations of selected columns.
The app begins by providing an option for users to load their data. The data must adhere to a specific schema defined by the app, ensuring compatibility and seamless processing. Once the data is loaded, the app presents a window that allows users to clean the data using a predefined set of rules. The cleaning process is handled in the app's backend, automatically applying the necessary transformations and adjustments to ensure data quality and consistency.
After the data is cleaned, the app offers a visualization feature that allows users to visualise the columns in the dataset.This visual representation enables users to gain insights, identify trends, and effectively communicate the information contained in the dataset.
By providing a focused and user-friendly interface, this app streamlines the data loading, cleaning, and visualization process. It ensures data adherence to a specific schema, automates the cleaning operations, and enables users to generate meaningful visualizations effortlessly. The app is designed to empower users with limited technical expertise to leverage the power of data analysis and visualization for informed decision-making and deeper understanding of their datasets.
Programming Language: Python
Libraries used: tkinter, scikit-learn, matplotlib