Viewfinder is a data exploration and visualization tool, designed to make the traversal of datasets both intuitive and simple. Built using Streamlit, Seaborn, Pandas, and Numpy, it offers a range of functionalities from basic statistical summaries to more complex visualizations.
- Data Loading and Processing: Easy upload of CSV files and preprocessing capabilities to ensure data quality.
- Exploratory Data Analysis: Provides various tools for initial data exploration including summary statistics and correlation matrices.
- Customizable Visualizations: Generate a variety of plots like histograms, scatter plots, and heatmaps with customizable options.
- Regression Analysis: Perform linear and logistic regression analysis with interactive visual feedback.
- Data Quality Report: Generate comprehensive reports outlinging missing values, outliers, and unique values in your dataset.
To set up Viewfinder for yourself:
- Clone this repository.
- Install required libraries:
pip install -r requirements.txt
- Run the app:
streamlit run viewfinder.py
- Local
- Start the Application: Launch Viewfinder using the Streamlit command.
- Upload Data: Use the sidebar to upload a CSV file.
- Explore Data: Navigate through different tabs to analyze and visualize your data.
- Live
If you do not have your own data to test on Viewfinder locate the 'Datasets' folder in the project directory, several datasets for testing are provided there.
- Download a CSV
- Run the tool
- Upload the CSV
- Special thank you to Proffessor Salu for a great semester in full stack.
- Huge thanks to Dylan for approaching me about the intial problem and continued support
- Everyone else!
This is just a start! Features and implementations are not final.