DataValet Application
A modern web application designed for data professionals that helps them stay organized and save time by performing basic data operations in a clean and efficient manner. It provides a user-friendly interface for data analysis, visualization, and exploration without requiring extensive coding knowledge.
Python
Flask
HTML
CSS
JavaScript
Plotly
Pandas
Features
Data Upload
Upload CSV and Excel files for analysis with a simple drag-and-drop interface.
Data Summary
Get comprehensive statistical summaries of your data including distributions, correlations, and missing values.
Data Visualization
Create interactive charts and graphs with Plotly, including bar charts, line charts, scatter plots, and more.
Interactive Notebook
Run Python code directly in your browser with an interactive notebook interface.
Responsive Design
Fully responsive web interface that works on desktop, tablet, and mobile devices.
How It Works
Upload Page
- Click the "Upload Data" button on the home page
- Select a CSV or Excel file from your computer
- Click the "Upload" button to process the data
- Once uploaded, you'll be redirected to the Summary page
Summary Page
View comprehensive statistics about your dataset including:
- Dataset dimensions
- Column data types
- Missing values
- Numerical column statistics (mean, median, etc.)
- Categorical column distributions
- Correlation matrix (interactive heatmap)
Visualization Page
- Click "Add Graph" to create a new visualization
- Select the plot type (Bar Chart, Line Chart, Scatter Plot, etc.)
- Select X and Y columns (as applicable for the plot type)
- Click "Update Graph" to generate the visualization
- Add as many graphs as needed
Notebook Page
- Write and execute Python code in cells
- Access the dataset via the global variable `df`
- Use standard data science libraries (pandas, numpy, matplotlib, seaborn)
- Run individual cells or run all cells in sequence
- Insert example code snippets from the "Examples" dropdown