csv-data-visualizer

CSV data visualization generates interactive charts using Plotly, including histograms, scatter plots, box plots, heatmaps, and bar charts. Load your CSV file and the Skill creates Plotly-based visualizations exported as HTML or static images for exploration and reporting.

Yes, multi-plot dashboards combine histograms, scatter plots, correlations, and statistical summaries into a single view. The create_dashboard.py script assembles multiple visualizations from your CSV into one HTML dashboard for presentations and exploratory analysis.

Data profiling automatically generates summary statistics, distributions, and correlation analysis on your CSV columns. The data_profile.py script outputs statistical summaries and insights alongside visualizations to support exploratory data analysis workflows.

The Skill uses pandas for data handling and Plotly for rendering. Performance depends on row count and chart complexity; Plotly renders interactively in browsers, though very large datasets may require filtering or aggregation before visualization.

Yes, visualizations can be exported to both HTML and static image formats like PNG. The visualize_csv.py script supports multiple export options for embedding charts in reports, presentations, or documentation.

Individual visualizations (histogram, scatter, box plot) focus on single variables or relationships, while dashboards combine multiple plot types into one view. Use individual charts for targeted analysis and dashboards for comprehensive data summaries and presentations.