Execute custom Python code using plotly express and pandas to generate complex Plotly charts from a data file, saving with a specified filename keyword.
Publish a chart to Autario by providing a Plotly spec with column references; Autario pulls real data from datasets to ensure integrity, making the chart permanent, shareable, and editable.
A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.
Generate an interactive FFT spectrum report with peak detection and harmonic labeling from a stored vibration signal, saving a timestamped HTML file for machinery fault analysis.
Generate Plotly figures from data and natural-language descriptions. Handles open-ended chart requests by writing and running Python code, returning the figure as JSON.
Ask a natural-language question about official statistics and receive a computed result with chart, code, and citations. Join series across agencies like BLS, Statistics Canada, and ONS.
Create a ready-to-run Jupyter notebook that bulk downloads ZTF alert photometry from Fritz, exports to CSV, and generates interactive light curve plots.
Generate ISO 20816-3 vibration reports as HTML with A-D zones and RMS marker. Assess severity with machine group and support type; include RPM. Requires loaded signal with sampling rate and unit.
Analyze transient light curves to measure rise time, fade time, and duration across photometric bands, including incomplete curves, and generate an interactive notebook with plots.
Add shaded vertical zones to Plotly charts to highlight time periods like crises or policy changes. Enhances figure with colored bands and optional labels.
Visualize relationships between numeric features with an interactive correlation heatmap. Supports Pearson and Spearman methods, with optional column filtering.