Tutorials
Learn MathJet by working through hands-on examples. Each tutorial produces a working analysis or visualization you can point at when you’re done.
Where to start
Section titled “Where to start”If you’re new to MathJet, start with Tutorial 1: Your first analysis in MathJet, then Tutorial 2: Mixing languages in formula bar and scripts. Together they take about 30 minutes and cover the core ideas behind MathJet’s design.
Choose your path
Section titled “Choose your path”After the first two tutorials, choose based on your background:
- Coming from MATLAB? → Tutorial 3
- Coming from Python or Jupyter? → Tutorial 4
- Coming from R or RStudio? → Tutorial 5
- Want to generate your own test data from statistical distributions? → Fill Function tutorial
- Ready for the patented interactive visualization features? → Interactive plots tutorial
- Want analytics inside the chart — characteristics tables, curve fits, derived graphs? → Graph analytics tutorial
- Pulling data from a SQL database — SQLite, PostgreSQL, MySQL, SQL Server, or Oracle? → Databases tutorial
The capability deep-dives cover specific features — work through them in any order.
Building toward a complete workflow
Section titled “Building toward a complete workflow”Building a reproducible analysis end-to-end is the capstone. After completing the earlier tutorials, work through it to see how MathJet’s pieces combine in a complete real-world analysis.
Quick glossary
Section titled “Quick glossary”A handful of terms recur across the tutorials. This table pins them down so they don’t blur together:
| Term | Meaning | Where introduced |
|---|---|---|
| Live linking | The bidirectional connection between cells and charts — edit a cell and the chart redraws; drag a chart point and the cell updates. Also applies to variable↔cell connections created via Create Variable from Cells. | Tutorial 1, Steps 9–10 |
| Dynamic links | Per-component links between a chart and its source variables, managed via Plot → Links to Data Sources. Each component (X coord, Y coord, …) can be toggled independently. | Tutorial 3, Step 5 |
| Dynamic variables | Variables defined with the => operator instead of =. A dynamic variable recomputes whenever its source variables change — a standing rule, not a one-time snapshot. | Tutorial 3, Step 5 |
| Shared data frame | MathJet’s internal store that holds user-defined variables and automatically transfers them between embedded interpreters (Jet, Python, R) when you switch languages. | Tutorial 2, Step 2 |
| Variable cell block | The inline worksheet (or notebook-output) rendering of a variable — a floating, collapsible, editable block that displays a variable’s contents without writing to actual spreadsheet cells. | Tutorial 2, Step 4 |
| Variable Editor | A specialized full-tab editor for a single variable, with configurable header rows (value filter, min, max, sparklines, …) and per-column dropdown filters. Distinct from a variable cell block: the Variable Editor is its own tab; a variable cell block is embedded in a worksheet or notebook output. | Tutorial 3, Step 4b |
| Workspace Manager | A side panel that exposes the full workspace structure — open worksheets, charts, variables, scripts — with multi-pane navigation. | Tutorial 1, Step 12 |
| Environment Pane / Overview Pane | Two coordinated panels on the right of the workspace. The Environment Pane lists every variable in the active interpreter; the Overview Pane shows a shape-appropriate visualization of whatever variable (or sub-component) is currently selected. | Tutorial 1, Step 4 |