eugenegujing opened a new pull request, #4406:
URL: https://github.com/apache/texera/pull/4406
PR Description
## Purpose
Adds a new **Empirical Cumulative Distribution Function (ECDF)** plot
operator to the Statistical Visualization group, letting users visualize the
cumulative distribution of a numeric column and easily compare distributions
across groups.
## Summary
- New operator `ECDFPlotOpDesc` under `operator/visualization/ecdfPlot/`,
rendered via `plotly.express.ecdf`.
- Configurable fields:
- **Value Column** (required, numeric): column to compute ECDF on
- **Color Column** (optional): group and color lines by category
- **SeparateBy Column** (optional): split plot into facets
- **Y Axis Mode**: `probability` / `count` / `sum`
- **CDF Mode**: `standard` / `reversed` / `complementary`
- **Orientation**: `vertical` / `horizontal`
- **Show Markers / Show Lines** toggles
- **Marginal Plot**: `""` / `histogram` / `rug`
- Registered in `LogicalOp.scala` as the `ECDFPlot` operator type.
- Added operator icon `frontend/src/assets/operator_images/ECDFPlot.png`.
- User-provided enum fields (`cdfMode`, `orientation`, `marginal`) use
`EncodableString` so generated Python safely passes
`PythonCodeRawInvalidTextSpec`.
- Unit tests in `ECDFPlotOpDescSpec` covering the empty-value assertion and
the generated figure with all optional parameters.
## Test
- [x] `sbt scalafmtCheckAll` passes
- [x] `sbt "scalafixAll --check"` passes
- [x] `sbt "WorkflowOperator/testOnly
org.apache.texera.amber.operator.visualization.ecdfPlot.ECDFPlotOpDescSpec
org.apache.texera.amber.util.PythonCodeRawInvalidTextSpec"`
— all tests pass (4/4), 110/110 raw-invalid OK, 110/110 py_compile OK
- [x] Manually tested end-to-end in the UI with CSV source → ECDF Plot
operator; verified the rendered plot in the result panel for all combinations
of color/facet/CDF mode/orientation/marginal options.
## Screenshots
<img width="3529" height="1962" alt="image"
src="https://github.com/user-attachments/assets/44392eaa-e6bb-48ee-80dc-a4c128425255";
/>
[ecdf_demo.csv](https://github.com/user-attachments/files/26813799/ecdf_demo.csv)
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