powerbi-python-visualslisted

# Python Visuals in Power BI (PBIR) > **Report modification requires tooling.** Two paths exist: > 1. **`pbir` CLI (preferred)** -- use the `pbir` command and the `pbir-cli` skill. Install with `uv tool install pbir-cli` or `pip install pbir-cli`. Check availability with `pbir --version`. > 2. **Direct JSON modification** -- if `pbir` is not available, use the `pbir-format` skill (pbip plugin) for PBIR JSON structure and patterns. Validate every change with `jq empty <file.json>`. > > If neither the `pbir-cli` skill nor the `pbir-format` skill is loaded, ask the user to install the appropriate plugin before proceeding with report modifications. Python visuals execute matplotlib/seaborn scripts to render static PNG images on the Power BI canvas. **Prefer seaborn** over raw matplotlib for cleaner syntax and better defaults -- it handles most chart types with less code. ## Visual Identity - **visualType:** `pythonVisual` - **Data role:** `Values` (columns and measures, multiple allowed) - **Data variable:** `dataset` (pandas DataFrame, auto-injected) - **Row limit:** 150,000 rows - **Output:** Static PNG at 72 DPI -- no interactivity ## Workflow: Creating a Python Visual ### Step 1: Add the Visual Create the visual.json file manually (see `pbir-format` skill in the pbip plugin for JSON structure) with `visualType: pythonVisual`, field bindings for the columns and measures you need (use `Values:Table.Column` or `Values:Table.Measure` format), and position/size as required.