> ## Documentation Index > Fetch the complete documentation index at: https://docs.trainy.ai/llms.txt > Use this file to discover all available pages before exploring further. # Bar Charts > Roll up sibling scalars into categorical {bars} distributions. Categorical **`{bars}`** rollups let you compare many related scalars — per-class accuracy, per-shard throughput, per-expert load — as a single distribution instead of dozens of overlapping line charts. ## Producing bar charts Log **three or more sibling scalars under a common prefix** and Pluto automatically offers that prefix as a `{bars}` rollup — no special SDK call needed: ```python theme={null} # Per-class accuracy under the "eval/per_class" prefix pluto.log({ "eval/per_class/cat": 0.91, "eval/per_class/dog": 0.88, "eval/per_class/bird": 0.79, }, step=epoch) ``` Pluto detects the `eval/per_class` prefix and surfaces it as `eval/per_class/{bars}`. If you control the SDK and want true binned distributions, [`pluto.Histogram`](/pluto/visualizations/histograms) is the richer option. ## Viewing Bar charts live in the **Distributions** widget alongside numeric [histograms](/pluto/visualizations/histograms). To add one, open **Add Widget**, choose the **Distributions** tab, and search for your `/{bars}` group. Adding a Distributions widget from the Add Widget modal ### View modes Each widget renders in one of three modes. **Step** — a bar chart at the scrubbed step, bars sorted by global max value. Use the step slider below the widget to scrub through training. Bar chart in Step mode — one bar per category at a single step **Ridgeline** — TensorBoard-style joyplots, one ridge per step, so you can watch each category's value evolve over training. Bar chart in Ridgeline mode — one ridge per step **Heatmap** — a density grid: value as color, category on the X axis and step on the Y axis. Bar chart in Heatmap mode — value as color A **`Y: step` / `Y: run`** toggle switches whether ridges and heatmap rows are stacked by step or by run. ### Steps on X In Ridgeline and Heatmap modes, the **Steps on X** toggle transposes the chart so training steps run along the X axis and categories stack down the Y axis. A `{bars}` heatmap aligns its X range with the line chart above it, so a metric and its distribution read as one coordinated view across time. Bar-chart ridgeline with Steps on X — steps run along the X axis The same transpose applies in Heatmap mode: Bar-chart heatmap with Steps on X ### Settings The settings popover has an **Ignore outliers** toggle (on by default) that clamps the shared frequency scale so one extreme step doesn't flatten the rest into a baseline. It's inert in **Step** mode, where the axis auto-scales to the current snapshot.