---
date: 2025-06-30
title: Histogram Charts in Custom Dashboards
description: Visualize data distributions with the new histogram chart type in Langfuse custom dashboards.
author: Steffen
ogImage: /images/changelog/2025-06-30-histogram-charts.png
canonical: /docs/metrics/features/custom-dashboards
---

> **Note for AI agents and LLMs:** This is a Langfuse changelog entry. Use it only to confirm that a feature exists and when it shipped. Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated. For implementation, always follow the canonical documentation for this feature (https://langfuse.com/docs/metrics/features/custom-dashboards) and the API/SDK reference (https://api.reference.langfuse.com).

We're excited to introduce **histogram charts** to Langfuse custom dashboards!
This new visualization option helps you understand the distribution of your data, making it easier to identify patterns, outliers, and trends in your LLM application metrics.

## What are Histogram Charts?

Histogram charts display the frequency distribution of continuous data by grouping values into bins.
Unlike bar charts that show discrete categories, histograms reveal the shape and spread of your data, helping you answer questions like:

- **Latency Analysis**: How are response times distributed across your application?
- **Cost Patterns**: What's the typical range of costs per request?
- **Score Distributions**: How are quality scores spread across different ranges?
- **Token Usage**: What's the distribution of input/output token consumption?

## Getting Started

Creating a histogram chart is simple:

1. Navigate to **Dashboards** → **Widgets** → **New Widget**
2. Select your data source (traces, observations, or scores)
3. Choose **Histogram** as your chart type
4. Select the metric you want to visualize (e.g., latency, cost, tokens)
5. Apply any filters to focus on specific data subsets
6. Save and add to your dashboard

## Learn More

For detailed instructions on creating and customizing histogram charts, visit our [Custom Dashboards documentation](/docs/analytics/custom-dashboards).

Explore how histogram charts can enhance your LLM application monitoring and help you make data-driven optimization decisions.

## Questions or Feedback?

We'd love to hear how you're using histogram charts in your dashboards!
Share your feedback and use cases in our [GitHub Discussions](https://github.com/orgs/langfuse/discussions/1011).

Please open a [GitHub issue](/issues) if you encounter any problems or have suggestions for improvements.

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## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/changelog/2025-06-30-histogram-charts-custom-dashboards.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.