---
date: 2025-07-01
title: Pivot Tables in Custom Dashboards
description: Analyze multi-dimensional data with the new pivot table widget in Langfuse custom dashboards.
author: Steffen
ogImage: /images/changelog/2025-07-01-pivot-tables.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 Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated.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 **pivot tables** to Langfuse custom dashboards!
This new widget type enables multi-dimensional analysis of your LLM application data, making it easier to uncover patterns and insights across different segments and metrics.

## What are Pivot Tables?

Pivot tables provide a flexible way to summarize and analyze data by organizing it into rows, columns, and values.
They excel at revealing relationships between multiple dimensions simultaneously, helping you answer complex analytical questions like:

- **Cross-Model Performance**: How do latency and cost metrics compare across different models and user segments?
- **Feature Analysis**: Which features drive the highest quality scores across different time periods?
- **User Behavior Patterns**: How do usage patterns vary by user type, geography, and application features?
- **Quality vs. Cost Trade-offs**: What's the relationship between model costs and quality scores across different use cases?

## Getting Started

Creating a pivot table is straightforward:

1. Navigate to **Dashboards** → **Widgets** → **New Widget**
2. Select your data source (traces, observations, or scores)
3. Choose **Pivot Table** as your chart type
4. Configure your pivot table:
   - **Metrics**: Select which metrics you want to plot, e.g. different latency percentiles
   - **Dimensions**: Select up to two dimensions that you want to group by
5. Apply filters to narrow down your analysis
6. Save and add to your dashboard

## Get started

- [Custom Dashboards Documentation](/docs/metrics/features/custom-dashboards)

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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/2025-07-01-pivot-tables-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>.