Dataset: Issues & Pull Requests
Entity: Pull Requests, Issues
Field ID: type
Type: Select list
Description: The type of the item. Possible values are:
issuethe item is an issuepull_requestthe item is a pull request
Source: Calculated
Transformation logic: Based on the source type of the record.
From: |
|
Github (PRs, Issues) | Calculated |
Gitlab (PRs, Issues) | Calculated |
Bitbucket (PRs) | Calculated |
Azure DevOps (PRs, Issues) | Calculated |
JIRA (Issues) | Calculated |
ClickUp (Issues) | Calculated |
Trello (Issues) | Calculated |
Reporting Use Cases
The Type field is the most fundamental classifier in the dataset, allowing you to distinguish between planning items (issue) and implementation items (pull_request). Its primary use is for filtering, which is the essential first step for creating almost any meaningful report.
Filtering for Scoped Reports: This is the most critical function of the type field. It allows you to create widgets that focus on a specific part of your workflow.
PR-Specific Metrics: All pull request metrics, such as cycle time, merge time, or lines of code, require a filter where
Type = "pull_request"to ensure you are only measuring development work.Issue-Specific Metrics: All issue-based metrics, such as story point velocity or issue triage time, require a filter where
Type = "issue"to focus on your planning and project management data.
Reporting on Work Distribution: When used as a dimension, this field provides a high-level overview of the composition of your work.
A pie chart with
Typeas the dimension andCOUNT()as the metric can quickly show the ratio of open issues to open pull requests in your backlog.A stacked column chart with a time-based dimension and type as the second dimension can visualize the volume of new issues being created versus new pull requests being opened over time.
Custom Formulas for Comparative Metrics: You can use this field within a single report to compare metrics across both types.
For example, in a list widget with project_name as the dimension, you could create two separate metrics to see the volume of each work type side-by-side:
COUNT_IF(type == "issue")andCOUNT_IF(type == "pull_request").