Dataset: Issues & Pull Requests
Entity: Pull Requests, Issues
Field ID: body
Type: Text
Description: The body of the pull request or issue in source format.
Source: App
Transformation logic: N/A
From: |
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Github (PRs, Issues) |
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Gitlab (PRs, Issues) |
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Bitbucket (PRs) |
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Azure DevOps (PRs, Issues) |
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JIRA (Issues) |
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ClickUp (Issues) |
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Trello (Issues) |
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Reporting Use Cases
The Body field, which contains the full description of an issue or pull request, is a rich source of qualitative data. While not typically used for direct grouping in reports, it is invaluable for keyword-based filtering and for extracting specific information using custom formulas.
Filtering and Scoping: You can find specific items by searching for keywords within their description, which is especially useful for topics not covered by labels.
Keyword Search: Create a report of all items related to a specific feature by filtering where
Body ~ "new-signup-flow".Compliance Checks: You can identify items that are missing a proper description by creating a filter where body is empty. This is the basis for the "Scoped Issues Ratio" insight, which helps enforce documentation standards.
Custom Formulas for Data Extraction and Categorization: The body field is powerful when used inside custom formulas to extract and structure information.
Extracting Information: Use regex functions to pull specific data out of the text. For example, if your issues reference external ticket numbers, a dimension with the formula
REGEX_EXTRACT(body, 'TICKET-\d+')would allow you to group items by their associated ticket.Categorizing by Content: You can automatically categorize work based on its description. A custom formula such as
IF(body ~ 'security vulnerability', 'Security Concern', 'Other')can be used as a dimension to group all items that mention security, even if they aren't labeled as such.Creating Advanced Metrics: You can build targeted KPIs, such as counting the number of pull requests that mention a deprecated function:
COUNT_IF(body ~ 'useDeprecatedFunction').