Cross Filtering Across Tabs in Dashboards
- Dominant language
- Python
- Stars
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- Forks
- 18.3k
- Avg merge
- 2d 5h
- Merged PRs (30d)
- 685
Description
### Bug description
Currently, dashboard visuals support cross-filtering only within the same tab and not across tabs. Users cannot select a chart data point or metric and have the corresponding detail tab update automatically, requiring manual navigation and reapplying filters.
###
**Expected Behavior**
Enable Cross-filtering functionality from any visual to its respective detail tab.
Maintain context and filters when navigating between tabs.
**TAB 1**
**TAB 2**
**When a user selects Genre = Sports on a chart in one tab, all rows related to Sports should automatically be filtered and displayed in the detailed report on the other tab.**
### **Actual Behavior**
Cross-filtering works only within the same tab. Detailed reports in other tabs do not update based on the selected chart data point in the current tab.
### **Impact**
Users must manually add filters in other tabs for the same chart data points.
For charts with multiple categories, this can require adding numerous filters, increasing effort and time.
### Screenshots/recordings
_No response_
### Superset version
6.0.0
### Python version
3.9
### Node version
16
### Browser
Chrome
### Additional context
_No response_
### Checklist
- [x] I have searched Superset docs and Slack and didn't find a solution to my problem.
- [x] I have searched the GitHub issue tracker and didn't find a similar bug report.
- [x] I have checked Superset's logs for errors and if I found a relevant Python stacktrace, I included it here as text in the "additional context" section.
Contributor guide
Research direction
Reproduce the issue in Superset 6.0.0 with a dashboard containing a chart and a detail report on separate tabs. Trace the existing same-tab cross-filter flow from a chart selection, then verify that selecting Genre = Sports updates the detail report while preserving context and filters across tabs.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- analytics, data-visualization
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100