EUbaldiEC opened a new issue, #40709: URL: https://github.com/apache/superset/issues/40709
### Bug description When creating heatmaps (both tested in 6.0.0 and 6.1.0) with normalisation across X/Y (and posibly color normalisation), the plot will fail when only one column/row is left by applying dynamic filters. Example is in the flights sample dataset, on a fresh install, putting `AIRLINE` as the X and `CITY` as Y (metric `COUNT(*)` or `SUM(AIRLINE_DELAY)` or anything else). <img width="1492" height="818" alt="Image" src="https://github.com/user-attachments/assets/411bc601-0ec8-4b98-ba63-d8ac208f7936"; /> It works as expected with the normalisation across X (above), but as soon as a filter reducing the data to a single column (like `AIRLINE = 'AA'`), a "Cannot set a DataFrame with multiple columns to the single column rank" error is shown. <img width="1492" height="818" alt="Image" src="https://github.com/user-attachments/assets/95804232-048f-421d-81df-8b862cf994f7"; /> The weird thing is that then the plot works with no issues if one normalises across rows (Y) (the same works when normalising across platform): <img width="1492" height="818" alt="Image" src="https://github.com/user-attachments/assets/a5d7e808-cc76-455e-9b2e-2b1d18f0782d"; /> To conclude, an unexptected behavior is also found when reducing both the rows and the columns to 1: - If one normalises across X/Y we get an empty plot (should plot a single square with 100% in both cases) <img width="1486" height="858" alt="Image" src="https://github.com/user-attachments/assets/4fc90c92-8266-4fa5-9093-d32b282460ed"; /> - Instead, when normalising over the heatmap this is working as expected: <img width="1496" height="847" alt="Image" src="https://github.com/user-attachments/assets/8b1604e6-43c9-4161-9cd6-0a1401eeb1bd"; /> This might be related to the underlying eChart heatmap implementation (and the error thrown [stems from pandas](https://stackoverflow.com/questions/75500734/cannot-set-a-dataframe-with-multiple-columns-to-the-single-column-total-servings) postprocessing rank function) but I am struggling to understand where to look in the codebase to check for issues. Let me know should you need any additional information, thanks! ### Screenshots/recordings Example is in the flights sample dataset, on a fresh install, putting `AIRLINE` as the X and `CITY` as Y (metric `COUNT(*)` or `SUM(AIRLINE_DELAY)` or anything else). <img width="1492" height="818" alt="Image" src="https://github.com/user-attachments/assets/411bc601-0ec8-4b98-ba63-d8ac208f7936"; /> It works as expected with the normalisation across X (above), but as soon as a filter reducing the data to a single column (like `AIRLINE = 'AA'`), a "Cannot set a DataFrame with multiple columns to the single column rank" error is shown. <img width="1492" height="818" alt="Image" src="https://github.com/user-attachments/assets/95804232-048f-421d-81df-8b862cf994f7"; /> The weird thing is that then the plot works with no issues if one normalises across rows (Y) (the same works when normalising across platform): <img width="1492" height="818" alt="Image" src="https://github.com/user-attachments/assets/a5d7e808-cc76-455e-9b2e-2b1d18f0782d"; /> To conclude, an unexptected behavior is also found when reducing both the rows and the columns to 1: - If one normalises across X/Y we get an empty plot (should plot a single square with 100% in both cases) <img width="1486" height="858" alt="Image" src="https://github.com/user-attachments/assets/4fc90c92-8266-4fa5-9093-d32b282460ed"; /> - Instead, when normalising over the heatmap this is working as expected: <img width="1496" height="847" alt="Image" src="https://github.com/user-attachments/assets/8b1604e6-43c9-4161-9cd6-0a1401eeb1bd"; /> ### Superset version 6.0.0 ### Python version 3.10 ### Node version 18 or greater ### Browser Not applicable ### Additional context Here is the python stacktrace from container logs: ``` 2026-06-03 12:27:08,053:WARNING:superset.views.error_handling:Exception Traceback (most recent call last): File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/flask/app.py", line 917, in full_dispatch_request rv = self.dispatch_request() File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/flask/app.py", line 902, in dispatch_request return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args) # type: ignore[no-any-return] File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/flask_appbuilder/security/decorators.py", line 101, in wraps return f(self, *args, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/views/base_api.py", line 120, in wraps duration, response = time_function(f, self, *args, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/utils/core.py", line 1559, in time_function response = func(*args, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/utils/log.py", line 299, in wrapper value = f(*args, add_extra_log_payload=log, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/charts/data/api.py", line 289, in data return self._get_data_response( File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/utils/log.py", line 301, in wrapper value = f(*args, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/charts/data/api.py", line 496, in _get_data_response result = command.run(force_cached=force_cached) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/commands/chart/data/get_data_command.py", line 46, in run payload = self._query_context.get_payload( File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context.py", line 99, in get_payload return self._processor.get_payload(cache_query_context, force_cached) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context_processor.py", line 353, in get_payload query_results = [ File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context_processor.py", line 354, in <listcomp> get_query_results( File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_actions.py", line 290, in get_query_results return result_func(query_context, query_obj, force_cached) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_actions.py", line 160, in _get_full payload = query_context.get_df_payload(query_obj, force_cached=force_cached) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context.py", line 129, in get_df_payload return self._processor.get_df_payload( File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context_processor.py", line 131, in get_df_payload query_result = self.get_query_result(query_obj) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context_processor.py", line 243, in get_query_result return self._qc_datasource.get_query_result(query_object) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/models/helpers.py", line 1343, in get_query_result df = query_object.exec_post_processing(df) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_object.py", line 542, in exec_post_processing df = getattr(pandas_postprocessing, operation)(df, **options) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/utils/pandas_postprocessing/rank.py", line 37, in rank df["rank"] = gb.apply(lambda x: x[metric].rank(pct=True)) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/pandas/core/frame.py", line 4081, in __setitem__ self._set_item_frame_value(key, value) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/pandas/core/frame.py", line 4239, in _set_item_frame_value raise ValueError( ValueError: Cannot set a DataFrame with multiple columns to the single column rank 2026-06-03 12:27:08,053:ERROR:superset.views.error_handling:Cannot set a DataFrame with multiple columns to the single column rank Traceback (most recent call last): File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/flask/app.py", line 917, in full_dispatch_request rv = self.dispatch_request() File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/flask/app.py", line 902, in dispatch_request return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args) # type: ignore[no-any-return] File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/flask_appbuilder/security/decorators.py", line 101, in wraps return f(self, *args, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/views/base_api.py", line 120, in wraps duration, response = time_function(f, self, *args, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/utils/core.py", line 1559, in time_function response = func(*args, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/utils/log.py", line 299, in wrapper value = f(*args, add_extra_log_payload=log, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/charts/data/api.py", line 289, in data return self._get_data_response( File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/utils/log.py", line 301, in wrapper value = f(*args, **kwargs) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/charts/data/api.py", line 496, in _get_data_response result = command.run(force_cached=force_cached) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/commands/chart/data/get_data_command.py", line 46, in run payload = self._query_context.get_payload( File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context.py", line 99, in get_payload return self._processor.get_payload(cache_query_context, force_cached) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context_processor.py", line 353, in get_payload query_results = [ File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context_processor.py", line 354, in <listcomp> get_query_results( File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_actions.py", line 290, in get_query_results return result_func(query_context, query_obj, force_cached) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_actions.py", line 160, in _get_full payload = query_context.get_df_payload(query_obj, force_cached=force_cached) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context.py", line 129, in get_df_payload return self._processor.get_df_payload( File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context_processor.py", line 131, in get_df_payload query_result = self.get_query_result(query_obj) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_context_processor.py", line 243, in get_query_result return self._qc_datasource.get_query_result(query_object) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/models/helpers.py", line 1343, in get_query_result df = query_object.exec_post_processing(df) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/common/query_object.py", line 542, in exec_post_processing df = getattr(pandas_postprocessing, operation)(df, **options) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/superset/utils/pandas_postprocessing/rank.py", line 37, in rank df["rank"] = gb.apply(lambda x: x[metric].rank(pct=True)) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/pandas/core/frame.py", line 4081, in __setitem__ self._set_item_frame_value(key, value) File "/home/user/.local/share/pipx/venvs/apache-superset/lib/python3.10/site-packages/pandas/core/frame.py", line 4239, in _set_item_frame_value raise ValueError( ValueError: Cannot set a DataFrame with multiple columns to the single column rank ``` ### 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. -- This is an automated message from the Apache Git Service. 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