[GitHub] [superset] zhaoyongjie commented on pull request #15975: fix: eliminate cartesian product columns in pivot operator

[GitBox <gi...@apache.org>]

zhaoyongjie commented on pull request #15975:
URL: https://github.com/apache/superset/pull/15975#issuecomment-890312917


   > Thanks for addressing this! ❤️
   > 
   > One minor comment. Also just wondering - would `dropna(how="all", ...)` on the final result work as a simpler solution?
   
   sorry, missing this review. `dropna with all` might be Ignore `NULL` value of metric, for instance
   ```
   import pandas as pd
   import numpy as np
   from datetime import datetime
   
   df = pd.DataFrame({
       "ds": [datetime(2012, 11, 1), datetime(2012, 11, 1)],
       "col1": ['a', 'b'],
       "col2": ['a', 'b'],
       "metric": [np.NaN, 9], #<--- metric values
   })
   df
   
     | ds | col1 | col2 | metric
   -- | -- | -- | -- | --
   2012-11-01 | a | a | NaN
   2012-11-01 | b | b | 9.0
   
   df = df.pivot_table(
       index="ds",
       columns=["col1", "col2"],
       values=["metric"],
       aggfunc={
        "metric": np.mean
       },
       dropna=False
   )
   
   df.dropna(how="all", axis=1)
   
   
   
     | metric
   -- | --
   9.0
   ```
   
   
   


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