Question 169673 in Azure Question posted in
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Can Azure search for specific values in a column and its corresponding data from other columns?

I have following scenerio where I have to check for values in a column and its corresponding values in other columns. If any one of the value is not null then need to return true.
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Suppose I have to check for values D, E and F in column1 and check its corresponding values in column2 and column3. Here column2 contains NaN but column3 contains data then return true

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2

Answers


  1. 0

    If I understand correctly, lets say you have the following data frame:

    import numpy as np
import pandas as pd
df=pd.DataFrame({"Column1":['A','B','C','D'],'Column2':[1,2,3,np.nan],'Column3':['x','y',np.nan,np.nan]})
print(df)

  Column1  Column2 Column3
0       A      1.0       x
1       B      2.0       y
2       C      3.0     NaN
3       D      NaN     NaN

    Then you should first set the column you want to check(Column1 in our case) as an index and do the following:

    df.set_index('Column1').notna().any(axis=1)

Column1
A     True
B     True
C     True
D    False
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  2. 0

    Assuming you want to test if all rows of the target have at least one non-NaN value (any), use:

    target = ['D', 'E', 'F']

out = (df.loc[df['Column1'].isin(target), ['Column2', 'Column3']]
         .notna().any(axis=1)
         .all()
      )

    output: True (but would be False if value1 was NaN)

    If you want to check if there is at least one non-NaN cell, use any in both cases:

    target = ['D', 'E', 'F']

out = (df.loc[df['Column1'].isin(target), ['Column2', 'Column3']]
         .notna().any(axis=1)
         .any()
      )

    output: True (and would still be True if value1 was NaN)

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