如何比较两个 pandas dataframe 行并返回值？

Question

I have 2 pandas dataframe like 1st Datafarme

 index  a   b   c   d
   0    4   5   3   2
   1    1   10  21  34
   2    3   32  1   45
   3    56  42  42  23

2nd Dataframe

index   a  b  c  d
  LL    2  2  2  1
  UL    42 2  1  8

I want excepted output like this.

 index  a   b   c   d   result
   0    4   5   3   2    [5,3]
   1    1   10  21  34   [1,10,21,34]
   2    3   32  1   45   [32,1,45]
   3    56  42  42  23   [56,42,42,23]

In this I m comparing 2nd dataframe rows with 1st dataframe row. Condition is like if 1st dataframe value is smaller than LL row of 2nd dataframe it will be add in result column likewise if 1st dataframe value is greater than UL row of 2nd dataframe it will be added in result column.

Answer 1

you could do

cond = (first_df<second_df.loc['LL',:]) | (first_df>second_df.loc['UL',:])
first_df['result'] = first_df[cond].apply(lambda x : list(x.dropna()), axis=1)

this being given that index is an index in both your dataframes, if it's not, you could do

first_df.set_index('index', inplace=True)
second_df.set_index('index', inplace=True)

    a   b   c   d   result
index                   
0   4   5   3   2   [5.0, 3.0]
1   1   10  21  34  [1.0, 10.0, 21.0, 34.0]
2   3   32  1   45  [32.0, 1.0, 45.0]
3   56  42  42  23  [56.0, 42.0, 42.0, 23.0]