Pandas 获取包含另一列值周围括号的列的列标题名称

Question

Consider this sample df

sample_df = pd.DataFrame({'our_value':[14,24], 'opt1':['10 - 20','10 - 20'],'opt2':['21 - 30','21 - 30'],'opt3':['31 - 40','31 - 40'],'opt4':['41 - 50','41 - 50']})

    our_value   opt1      opt2    opt3    opt4
0      14      10 - 20  21 - 30 31 - 40 41 - 50
1      24      10 - 20  21 - 30 31 - 40 41 - 50

I am attempting to create a column that contains the name of the column header if the value in the 'our_value' column is between the two values in the respective column. So, intended outcome is:

     our_value    opt1    opt2    opt3    opt4   our_opt
0      14      10 - 20  21 - 30 31 - 40 41 - 50     opt1
1      24      10 - 20  21 - 30 31 - 40 41 - 50     opt2

Tried various approaches including a dictionary of keys of the column headers and values being a list with two items, the lower and upper bound of the column like this:

test_dict = {'opt1':['10, 20], 'opt2':[21,30]....}  

Using map to apply that did not work.

These approaches, likewise, did not work

for k,v in test_dict.items():
    df[k] = df['our_value'].map(lambda x: v[0] if x < v[1] else v[1])
      if df['our_value'].between(v[0], v[1]).all():
         df['our_opt'] = k

I am sure I am missing something fundamental at this point. But, like writing your own novel or article, I am unable to proofread this code and find what is missing. Thanks for taking a look.

Answer 1

Let us get the low and high for the range , then we can do

s = sample_df.filter(like='opt')
low = s.apply(lambda x : x.str.split(' - ').str[0].astype(int))
high = s.apply(lambda x : x.str.split(' - ').str[1].astype(int))
sample_df['out'] = (low.le(sample_df['our_value'],axis=0) & high.ge(sample_df['our_value'],axis=0)).dot(s.columns)
Out[63]: 
0    opt1
1    opt2
dtype: object