Return the closest matched value to [reference] from [ABCD] columns

What is the cleanest way to return the closest matched value to [reference] from [ABCD] columns.

Output is the closest value. e.g. for the first row, absolute delta is [19 40 45 95] so the closest value to return is -21.

df1 = pd.DataFrame(np.random.randint(-100,300,size=(100, 4)), columns=list('ABCD')) # Generate Random Dataframe
df2 = pd.DataFrame(np.random.randint(-100,100,size=(100, 1)), columns=['reference'])
df = pd.concat([df1,df2], axis=1)
df['closest_value'] = "?"
df

>Solution :

Try this :

idx = df.drop(['reference'], axis=1).sub(df.reference, axis=0).abs().idxmin(1)
df['closest_value'] = df.lookup(df.index, idx)

>>> display(df)

Edit:

Since pandas.DataFrame.lookup will be (or is?) deprecated, you can :
Replace this line :

df.lookup(df.index, df['col'])

By these:

out = df.set_index(idx, append=True)
out['closest_value'] = df.stack()