Properly map values between two dataframes - pandas

Question

I have dataframe df
d = {'Col1': [10,67], 'Col2': [30,10],'Col3': [70,40]}
df = pd.DataFrame(data=d)
which results in
Col1 Col2 Col3
0 10 30 70
1 67 10 40
and df2
df2=pd.DataFrame(data=([25,36,47,(0,20)],[70,85,95,(20,40)],
[12,35,49,(40,60)],[50,49,21,(60,80)],[60,75,38,(80,100)]),
columns=["Col1","Col2","Col3","Range"])
which results in:
Col1 Col2 Col3 Range
0 25 36 47 (0, 20)
1 70 85 95 (20, 40)
2 12 35 49 (40, 60)
3 50 49 21 (60, 80)
4 60 75 38 (80, 100)
Both frames are just for example purposes and might be much bigger in reality. Both frames have the same columns but one.
I want to apply some function (x/y) between each value from df and a value in df2 from the same column. The value from df2 however maybe in varying rows depending on the Range column.
For example 10 from df (Col1) falls in range (0,20) in df2 therefore I want to use 25 from Col1 (df2) and do 10/25.
30 from df (Col2) falls in range (20,40) in df2 therefore I want to take 85 from Col2 (df2) and do 30/85.
70 from df (Col3) falls in range (60,80) in df2 therefore I want to take 21 from Col3 (df2) and do 70/21.
I want to do this for each row in df.
Don't really know how to do the proper mapping; I always tend to start with some for loops which are not very pretty especially if both dataframes are of bigger shape. Expected output can be any array, dataframe or the like composed of the resulting numbers.

Answer 1

Here is one way to do it by defining a helper function:
def find_denominator_for(v):
"""Helper function.
>>> find_denominator_for(10)
{'Col1': 25, 'Col2': 36, 'Col3': 47}
"""
for tup, sub_dict in df2.set_index("Range").to_dict(orient="index").items():
if min(tup) <= v <= max(tup):
return sub_dict
for col in df.columns:
df[col] = df[col] / df[col].apply(lambda x: find_denominator_for(x)[col])
Then:
print(df)
# Output
Col1 Col2 Col3
0 0.40 0.352941 3.333333
1 1.34 0.277778 0.421053