Compare 'like' columns in Python dataframe

Question

I have two dataframes that should have the same data but come from different sources. I would like to return the column names from df1 and the corresponding match rate for that column when compared against the equivalent in df2.

Inputs:

df1 = 

ID  Age  Value  Name

1   10    1000  Red

2   20    2000  Blue

3   30    3000  Orange

4   40    4000  Grey

df2 =

Age_2  Value_2  Name_2

10    1000  red

20    1500  blue

30    3000  orange

40    4000  white

Desired output:

Name  MatchRate

ID     N/A

Age    1.00

Value  0.75  

Name   0.75

Answer 1

I suggest using difflib.SequenceMatcher for comparing strings for example following way

import difflib
import pandas as pd
def get_ratio(x,y):
    return difflib.SequenceMatcher(None,x,y).ratio()
df = pd.DataFrame({"col1":["Red","Blue","Orange","Grey","White"],"col2":["red","blue","orange","grey","black"]})
df["ratio"] = df.apply(lambda row:get_ratio(row.col1,row.col2),axis=1)
print(df)

gives output

     col1    col2     ratio
0     Red     red  0.666667
1    Blue    blue  0.750000
2  Orange  orange  0.833333
3    Grey    grey  0.750000
4   White   black  0.000000