Replace column values based on partial string match from another dataframe python pandas

Question

I need to update some cell values, based on keys from a different dataframe. The keys are always unique strings, but the second dataframe may or may not contain some extra text at the beginning or at the end of the key. (not necessarily separated by " ")

Frame: 

Keys   Values   

x1      1            
x2      0              
x3      0             
x4      0             
x5      1 

Correction:

Name   Values   
SS x1       1             
x2 AA       1            
 x4         1


Expected output Frame: 

Keys   Values   

x1      1            
x2      1              
x3      0             
x4      1             
x5      1 

I am using the following:

frame.loc[frame['Keys'].isin(correction['Keys']), ['Values']] = correction['Values']

The problem is that isin returns True only on exact mach (as far as I know), which works for only about 30% of my data.

Answer 1

First extract values by Frame['Keys'] joined by | for OR:

pat = '|'.join(x for x in Frame['Keys'])

Correction['Name'] = Correction['Name'].str.extract('('+ pat + ')', expand=False)
#remove non matched rows filled by NaNs
Correction = Correction.dropna(subset=['Name'])
print (Correction)
  Name  Values
0   x1       1
1   x2       1
2   x4       1

Then create dictionary and map for map by Correction['Name']:

d = dict(zip(Correction['Name'], Correction['Values']))
Frame['Values'] = Frame['Keys'].map(d).fillna(Frame['Values']).astype(int)
print (Frame)
  Keys  Values
0   x1       1
1   x2       1
2   x3       0
3   x4       1
4   x5       1