I have two dataframe

One with codes and values need to map to other dataframe

```py
B = pd.DataFrame({'Code': ['a', 'b', 'c', 'a', 'e','b','b','c'],
                  'Value': ["House with indoor pool", "House with Gray_C_Door", "Big Chandelier",
                            "Window Glass", "Frame Window",'High Column','Wood Raling', 'Window Glass trim']})

```

Other datframe content lots of data with values and need to make a new column base on dataframe "B" column "Code".

```py
A = pd.DataFrame({'Test': [2,34,12,45,np.nan,34,56,23,56,87,23,67,89,123,np.nan],
                  'Name': [ "House with indoor pool","House with Gray_C_Door",'House with indoor pool and Porch',"Wood Raling",
                           'Window Glass Tinted',"Windows Glass_with",'Big Chandelier', "Frame Window",np.nan,"Window glass","House with indoor pool",'High column with',
                           "Window Glass trim",'Frame Window',"glass Window"],
                 'Value': ["50", "100", "70", "20", "15",'75','50',"10", "10", "34", "5", "56",'12','83',np.nan]})
A.loc[:,'NewName'] = A['Name']

```

So I'm using the below code to replace A['NewName'].

```
A['NewName']= A['NewName'].replace(B.set_index('Value')['Code'])

    Test    Name                                Value   NewName
0   2.0000  House with indoor pool              50      a
1   34.0000 House with Gray_C_Door              100     b
2   12.0000 House with indoor pool and Porch    70      House with indoor pool and Porch
3   45.0000 Wood Raling                         20      b
4   NaN     Window Glass Tinted                 15      Window Glass Tinted
5   34.0000 Windows Glass_with                  75      Windows Glass_with
6   56.0000 Big Chandelier                      50      c
7   23.0000 Frame Window                        10      e
8   56.0000 NaN                                 10      NaN
9   87.0000 Window glass                        34      Window glass
10  23.0000 House with indoor pool              5       a
11  67.0000 High column with                    56      High column with
12  89.0000 Window Glass trim                   12      c
13  123.000 Frame Window                        83      e
14  NaN     glass Window                        NaN     glass Window

```

However, some A['NewName'] are not matching with B['Value'] and doesn't give an exact expected outcome.

Is there a way, I can match those values when It has partial matching with A['NewName'] and give the correct code?
I mean for instance when A['NewName'] has "House with indoor pool and Porch" I want to match it with B['Value'] = 'House with indoor pool' and replace it with correct B['Code] = 'a'. I couldn't add that to the data frame B Values column because there are several ways it could change after "House with indoor pool" (for ex: "House with indoor pool\_ with big glass door", "House with indoor pool and High railings" etc.)

Is this possible to do it in a map/replace function or any other method?

Thanks in advacne!