将元组列表中的对象与数据帧中的对象进行匹配，如果存在匹配项，则创建新列

Question

Consider the following list of tuples:

some_strings = [('Name1', 'ABCD', 'DEFG', 'Score=12'),
                ('Name2', 'JKLL', 'RMPQ', 'Score=11')]

And the following pandas dataframe:

Sequence ID    Left Sequence    Right Sequence
Name1              ABCD             RQLM
Name1              ABCR             PLMT
Name2              JKLL             ZFGQ
Name2              RPLP             FTRD

I am trying to compare the second object in the tuple to the column df['Left Sequence'] to check for an exact match (not concerned with partial matches), and if the match occurs, print dimer in a new column at the end of the df. If a match does not occur, I will print NA. Here is the code I have tried:

for x in some_strings:
    for y in x:
        df['Dimers'] = df['Left Sequence'].apply(lambda s: 'Dimer' if s == y[1] else 'NA')

My expected output:

Sequence ID    Left Sequence    Right Sequence    Dimers
Name1              ABCD             RQLM          Dimer
Name1              ABCR             PLMT           NA
Name2              JKLL             ZFGQ          Dimer
Name2              RPLP             FTRD           NA

My actual output (you can probably guess this):

Sequence ID    Left Sequence    Right Sequence    Dimers
Name1              ABCD             RQLM           NA
Name1              ABCR             PLMT           NA
Name2              JKLL             ZFGQ           NA
Name2              RPLP             FTRD           NA

Any suggestions would be great.

Answer 1

Create mask of Boolean : we using isin to create the mask

mask=df.iloc[:,:-1].apply(tuple,1).isin([x[:-2] for x in some_strings])    
df['Dimer']='NA'
df.loc[mask,'Dimer']='Dimer'        
df
Out[1120]: 
  SequenceID LeftSequence RightSequence  Dimer
0      Name1         ABCD          RQLM  Dimer
1      Name1         ABCR          PLMT     NA
2      Name2         JKLL          ZFGQ  Dimer
3      Name2         RPLP          FTRD     NA