I think you need Index.intersection:

df = pd.DataFrame({'A':[1,2,3],
                   'B':[4,5,6],
                   'C':[7,8,9],
                   'D':[1,3,5],
                   'E':[5,3,6],
                   'F':[7,4,3]})

print (df)
   A  B  C  D  E  F
0  1  4  7  1  5  7
1  2  5  8  3  3  4
2  3  6  9  5  6  3

lst = ['A','R','B']

print (df.columns.intersection(lst))
Index(['A', 'B'], dtype="object")

data = df[df.columns.intersection(lst)]
print (data)
   A  B
0  1  4
1  2  5
2  3  6

Another solution with numpy.intersect1d:

data = df[np.intersect1d(df.columns, lst)]
print (data)
   A  B
0  1  4
1  2  5
2  3  6