DataFrame.

import pandas

dict1 = {"Subjects": ["Physics", "Chemistry", "Mathematics"], "Grades": ["A", "C", "B"], "Marks": [95, 72, 88]}
df1 = pandas.DataFrame(dict1)
print("df1: \n", df1)

dict2 = {"Subjects": ["Biology", "Chemistry", "Literature"], "Marks": [85, 72, 68], "Remarks": ["Very Good", "Good", "Fair"]}
df2 = pandas.DataFrame(dict2)
print("df2: \n", df2)

df6 = pandas.merge(df1, df2, how="outer", on="Subjects")
print("After outer join: \n", df6)

As we can see the how parameter indicates we are performing one outer join operation. And the “on” parameter indicates that we are performing the merge operation on the “Subjects” column.

So, the output of the merge operation using outer join will be:

df1: 
       Subjects Grades  Marks
0      Physics      A     95
1    Chemistry      C     72
2  Mathematics      B     88
df2: 
      Subjects  Marks    Remarks
0     Biology     85  Very Good
1   Chemistry     72       Good
2  Literature     68       Fair
After outer join: 
       Subjects Grades  Marks_x  Marks_y    Remarks
0      Physics      A     95.0      NaN        NaN
1    Chemistry      C     72.0     72.0       Good
2  Mathematics      B     88.0      NaN        NaN
3      Biology    NaN      NaN     85.0  Very Good
4   Literature    NaN      NaN     68.0       Fair