Merging 2 columns within 1 pandas dataframe

Question

Given 2 different dataframes, I would actually like to map column D in df1 and column E in df2 as New on my appended dataframe.

Below are my test codes.

df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
   ...:                     'B': ['B0', 'B1', 'B2', 'B3'],
   ...:                     'C': ['C0', 'C1', 'C2', 'C3'],
   ...:                     'D': ['D0', 'D1', 'D2', 'D3']},
   ...:                     index=[0, 1, 2, 3])

df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
   ...:                     'B': ['B4', 'B5', 'B6', 'B7'],
   ...:                     'C': ['C4', 'C5', 'C6', 'C7'],
   ...:                     'E': ['D4', 'D5', 'D6', 'D7']},
   ...:                      index=[4, 5, 6, 7])

results = df1.append(df2)

I get dataframe with column E and D essentially meaning the same thing, is there a way I can join those 2 columns?

I am also dealing with huge amounts of data, so its preferred that no duplicate dataframes are created just to do that.

Answer 1

I think you can rename columns D and E before append :

df1 = df1.rename(columns={'D':'New'})
df2 = df2.rename(columns={'E':'New'})

results = df1.append(df2)
print results
    A   B   C New
0  A0  B0  C0  D0
1  A1  B1  C1  D1
2  A2  B2  C2  D2
3  A3  B3  C3  D3
4  A4  B4  C4  D4
5  A5  B5  C5  D5
6  A6  B6  C6  D6
7  A7  B7  C7  D7