I have two tables that have the same column names. I want to merge them but need to keep the order of the index:
df1
x y
0 one 1
1 two 2
2 three 3
3 four 4
4 five 5
df2
x y
0 six 6
1 seven 7
2 eight 8
3 nine 9
4 ten 10
the order of the merge is very important as I need index 0 of df1 to be first and index 0 of df2 to be second and so on.The result I want is the following:
This is to create an excel file to integrate into SAP so the order is very important . Could you help me find the correct merge for this?
df
x y
0 one 1
0 six 6
1 two 2
1 seven 7
2 three 3
2 eight 8
3 four 4
3 nine 9
4 five 5
4 ten 10
```
I tried different merges but couldn't find one that respects the order of the index.
You can pd.concat()
the two dataframes and sort the index as next step:
out = pd.concat([df1, df2]).sort_index(kind="stable")
print(out)
Prints:
x y
0 one 1
0 six 6
1 two 2
1 seven 7
2 three 3
2 eight 8
3 four 4
3 nine 9
4 five 5
4 ten 10