ENH: Add a level option to pd.DataFrame.append()

[MoAly98]

I have two dataframes:

The first one looks like this:

		variable
entry	subentry
0	1	X
	2	Y
	3	Z

and the second one looks like:

		variable
entry	subentry
0	1	A
	2	B

I would like to merge the two dataframe such that I get:

		variable
entry	subentry
0	1	X
	2	Y
	3	Z
1	1	A
	2	B

Simply using df1.append(df2, ignore_index=True) gives

	variable
0	X
1	Y
2	Z
3	A
4	B

In other words, it appends on the highest level (level 1) in the dataframes. I think it important to allow the user dealing with mutli-index dataframes to specify which level of the dataframe to append on. In the simple example above, this would allow me to specify "entry" as the index to append on.

Here is a code sinppet that will reproduce the problem:

	arrays = [
	    np.array([0,0,0]),
	    np.array([0,1,2]),]
	arrays_2 = [
	    np.array([0,0]),
	    np.array([0,1]),]
	df1 = pd.DataFrame(np.random.randn(3, 1), index=arrays)
	df2 = pd.DataFrame(np.random.randn(2, 1), index=arrays_2)
	df = df1.append(df2, ignore_index=True)
	print(df)

In practice, I am looking ao combine N dataframes, each with a different number of "entry" rows. So I am looking for an approach that will not rely on me knowing the exact of the dataframes I am combining.

[phofl]

It does append on all levels and calls reset_index afterwards.

-1 on this

[MoAly98]

This is exactly what I'm asking to make more flexible. The reseting of the index causes the loss of my multi-index structure. I think there should be flexibility in append to just append on one level and only reset one level's index.

[mroeschke]

I would be also -1 toward this suggestion for similar reasons as well as the likelihood for append to be deprecated in a future release: #35407

[mroeschke]

Thanks for the suggestion, but since there hasn't been additional support from the community or other core devs, going to close.