BUG: should constructing Index from a Series make a copy?

From a comment of @jbrockmendel at https://github.com/pandas-dev/pandas/pull/41878#issuecomment-881557871:

ser = pd.Series(range(5))
idx = pd.Index(ser)
ser[0] = 10
>>> idx[0]
10

In the above, we create an Index from a Series, then mutate the Series, which also updated the Index, while an Index is assumed to be immutable.

Changing the example a bit, you can obtain wrong values with indexing this way:

ser = pd.Series(range(5))
idx = pd.Index(ser)

ser.index = idx

>>> ser[0]
0
>>> ser.iloc[0] = 10
>>> ser[0]
10
>>> ser
10    10
1      1
2      2
3      3
4      4
dtype: int64

So ser[0] is still giving a result, while that key doesn’t actually exist in the Series’ index at that point.

I know that generally we consider this a user error if you would do this with a numpy array (idx = pd.Index(arr) and mutating the array), but here you get that by only using high-level pandas objects itself. In which case we should prevent this from happening?

[ehansis]

@rhshadrach OK, thanks, I’ll try to check that if I ever manage to get the segmentation faults reproduced. Let me know if I can be of further help.

[jorisvandenbossche]

BTW, the other way around, when constructing a Series from an Index, we do take a copy to avoid such issues. In Series.__init__:

https://github.com/pandas-dev/pandas/blob/57d8d3a7cc2c4afc8746bf774b5062fa70c0f5fd/pandas/core/series.py#L401-L409