I don't think this is a good idea. This breaks the current behavior and the special case for object looks a bit weird. What happens if you assign a different dtype? This would still change which is inconsistent then-

Also you have to keep the fall through clause

also wont this isinstance be True for everything?

also wont this isinstance be True for everything? Yes. I should not do like this

I don't think this is a good idea. This breaks the current behavior and the special case for object looks a bit weird. What happens if you assign a different dtype? This would still change which is inconsistent then-

Also you have to keep the fall through clause

From this issue #19647 , when adding element to empty object Series. The series should change based on type object which is set by user.

s = pd.Series(dtype='object')
s.loc['myint'] = 1
s.loc['myfloat'] = 2.

Expected output:

myint      1.0
myfloat    2.0
dtype: object

If I assign to different dtype, for example

s = pd.Series(dtype=float)
s.loc['myint'] = 1.0
s.loc['myfloat'] = 2

Output:

myint      1.0
myfloat    2.0
dtype: float64

What happens if the empty series has some other dtype apart from object? Then this is not caught by your current change.

on the other side, if the dtype is the default this should still change, this is not covered here

What happens if the empty series has some other dtype apart from object? Then this is not caught by your current change.

If the empty series has some other dtype apart from object, for example

s = pd.Series(dtype=float)
s.loc['myint'] = 1.0
s.loc['myfloat'] = 2
print(s)

Output will be like this

myint      1.0
myfloat    2.0
dtype: float64