Using pyarrow strings with pandas map or apply

I trying to create a new DataFrame column based on a transformation from another.
I'd like to have the return dtype as pyarrow[string] and not object.

I can do

In [2]: s = pd.Series([1, 2, 1, 2])
In [3]: names = {1: 'Creative', 2: 'VeriFone'}
In [4]: s.map(names)
Out[4]: 
0    Creative
1    VeriFone
2    Creative
3    VeriFone
dtype: object
In [5]: s.map(names).astype('string[pyarrow]')
Out[5]: 
0    Creative
1    VeriFone
2    Creative
3    VeriFone
dtype: string

But this create an intermediate series with object dtype.

I also tried:

In [6]: arr = pa.array(['', 'Creative', 'VeriFone'])
In [7]: s.apply(arr.__getitem__)
Out[7]: 
0    Creative
1    VeriFone
2    Creative
3    VeriFone
dtype: object

But the return dtype is object.

Is there a way to directly create a pd.Series with string[pyarrow] type from s?

When calling pd.Series.map or pd.Series.apply python code gets executed so there will be an intermediate python object no matter what.

If you're looking for performances it's best to use vectorized operations. For example you can use join:

s = pd.Series([1, 2, 1, 2])
names = pd.Series({1: 'Creative', 2: 'VeriFone'}, dtype='string[pyarrow]', name='name')
s.to_frame().join(names)['name']