BUG: When using apply on a DataFrame with SparseDtype, passing raw=True doesn't have any effect.

[victor-ab]

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of pandas.

---

Code Sample, a copy-pastable example

import pandas as pd
import numpy as np

pd.DataFrame(
    [[0, 1, 0, 2, 0, 3, 0, 4]],
    dtype=pd.SparseDtype(np.dtype("int")),
).apply(lambda x: type(x), raw=True, axis=1)

Output:

0 <class 'pandas.core.series.Series'>

Problem description

When using apply on a DataFrame with SparseDtype, passing raw=True doesn't have any effect.

#32425 is related but did not solve it.

Expected Output

0 <class 'numpy.ndarray'>

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.6.8.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None

pandas : 1.0.3
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 46.1.3.post20200330
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.13.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : 0.3.2
gcsfs : None
lxml.etree : 4.4.2
matplotlib : 3.1.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
xlsxwriter : None
numba : 0.48.0

[mroeschke]

#32425's fix will be applied when pandas 1.1 is released (should be in a couple of months). This fix was not backported to the 1.0.x versions of pandas