BUG: Type error in groupby.transform(interpolate)

[hliatrussellinvestments]

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Reproducible Example

import numpy as np
import pandas as pd

np.random.seed(500)
test_df = pd.DataFrame({
    'a': np.random.randint(low=0, high=1000, size=10000),
    'b': np.random.choice([1, 2, 4, 7, np.nan], size=10000, p=([0.2475] * 4 + [0.01]))
})
test_df.groupby('a').transform(pd.DataFrame.interpolate)

Issue Description

When I want to interpolation of some columns (column ‘b’ in example) in a data frame according to some other columns (column ‘a’ in example), I group by the accorded columns (column ‘a’ in example) and then transform the group using the interpolate method.
It worked in version 1.1.1.

Expected Behavior

The nan values in column ‘b’ should be replaced by interpolated value according to column ‘a’.

Installed Versions

INSTALLED VERSIONS

commit : bb1f651
python : 3.8.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.4.0
numpy : 1.19.0
pytz : 2021.3
dateutil : 2.8.1
pip : 21.3.1
setuptools : 49.2.1
Cython : None
pytest : 5.4.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
fsspec : 2021.10.0
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.5.4
sqlalchemy : 1.4.31
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None

[jbrockmendel]

If you look at the full traceback, you'll see the problem is that pd.DataFrame.interpolate is the wrong method to pass. Try pd.Series.interpolate instead.

[mroeschke]

Correct, the internals were refactored since 1.1 to fix bugs related to 2D processing therefore passing in pd.Series.interpolate works instead

In [6]: import numpy as np
   ...: import pandas as pd
   ...:
   ...: np.random.seed(500)
   ...: test_df = pd.DataFrame({
   ...:     'a': np.random.randint(low=0, high=1000, size=10000),
   ...:     'b': np.random.choice([1, 2, 4, 7, np.nan], size=10000, p=([0.2475] * 4 + [0.01]))
   ...: })
   ...: test_df.groupby('a').transform(pd.Series.interpolate)
Out[6]:
        b
0     4.0
1     1.0
2     2.0
3     7.0
4     4.0
...   ...
9995  4.0
9996  7.0
9997  4.0
9998  4.0
9999  4.0

[10000 rows x 1 columns]

[simonjayhawkins]

Correct, the internals were refactored since 1.1 to fix bugs related to 2D processing therefore passing in pd.Series.interpolate works instead

hmm, looks like first bad commit: [a395185] Deprecate passing args as positional in DataFrame/Series.interpolate (#41510)

So previously DataFrame/Series.interpolate were the same function and was changed in pandas 1.3