BUG: Numpy ufunc accumulate doesn't run correctly on Pandas 1.2.0
- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the latest version of pandas.

- [X] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample

```python
import pandas as pd
import numpy as np

# %% Create random data

np.random.seed(50)
number_of_observations = 100
values = np.random.randn(number_of_observations)

# %% Form DataFrame

data = pd.DataFrame(values, columns=['A'])
data = data.cumsum()  # Get more local maximums for comparison

# %% Accumulate the maximum

pandas_accumulate = np.maximum.accumulate(data).to_numpy()
numpy_accumulate = np.maximum.accumulate(data.to_numpy())

assert np.allclose(pandas_accumulate, numpy_accumulate)

```

#### Problem description

Numpy maximum accumulate does nothing to the data compared with the same function applied to the numpy array (confirmed with axis argument specified too). Assert statement passed on pandas version 1.1.5. Broken in master as of writing also.

#### Expected Output

As previous version, the result of the numpy function in the pandas DataFrame.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 3e89b4c4b1580aa890023fc550774e63d499da25
python           : 3.7.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Tue Nov 10 00:10:30 PST 2020; root:xnu-6153.141.10~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_GB.UTF-8
pandas           : 1.2.0
numpy            : 1.19.5
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.0.3
setuptools       : 40.8.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.4.1
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.12.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
