BUG: Assigning back dataframe with dropna does not work, but works with inplace = True
- [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.

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

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**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
# Your code here
import pandas as pd
import numpy as np
test_df1 = pd.DataFrame({'a':[1,2,3,4],'b':['a','b','c','d'],'c':[np.nan,np.nan,np.nan,np.nan]})
test_df2 = pd.DataFrame({'a':[1,2,3,4],'b':[np.nan,np.nan,np.nan,np.nan],'c':['a','b','c','d']})

def drop_na_test1(df):
    df = df.dropna(axis=1,how='all')
    return df

def drop_na_test2(df):
    df.dropna(axis=1,how='all',inplace=True)
    return df

dfs_to_process = [test_df1,test_df2]
for df in dfs_to_process:
    df = drop_na_test1(df)
display(test_df1)
display(test_df2)

for df in dfs_to_process:
    df = drop_na_test2(df)
display(test_df1)
display(test_df2)
```

#### Problem description

[this should explain **why** the current behaviour is a problem and why the expected output is a better solution]
Assigning back dataframe with dropna() should yield same result as dropna(inplace=True).

#### Expected Output
Expect same result with df=df.dropna() as df.dropna(inplace=True)
#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here leaving a blank line after the details tag]

</details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.9.4.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 42 Stepping 7, GenuineIntel
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : English_United States.1252

pandas           : 1.2.4
numpy            : 1.20.2
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1
setuptools       : 56.0.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.22.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.1
numexpr          : None
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.3
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : None
numba            : None
