BUG:dtype=object columns with NaNs coerce integers to floats
- [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.

---

**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
df = pd.DataFrame({'name': [np.nan, "hi"],
                   'mask': [True, 4],
                   'weapon': [5, np.nan]}).astype(object)
print(df) 
"""
name  mask weapon
0  NaN  True      5
1   hi     4    NaN
""" # everything prints out correctly
print(df.iloc[0].values) # [nan True 5.0] # during indexing, 5 gets coerced to 5.0
# ultimately I want to be able to do df.to_csv(), and get unmodified data
```
#### Problem description

I have a dataframe of mixed types, which I cast to dtype=object, and NaNs in certain grids. Printing out the dataframe works fine, but when I try indexing into specific rows, or exporting to_csv, the values in the columns with NaNs are quietly modified - integers become floats. I believe this is a bug because I would expect to_csv to produce a csv file that is similar to printing the dataframe, without data types being changed. I cannot cast the dataframe to type Int64, since I have other types in the dataframe as well.

#### Expected Output

Instead of [nan True 5.0], I should get [nan True 5]

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

<details>

INSTALLED VERSIONS
------------------
commit           : d9fff2792bf16178d4e450fe7384244e50635733
python           : 3.7.8.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Sun Jul  5 00:43:10 PDT 2020; root:xnu-6153.141.1~9/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.0
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.1
setuptools       : 49.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.0
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
