BUG: pandas.DataFrame.compare causes loss of accuracy for big ints
- [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
# Your code here
import pandas as pd
left = pd.DataFrame({'a':[1567808378753000000], 'b':[0]})
right = pd.DataFrame({'a':[1567808378753274000], 'b':[0]})
print(left.compare(right))
```

#### Problem description
The current output is
```

                     a                     
                  self                other
0  1567808378752999936  1567808378753274112
```
which differs from the values in the original dataframe.
[this should explain **why** the current behaviour is a problem and why the expected output is a better solution]

#### Expected Output

                     a                     
                  self                other
0  1567808378753000000  1567808378753274000
#### Output of ``pd.show_versions()``
<details>

[paste the output of ``pd.show_versions()`` here leaving a blank line after the details tag]
INSTALLED VERSIONS
------------------
commit           : 7d32926db8f7541c356066dcadabf854487738de
python           : 3.8.7.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-1036-gcp
Version          : #39-Ubuntu SMP Thu Jan 14 18:41:17 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.2
numpy            : 1.20.1
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 49.2.1
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.22
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None
</details>
