BUG:Dtypes changed from Int to Float when merging for different colunm names with Left_on Right_on outter join
- [ ] 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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#### Code Sample, a copy-pastable example

```python
#Different label names 'A' and 'a'
testa = pd.DataFrame([{"A":1,"b":2}])
testb = pd.DataFrame([{"a":2,"c":2}])
result = pd.merge(testa, testb, left_on='A', right_on='a', how="outer")
result.dtypes

Out[1]: 
A    float64
b    float64
a    float64
c    float64
dtype: object

#Same lable name with on[''] methond looks fine

testa = pd.DataFrame([{"a":1,"b":2}])
testb = pd.DataFrame([{"a":2,"c":2}])
result1 = pd.merge(testa, testb, on=["a"], how="outer")

result1.dtypes
Out[2]: 
a      int64
b    float64
c    float64
dtype: object
```

#### Problem description

I was merging some df with the zipcode, so I found this might be a problem. Maybe I am wrong about this, and probably pandas designed this way for some reasons? I don't know. If anyone knows the reasons why it had built this way, please share.
I also came across with this post: https://github.com/pandas-dev/pandas/issues/9958

#### Expected Output
I expecte there's no data type changes after merging.
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en
LOCALE           : None.None

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0.post20200210
Cython           : 0.29.15
pytest           : 5.3.5
hypothesis       : 5.5.4
sphinx           : 2.4.0
blosc            : None
feather          : None
xlsxwriter       : 1.2.7
lxml.etree       : 4.5.0
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.12.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : 1.3.2
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.1.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.3.5
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.13
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.7
numba            : 0.48.0

</details>
