BUG: Join changes dtypes
Hello,

#### Problem description

I have two pandas dataframes that I want to join using pandas (1.1.12).

However, when I join them, "alerts", in the table B gets its type changed from int64 to float64 ("alerts_cards"):

```python
(Pdb) A.dtypes
threshold_step      int64
precision         float64
alerts              int64
alerted_money     float64
dtype: object

(Pdb) B.dtypes
threshold_step      int64
precision         float64
alerts              int64
dtype: object

(Pdb) A.join(B, on="threshold_step", rsuffix="_cards", sort=True).dtypes
threshold_step            int64
precision               float64
alerts                    int64
alerted_money           float64
threshold_step_cards    float64
precision_cards         float64
alerts_cards            float64
dtype: object
```
I usually then remove the join key ("threshold_step_cards"), but now I'm noticing it became a float as well.

The join key column has the same entries in both tables (all integers in range 0 to 100) and there are no NaN's in my dataframes.

#### Expected Output

The join should preserve the datatypes of the original columns. I spent several hours looking for a bug in my code until with the debugger I found it came from this pandas join.

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python           : 3.7.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-118-generic
Version          : #119-Ubuntu SMP Tue Sep 8 12:30:01 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : pt_PT.UTF-8

pandas           : 1.1.2
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.2.0.post20200511
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.1
numexpr          : None
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.16
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : None

</details>

Thank you