pd.merge regression when doing a left-join with missing data on the right. Result has a Float64Index
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd

X = pd.DataFrame({ "count": [1, 2] }, index=["A", "B"])
Y = pd.DataFrame({"name": ["A", "C"], "value": [100, 200]})
Z = pd.merge(X, Y, left_index=True, right_on="name", how='left')
print(Z.to_string())
# in 0.23.4
#    count name  value
# 0      1    A  100.0
# 1      2    B    NaN

# in 0.24.2
#    count name  value
# 0      1    A  100.0
# 1      2    B    NaN

# in 0.25.1
#      count name  value
# 0.0      1    A  100.0
# NaN      2    B    NaN

assert isinstance(Z.index, pd.Int64Index)

```
#### Problem description

I looked on the GitHub tracker for similar issues but the closest I found was #24897. In previous versions of pandas it would return a Int64Index but now returns a Float64Index. I didn't see this behaviour documented in the release notes of 0.25, but please let me know if I've missed it. This bug is easy to reproduce in a virtualenv.

#### Expected Output

```
   count name  value
0      1    A  100.0
1      2    B    NaN
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.3.final.0
python-bits      : 64
OS               : Linux
OS-release       : 3.10.0-957.el7.x86_64
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           : 0.25.1
numpy            : 1.17.1
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 19.2.3
setuptools       : 41.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>
