BUG: `read_excel` function auto-fills `NaN` values in index-columns with recent not-NaN values in the column
- [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
>>> # Notice for col2 cells are populated for rows 2,3 & 5, where as they are emply in the excel file and csv file
>>> pd.read_excel("test.xlsx", index_col=[0,1]) 
           data
col1 col2
1    2        5
2    2       10
3    2       15
4    8       20
5    8       25
6    12      30

>>> # Notice how read_csv works correctly and has NaN in col2 for rows 2,3 & 5
>>> pd.read_csv("test.csv", index_col=[0,1]) 
           data
col1 col2
1    2.0      5
2    NaN     10
3    NaN     15
4    8.0     20
5    NaN     25
6    12.0    30

>>> pd.read_excel("test.xlsx", index_col=[0,1], engine="xlrd") # same issue with 'xlrd' engine
           data
col1 col2
1    2        5
2    2       10
3    2       15
4    8       20
5    8       25
6    12      30

>>> pd.read_excel("test.xlsx", index_col=[0,1], engine="openpyxl") # same issue with 'openpyxl' engine
           data
col1 col2
1    2        5
2    2       10
3    2       15
4    8       20
5    8       25
6    12      30
```

#### Problem description

The `read_excel` function auto-fills `NaN` values in index columns with prev not `NaN` values. where as `read_csv` funtion works correctly.

Here is a screenshot of the excel file
![Annotation 2020-06-21 202246](https://user-images.githubusercontent.com/850012/85227780-0b8b5580-b3fd-11ea-9d55-84bd733f5321.png)


Here are the two test files in one zip archive. [test.zip](https://github.com/pandas-dev/pandas/files/4809648/test.zip)


#### Expected Output

The `NaN` cells should be left untouched as correctly read by `read_csv`.

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

<details>

```

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.3.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_India.1252

pandas           : 1.0.4
numpy            : 1.18.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.3.0.post20200616
Cython           : 0.29.20
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.15.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : 0.15.1
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : 3.6.1
tabulate         : None
xarray           : 0.15.1
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.9
numba            : 0.49.1
```

</details>
