DOC: read_excel skiprows does not work as documented
#### Location of the documentation

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html


#### Documentation problem

Both, stable and dev documentations read

> **skiprows : _list-like, int, or callable, optional_**  
>     Line numbers to skip (0-indexed) or number of lines to skip (int) at the start of the file. 

but the phrase "number of lines to skip (int) at the start of the file" does not resemble the behavior that I observe.

Consider the demo [data.xlsx](https://github.com/pandas-dev/pandas/files/6680539/data.xlsx):
![data.xlsx preview](https://user-images.githubusercontent.com/12622691/122639255-389a4300-d0f9-11eb-9b4a-75aada22ada8.png)

Now, if I wanted to only read the highlighted cells containing 1,2,3 I would basically want to skip the first _5 lines at the start of the file_.

Based on the documentation I would then use `skiprows=5` (and `nrows=3`), but that is not how `skiprows` works:

```python
import pandas as pd
print( pd.read_excel( 'data.xlsx', engine='openpyxl', usecols='A', skiprows=0, names=['with skiprows=0:'] ) )
print( pd.read_excel( 'data.xlsx', engine='openpyxl', usecols='A', skiprows=2, names=['with skiprows=2:'] ) )
print( pd.read_excel( 'data.xlsx', engine='openpyxl', usecols='A', skiprows=5, names=['with skiprows=5:'] ) )
```
prints:
```
   with skiprows=0:
0                22
1                33
2                 1
3                 2
4                 3
5                 4
   with skiprows=2:
0                 1
1                 2
2                 3
3                 4
   with skiprows=5:
0                 2
1                 3
2                 4
```

pandas 1.0.4  
openpyxl 3.0.6

#### Suggested fix for documentation

Based on my observations I would suggest the following formulation:

> [...] or number of **non-empty** lines to skip (int) at the start of the file. 


#### NB

It would actually be helpful to get the documented behavior, i.e. being able to select rows based on the rows in the file (corresponding to the coordinates within the excel file).  
This is implemented for column selection via the `usecols` keyword but not for rows.
I am planning on opening a separate request to ask about that functionality.


#### _Update_

I just realized that it was the interference with the default `header=0` that confused me.
Of course, I would want to and should have included `header=None` in my example.

With `header=None` I get the the desired selection for `skiprows=5` (and also `skiprows=3` due to the empty cells)

```python
print( pd.read_excel( 'data.xlsx', engine='openpyxl', usecols='A', skiprows=0, header=None, names=['with skiprows=0:'] ) )
print( pd.read_excel( 'data.xlsx', engine='openpyxl', usecols='A', skiprows=3, header=None, names=['with skiprows=3:'] ) )
print( pd.read_excel( 'data.xlsx', engine='openpyxl', usecols='A', skiprows=5, header=None, names=['with skiprows=5:'] ) )
```
produces
```
   with skiprows=0:
0                11
1                22
2                33
3                 1
4                 2
5                 3
6                 4
   with skiprows=3:
0                 1
1                 2
2                 3
3                 4
   with skiprows=5:
0                 1
1                 2
2                 3
3                 4
```

 So the documentation is right.
