ENH: Implement skiptrailingspace parameter for the read_table function
#### Is your feature request related to a problem?

I had to do several additional manual data cleaning steps to parse certain markdown tables using the read_table function. The most cumbersome was not having an option to strip trailing spaces between values and separators. See mock code example at the end of this description.

#### Describe the solution you'd like

I would like the read_table function to have a skiptrailingspace boolean parameter that would automatically strip trailing whitespace in the same way the skipinitialspace parameter enables stripping leading whitespace.

#### API breaking implications

It would involve adding a new named parameter to read_table - so if users were calling with positional arguments it would be a breaking change if it wasn't made the last argument to the function.

#### Describe alternatives you've considered

Manual data cleaning is tolerable but more onerous. Another alternative that would be ideal from my perspective would be a read_markdown function that could extract indexed tables from markdown text in the same way the read_html function does for html. I suppose a related alternative is to use another Python package to render the markdown then use read_html but that is also onerous.

#### Additional context

See code example below for my current manual work-around.

```python
import pandas as pd
import io

annoying_table = """
| Heading 1 | Heading 2 | Heading 3 |
| --------- | --------- | --------- |
|      3.14 | cat       | 72        |
|        42 | mat       | 87.3      |
|   1234.56 | rat       | 128       |"""

df = (
    pd.read_table(
        filepath_or_buffer=io.StringIO(annoying_table),
        sep="|",
        skipinitialspace=True,
        # Would like a skiptrailingspace=True too
        skiprows=[2],
    )
    .convert_dtypes()
    .iloc[:, 1:-1]
)

df.columns = df.columns.str.strip()
print(df)

print(df.loc[0,"Heading 2"]) # output "cat       "

# Hacky work-around to strip trailing spaces
for column in df.select_dtypes("string").columns:
    df[column] = df[column].str.strip()

print(df.loc[0,"Heading 2"]) # output "cat"
```
