ENH: Add option to keep index in `pd.melt`
When melting a dataframe, there's no option to keep the original index. This can be beneficial for example when users want to do different kind `ravel` than the  deault `F` (Fortran style) right now. To make this more clear, see example:

```python
df = pd.DataFrame({'A': [1, 4],
                   'B': [2, 5],
                   'C': [3, 6]})
print(df)
   A  B  C
0  1  2  3
1  4  5  6

print(df.melt())
  variable  value
0        A      1
1        A      4
2        B      2
3        B      5
4        C      3
5        C      6
```
But the expected output can be row wise instead:
```python
  variable  value
0        A      1
1        B      2
2        C      3
3        A      4
4        B      5
5        C      6
```

**Solution proposal**
This could be solved by adding an `ignore_index` argument which is `True` by default, but if it is set to `False`, the result would come out like:
```python
  variable  value
0        A      1
1        A      4
0        B      2
1        B      5
0        C      3
1        C      6
```
This way the user can sort the index themself and achieve the same result:
```python
print(df.sort_index())
  variable  value
0        A      1
0        B      2
0        C      3
1        A      4
1        B      5
1        C      6
```

Also in `pandas/core/reshape/melt` there is an `# TODO: what about the existing index?` in the `melt` function. This might solve that TODO if I'm not mistaken.
