Is there a bug while slicing in the non monotonic multi indices?
Please take this question lightly as asked from curiosity:

<b>As</b> I was trying to see how the slicing in MultiIndex works, I came across the following situation ↓

```python
# Simple MultiIndex Creation
index = pd.MultiIndex.from_product([['a', 'c', 'b'], [1, 2]])

# Making Series with that MultiIndex
data = pd.Series(np.random.randint(10, size=6), index=index)
``` 
Returns:
<pre>
a  1    5
   2    0
c  1    8
   2    6
b  1    6
   2    3
dtype: int32
</pre>

**NOTE** that the indices are ***not*** in the sorted order ie. `a, c, b` is the order which will result in the ***expected*** error that we want while slicing.

```python
# When we do slicing
data.loc["a":"c"]
```
Errors like:
<pre>
UnsortedIndexError

----> 1 data.loc["a":"c"]
UnsortedIndexError: 'Key length (1) was greater than MultiIndex lexsort depth (0)'
</pre>

That's expected. But now, after doing the following steps:

```python
# Making a DataFrame
data = data.unstack()

# Redindexing - to unsort the indices like before
data = data.reindex(["a", "c", "b"])

# Which looks like 
   1  2
a  5  0
c  8  6
b  6  3

# Then again making series
data = data.stack()

# Reindex Again!
data = data.reindex(["a", "c", "b"], level=0)


# Which looks like before
a  1    5
   2    0
c  1    8
   2    6
b  1    6
   2    3
dtype: int32
```

### The Problem
So, now the process is: `Series → Unstack → DataFrame → Stack → Series`

Now, if I do the slicing like before *(still on with the indices unsorted)* we **don't get any error!**

```python
# The same slicing
data.loc["a":"c"]
```
Results without an error:
<pre>
a  1    5
   2    0
c  1    8
   2    6
dtype: int32
</pre>

**Even if** the `data.index.is_monotonic` → `False`. Then still why can we slice?

So the question is: **WHY?**. <br>
> I hope you got the understanding of the situation here. Because see, the same series which was before giving the error, after the `unstack` and `stack` operation is not giving any error.

So is that a bug, or a new concept that I am missing here?

Thanks!<br>
Aayush ∞ Shah