Converting a pandas multi-index series to a dataframe by using second index as columns : <p>Hi I have a DataFrame/Series with 2-level multi-index and one column. I would like to take the second-level index and use it as a column. For example (code taken from <a href="https://pandas.pydata.org/pandas-docs/stable/advanced.html#creating-a-multiindex-hierarchical-index-object" rel="noreferrer">multi-index docs</a>):</p>

<pre><code>import pandas as pd
import numpy as np

arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
          ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
tuples = list(zip(*arrays))
index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
s = pd.DataFrame(np.random.randn(8), index=index, columns=["col"])
</code></pre>

<p>Which looks like:</p>

<pre><code>first  second
bar    one      -0.982656
       two      -0.078237
baz    one      -0.345640
       two      -0.160661
foo    one      -0.605568
       two      -0.140384
qux    one       1.434702
       two      -1.065408
dtype: float64
</code></pre>

<p>What I would like is to have a DataFrame with index <code>[bar, baz, foo, qux]</code> and columns <code>[one, two]</code>.</p>
