nal(m.values, np.nan)

    tmp = pd.DataFrame([(a, b) for a, b in list(zip(list(m), np.nanmean(m, axis=1)))],
                       columns=[alternative, &#34;value&#34;])
    if show_rank:
        tmp = __set_rank(tmp)

    return tmp</code></pre>
</details>
</dd>
</dl>
</section>
<section>
</section>
</article>
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<li><h3>Super-module</h3>
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<li><code><a title="comchoice.aggregate" href="index.html">comchoice.aggregate</