efficiently merge multiple dataframes in pandas
<p>What is the most efficient way to merge multiple data frames (i.e., more than 2) in pandas? There are a few answers:</p>

<ol>
<li><a href="https://stackoverflow.com/questions/23668427/pandas-joining-multiple-dataframes-on-columns">pandas joining multiple dataframes on columns</a></li>
<li><a href="https://stackoverflow.com/questions/21786490/pandas-left-outer-join-multiple-dataframes-on-multiple-columns">Pandas left outer join multiple dataframes on multiple columns</a></li>
</ol>

<p>but these all involve multiple joins. If I have N data frames these would require N-1 joins. </p>

<p>If I weren't using pandas, another solution would be to just put everything into a hash table based on the common index as the key and build the final version. This is basically like a hash join in SQL I believe. Is there something like that in pandas?</p>

<p>If not, would it be more efficient to just create a new data frame with the common index and pass it the raw data from each data frame? It seems like that would at least prevent you from creating a new data frame in each of the N-1 joins.</p>

<p>Thanks.</p>