title: Fastest way to copy columns from one DataFrame to another using pandas?
body: <p>I have a large DataFrame (million +) records I'm using to store core of my data (like a database) and I then have a smaller DataFrame (1 to 2000) records that I'm combining a few of the columns for each time step in my program which can be several thousand time steps .  Both DataFrames are indexed the same way by a id column.</p>
  
  <p>the code I'm using is:</p>
  
  <pre><code>df_large.loc[new_ids, core_cols] = df_small.loc[new_ids, core_cols]
  </code></pre>
  
  <p>Where core_cols is a list of about 10 fields that I'm coping over and new_ids are the ids from the small DataFrame.  This code works fine but it is the slowest part of my code my a magnitude of three. I just wanted to know if they was a faster way to merge the data of the two DataFrame together.</p>
  
  <p>I tried merging the data each time with the merge function but process took way to long that is way I have gone to creating a larger DataFrame that I update to improve the speed.</p>