title: Split, apply, and combine multiple data frames into one data frame
body: <p>I have completed an origin-destination cost matrix (23 origins, ~600,000 destinations) for traveling through a street network in ArcGIS and disaggregated the resulting matrix into DBF tables by store ID using a Python script. I have loaded each DBF table into an R session as follows:</p>
  
  <pre><code># Import OD cost matrix results for each store
  origins &lt;- read.dbf('ODM_origins.dbf')
  store_17318 &lt;- read.dbf('table_17318.dbf')
  store_17358 &lt;- read.dbf('table_17358.dbf')
  store_17601 &lt;- read.dbf('table_17601.dbf')
  store_17771 &lt;- read.dbf('table_17771.dbf')
  store_18068 &lt;- read.dbf('table_18068.dbf')
  store_18261 &lt;- read.dbf('table_18261.dbf')
  store_18289 &lt;- read.dbf('table_18289.dbf')
  store_18329 &lt;- read.dbf('table_18329.dbf')
  store_18393 &lt;- read.dbf('table_18393.dbf')
  store_18503 &lt;- read.dbf('table_18503.dbf')
  store_18522 &lt;- read.dbf('table_18522.dbf')
  store_19325 &lt;- read.dbf('table_19325.dbf')
  store_19454 &lt;- read.dbf('table_19454.dbf')
  store_20068 &lt;- read.dbf('table_20068.dbf')
  store_20238 &lt;- read.dbf('table_20238.dbf')
  store_20292 &lt;- read.dbf('table_20292.dbf')
  store_20435 &lt;- read.dbf('table_20435.dbf')
  store_20465 &lt;- read.dbf('table_20465.dbf')
  store_20999 &lt;- read.dbf('table_20999.dbf')
  store_22686 &lt;- read.dbf('table_22686.dbf')
  store_22715 &lt;- read.dbf('table_22715.dbf')
  store_24445 &lt;- read.dbf('table_24445.dbf')
  store_24446 &lt;- read.dbf('table_24446.dbf')
  ID &lt;- as.vector(origins$Name) # Create list of store IDs
  object_list &lt;- list(ls(pat="store_")) # Create list of DBF object names
  </code></pre>
  
  <p>Here's the layout of every data frame:</p>
  
  <pre><code>&gt; head(store_17318)
    OID_          NAME ORIGINID DESTINATIO DESTINAT_1 TOTAL_TRAV SHAPE_LENG
  1    0 17318 - 17318       25       5367          1  0.2056914   202.2393
  2    0 17318 - 17318       25       5368          2  0.2056914   202.2393
  3    0 17318 - 17318       25       5381          5  0.2432538   224.3947
  4    0 17318 - 17318       25       5382          6  0.2432538   224.3947
  5    0 17318 - 17318       25       5362          7  0.3670772   294.8987
  6    0 17318 - 17318       25       5363          8  0.3670772   294.8987
  </code></pre>
  
  <p>For every data frame, I would like to find the summary statistics (mean, SD) for travel time by store ID and write it to a new data frame. This seems like a standard split, apply, combine workflow but it involves splitting multiple objects. Any help with this problem would be appreciated.</p>