title: most efficient method to extract key: value pairs from a pandas column and use the keys as columns
body: <p>I have a large data set, 50000 or so csv's containing about 40000 lines, that I need to read into dataframes, extract the key: value pairs and use them as columns/values in the same dataframe. The excerpt below is a single column of my pandas dataframe:</p>
  
  <pre><code>column 
  'this is my string of data., you can:  parse me now, but:  you will never find me'
  'this is some crazy data., where are:  you at today?, you can:  never find me, but:  this is fun.' 
  'this is more crazy than ever, where are:, you can:  not parse me, strange:  stuff'
  </code></pre>
  
  <p>How can I extract just the key: value pairs that match the following criteria? I am trying to do this in the most efficient method due to the iteration over multiple files. </p>
  
  <pre><code>between two commas
  must contain a colon
  two spaces after the colon
  any character to include spaces
  </code></pre>
  
  <p>With an expected output of expanding the keys to columns and values in the columns: </p>
  
  <pre><code>you can          but                      where are      strange     &lt;==columns
  parse me now     you will never find me   NONE           NONE
  never find me    this is fun              you at today?  NONE
  not parse me     NONE                     NONE           stuff
  </code></pre>
  
  <p>Updated visual of data.</p>
  
  <pre><code>                                 1
    0                               
  0  subject                     NaN
    strange sub                AcDe1
    strange name               i001$
    stuff and things           86753
    newby id                      09
  </code></pre>