title: Easiest way to read csv files with multiprocessing in Pandas
body: <p>Here is my question.<br />
  With bunch of .csv files(or other files). Pandas is an easy way to read them and save into <code>Dataframe</code> format. But when the amount of files was huge, I want to read the files with multiprocessing to save some time.</p>
  <h3>My early attempt</h3>
  <p>I manually divide the files into different path. Using severally:</p>
  <pre class="lang-py prettyprint-override"><code>os.chdir(&quot;./task_1&quot;)
  files = os.listdir('.')
  files.sort()
  for file in files:
      filename,extname = os.path.splitext(file)
      if extname == '.csv':
          f = pd.read_csv(file)
          df = (f.VALUE.as_matrix()).reshape(75,90)   
  </code></pre>
  <p>And then combine them.</p>
  <p>How to run them with <code>pool</code> to achieve my problem?<br />
  Any advice would be appreciated!</p>