title: Preserving the Custom Number Format when using read_excel() then converting to CSV with to_csv() with Pandas
body: <p>I've created a simple script that converts Excel files to CSV using Pandas. Here's the gist of my code:</p>
  <pre><code>read_file = pd.read_excel(excel_file)
  read_file.to_csv(csv_file, index=None, header=True, float_format='%.0f')
  </code></pre>
  <p>However, my issue is that the Excel file has several columns with dates, and the output in the CSV file is with the cell's literal value with the format mm/dd/yyyy. On the Excel file, a Custom Number Format has been applied to convert the dates to mmm yyyy format (e.g. 01/01/2001 becomes Jan 2001).</p>
  <p>I want to convert the Excel to CSV and have the date values stay in its Custom Number Format rather than the literal value in the cell. Is this possible?</p>
  <p>P.S. I know about adding a <code>date_format</code> in <code>to_csv()</code>, but I'd prefer keeping the Custom Number Format as this tool is going to be used in a number of different Excel files that may or may not contain their own Custom Number Formats. That's why I'm having a hard time.</p>