title: Check if pandas dataframe date column is in correct date format or not?
body: <p>I have a dataframe having multiple columns. One of the column is having dates of format <code>(%m/%d/%Y)</code> or having null values. I have to apply a check to make sure that date column contains date in correct format (mentioned above). </p>
  
  <p>What I am trying to do is:</p>
  
  <pre><code>pd.to_datetime(df['DOB'], format='%m/%d/%Y', errors='coerce').all(skipna=True)
  </code></pre>
  
  <p>to check it has correct date format and empty values can be ignored, but I am getting this error, </p>
  
  <pre><code>TypeError: invalid_op() got an unexpected keyword argument 'skipna'
  </code></pre>
  
  <p>So, kindly let me know how to do it or what other logic I can apply ?</p>
  
  <p>EDIT 1:
  Suppose data having 3 DOBs and 1 null value:</p>
  
  <p><code>data = {"Name": ["James", "Alice", "Phil", "Jacob"],
              "DOB": ["07-01-1997", "06-02-1995", "", "03-07-2002"]}</code></p>
  
  <p>Modifying DOB column to convert date as per my format and replacing empty fields with NaN:</p>
  
  <p><code>df['DOB']=pd.to_datetime(df['DOB']).apply(lambda cell: cell.strftime(DATE_IN_MDY) if not pd.isnull(cell) else np.nan)</code></p>
  
  <p>And in this case I want result to be true.</p>