title: How to parse pandas timestamp where the milliseconds field is not zero padded?
body: <p>I have a pandas data frame with a timestamp column formatted as a string. The time variable has micro second level precision but with no zero padding. Below are some sample values of the timestamp.</p>
  <pre><code>2015-05-12 05:25:23.904 UTC
  2015-05-12 05:55:10.496544 UTC
  2015-05-18 15:10:44.295 UTC
  </code></pre>
  <p>I want to parse this column and have datetime formatting. I tried the following options as stated in other stackoverflow threads but none worked.</p>
  <pre><code>input_data['event_timestamp'] = pd.to_datetime(input_data['event_timestamp'], format=&quot;%Y-%m-%d %H:%M:%S.%-f %z&quot;)
  
  ValueError: '-' is a bad directive in format '%Y-%m-%d %H:%M:%S.%-f %z'
  </code></pre>
  <pre><code>input_data['event_timestamp'] = pd.to_datetime(input_data['event_timestamp'], format=&quot;%Y-%m-%d %H:%M:%S.%f %z&quot;)
  
  ValueError: time data '2015-05-12 05:25:23.904 UTC' does not match format '%Y-%m-%d %H:%M:%S.%f %z' (match)
  </code></pre>
  <p>How do I parse this variable to timestamp format?</p>