title: How to work around Python Pandas DataFrame's "Out of bounds nanosecond timestamp" error?
body: <p>The following code throws an "<code>Out of bounds nanosecond timestamp: 1452-04-15 00:00:00
  </code>" error. The same code works if I replace the date strings to some recent dates such as 2017-01-01. </p>
  
  <pre><code>df=pd.DataFrame({'Date':np.arange('1452-04-15', '1519-05-02', dtype='datetime64[D]')})
  </code></pre>
  
  <p>This example code is for providing an easy way to reproduce the error. What I am really trying to get done is to read a csv containing very early dates like these into a dataframe, and to convert the string dates into np.datetime64[D] or any comparable date format.</p>