title: Pandas read DataFrame with datetime columns from clipboard
body: <p>I see a lot of DataFrames posted to StackOverflow that look like:</p>
  
  <pre><code>          a                  dt         b
  0 -0.713356 2015-10-01 00:00:00 -0.159170
  1 -1.636397 2015-10-01 00:30:00 -1.038110
  2 -1.390117 2015-10-01 01:00:00 -1.124016
  </code></pre>
  
  <p>I still haven't figured out a good way to copy these into my interpreter using <a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_clipboard.html" rel="nofollow noreferrer"><code>.read_clipboard</code></a> (argument list in <a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_table.html#pandas.read_table" rel="nofollow noreferrer"><code>.read_table</code> docs</a>).</p>
  
  <p>I thought the key was the <code>parse_dates</code> parameter:</p>
  
  <pre><code>parse_dates : boolean or list of ints or names or list of lists or dict, default False
  * boolean. If True -&gt; try parsing the index.
  * list of ints or names. e.g. If [1, 2, 3] -&gt; try parsing columns 1, 2, 3 each as a separate date column.
  * list of lists. e.g. If [[1, 3]] -&gt; combine columns 1 and 3 and parse as a single date column.
  * dict, e.g. {‘foo’ : [1, 3]} -&gt; parse columns 1, 3 as date and call result ‘foo’
  </code></pre>
  
  <p><code>pd.read_clipboard(parse_dates={'dt': [1, 2]})</code> raises the exception <code>NotImplementedError: file structure not yet supported</code>.</p>
  
  <p>When I try skipping the first row <code>pd.read_clipboard(parse_dates=[[1, 2]], names=['a', 'dt1', 'dt2', 'b'], skiprows=1, header=None)</code> I get the same exception.</p>
  
  <p>How do others do this?</p>