title: How to plot a vertical line on a time series axis?
body: <p>I would like to 'link' two pieces of code. One,</p>
  <pre><code>x= df[df['Value']==True].sort_values(by='Date').head(1).Date
  
  Out[111]:
  8    2020-03-04
  </code></pre>
  <p>extracts the date where the first value appears; the other one</p>
  <pre><code>df[df['Buy']==1].groupby('Date').size().plot(ax=ax, label='Buy')
  </code></pre>
  <p>should plot some information through time.</p>
  <p>I would like to add a vertical line at the first date where the value is true, i.e. <code>2020-03-04</code>. In order to do it, I would need to extract this information from the first code (not using copy and paste) to the other piece of code which generates the plot.
  Can you give me some guide on how to do it? Thanks a lot</p>
  <p>Update:</p>
  <p>I tried as follows:</p>
  <pre><code>x= df[df['Value']==True].sort_values(by='Date').head(1).Date.tolist()
  
  Out[111]:
  8    ['2020-03-04']
  
  df[df['Buy']==1].groupby('Date').size().plot(ax=ax, label='Buy')
  
  ax.axvline(x, color=&quot;red&quot;, linestyle=&quot;--&quot;)
  </code></pre>
  <p>but I got a TypeError: unhashable type: 'numpy.ndarray'</p>
  <p>Some data:</p>
  <pre><code>Date           Buy      Value
  0   2020-02-23  0   False
  1   2020-02-23  0   False
  2   2020-02-25  0   False
  3   2020-02-27  1   False
  4   2020-03-03  1   False
  5   2020-03-03  1   False
  6   2020-03-03  0   False
  7   2020-03-04  1   False
  8   2020-03-04  0   True
  9   2020-03-04  0   True
  10  2020-03-04  1   False
  11  2020-03-05  0   True
  12  2020-03-05  1   False
  13  2020-03-05  1   False
  14  2020-03-05  1   False
  15  2020-03-06  0   False
  16  2020-03-06  1   False
  17  2020-03-06  1   False
  18  2020-03-07  1   False
  19  2020-03-07  1   False
  20  2020-03-07  1   False
  21  2020-03-08  1   False
  22  2020-03-08  1   False
  23  2020-03-09  1   False
  24  2020-03-09  1   False
  25  2020-03-09  1   False
  26  2020-03-10  1   False
  27  2020-03-10  1   False
  28  2020-03-10  1   False
  29  2020-03-10  0   True
  30  2020-03-11  1   False
  31  2020-03-11  1   False
  32  2020-03-13  0   True
  33  2020-03-13  0   False
  34  2020-03-15  0   True
  35  2020-03-16  0   False
  36  2020-03-19  0   False
  37  2020-03-22  0   True
  </code></pre>