title: Seaborn pairplot: data must have variance to compute a kernel density estimate
body: <p>I am trying to run this code below:</p>
  <pre class="lang-py prettyprint-override"><code>print(); print('Scatter Matrix Plot')
  sns.pairplot(dataset, hue = 'Protein', diag_kind=&quot;kde&quot;)
  plt.show()
  </code></pre>
  <p>where dataset is data read from a csv using <code>dataset = pd.read_csv(filename, sep = ',', names = col_names)</code>.</p>
  <p>I do not get a terminating error when I run this code, but instead I get a warning, which is &quot;<code>data must have variance to compute a kernel density estimate</code>&quot; and none of the plots have a kde curve through them. I have looked this up and found that this might be due to repeating data, but the only instances where solutions are documented are ones using the <code>kdeplot()</code> function, so I am at a loss.</p>