title: How to plot heatmap for high-dimensional dataset?
body: <p>I would greatly appreciate if you could let me know how to plot high-resolution heatmap for a large dataset with approximately 150 features. </p>
  
  <p>My code is as follows: </p>
  
  <pre><code>XX = pd.read_csv('Financial Distress.csv')
  
  y = np.array(XX['Financial Distress'].values.tolist())
  y = np.array([0 if i &gt; -0.50 else 1 for i in y])
  XX = XX.iloc[:, 3:87]
  df=XX
  df["target_var"]=y.tolist()
  target_var=["target_var"]
  
  fig, ax = plt.subplots(figsize=(8, 6))
  correlation = df.select_dtypes(include=['float64',
                                               'int64']).iloc[:, 1:].corr()
  sns.heatmap(correlation, ax=ax, vmax=1, square=True)
  plt.xticks(rotation=90)
  plt.yticks(rotation=360)
  plt.title('Correlation matrix')
  plt.tight_layout()
  plt.show()
  k = df.shape[1]  # number of variables for heatmap
  fig, ax = plt.subplots(figsize=(9, 9))
  corrmat = df.corr()
  # Generate a mask for the upper triangle
  mask = np.zeros_like(corrmat, dtype=np.bool)
  mask[np.triu_indices_from(mask)] = True
  cols = corrmat.nlargest(k, target_var)[target_var].index
  cm = np.corrcoef(df[cols].values.T)
  sns.set(font_scale=1.0)
  hm = sns.heatmap(cm, mask=mask, cbar=True, annot=True,
                   square=True, fmt='.2f', annot_kws={'size': 7},
                   yticklabels=cols.values,
                   xticklabels=cols.
                   values)
  plt.xticks(rotation=90)
  plt.yticks(rotation=360)
  plt.title('Annotated heatmap matrix')
  plt.tight_layout()
  plt.show()
  </code></pre>
  
  <p>It works fine but the plotted heatmap for a dataset with more than 40 features is too small.
  <a href="https://i.stack.imgur.com/A3Vrj.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/A3Vrj.jpg" alt="enter image description here"></a></p>
  
  <p>Thanks in advance,</p>