title: Convert list of two dimensional DataFrame to Torch Tensor
body: <p><strong>Goal:</strong> I am working with RNNs in PyTorch, and my data is given by a list of DataFrames, where each DataFrame means one observation like:</p>
  
  <pre><code>import numpy as np
  data = [pd.DataFrame(np.zeros((5,50))) for x in range(100)]
  </code></pre>
  
  <p>which means 100 observation, with 50 parameters and 5 timesteps each. For my Model i need a tensor of shape <code>(100,5,50)</code>. </p>
  
  <p><strong>Issue:</strong> I tried a lot of things but nothing seems to work, does anyone know how this is done?
  This approaches doesn't work:</p>
  
  <pre><code>import torch
  torch.tensor(np.array(data))
  </code></pre>
  
  <p>I thing the problem is to convert the DataFrames into Arrays and the List into a Tensor at the same time.</p>