title: how to convert pandas Series of Numpy object into a Numpy matrix?
body: <p>I find it hard to convert pandas Series of size <code>M</code> each containing a numpy arrays each of size <code>N</code> into a matrix/numpy array/dataframe of size <code>MxN</code></p>
  
  <p>Example:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  from scipy import stats
  d = pd.DataFrame({'grp': np.random.randint(1, 10, 1000), 'x':np.random.rand(1000,)})
  s = d.groupby('grp')['x'].apply(lambda x: stats.gaussian_kde(x.values, bw_method = .01).evaluate(np.linspace(0,1,100)))
  </code></pre>
  
  <p>The output I get is of type Series where the type of the entries are numpy.ndarray.
  How do I convert this to be size of 10 (groups) times 100 (evaluation bins)?</p>