title: ValueError: could not convert string to float: ' '. Is Permutation importance only applicable for numeric features?
body: <p>I've a Data frame that contain dtypes as categorical, float, int.<br>
  X - contain features of all the three given dtypes and y is int.<br>
  I've created a pipline as given below.</p>
  
  <pre><code>get_imputer():
      imputing function
  
  get_encoder():
      some encoder function
  
  #model 
  
  pipeline = Pipeline(steps=[
          ('imputer', get_imputer()),
          ('encoder', get_encoder()),
          ('regressor', RandomForestRegressor())
      ])
  </code></pre>
  
  <p>I needed to find permutation importance of the model. below is the code for that.    </p>
  
  <pre><code>import eli5
  from eli5.sklearn import PermutationImportance
  perm = PermutationImportance(pipeline.steps[2][1], random_state=1).fit(X, y)
  eli5.show_weights(perm)
  </code></pre>
  
  <p>But this code is throwing an error as follows:  </p>
  
  <pre><code>ValueError: could not convert string to float: ''
  </code></pre>