title: Problems using genfromtxt to input into scikit-learn fit function
body: <p>I am trying to genfromtxt to read in a csv file and then use RandomForestClassifier. I wind up having use genfromtxt twice;once to read in the features and then to get the proper format.
  The code for this attempt follows:
     import csv 
      import numpy as np</p>
  
  <pre><code>data = np.genfromtxt('plants.csv',dtype=float, delimiter=',', names=True)
  feature_names = np.array(data.dtype.names)
  feature_names = feature_names[[ 0,1,2,3,4]] 
  
  data = np.genfromtxt('plants.csv',dtype=float, delimiter=',', skip_header=1)
  plants_X = data[:, [0,1,2,3,4]] 
  _y = np.ravel(data[:,[5]]) #Return a flattened array required by scikit-learn fit for 2nd argument
  
  from sklearn.ensemble import RandomForestClassifier 
  clf = RandomForestClassifier( n_estimators = 10, random_state = 33)
  clf = clf.fit(plants_X, plants_y)
  
  print feature_names, '\n', clf.feature_importances_
  
  print feature_names, '\n', clf.feature_importances_
  </code></pre>
  
  <p>When I use genfromtxt with the "names=True option  "data" read in is not in the format I expected!</p>
  
  <p>" ([(31.194181, 0.0, 0.0, 0.0, 1.0, 1.0),
         (12.0, 0.0, 0.0, 1.0, 0.0, 1.0), (18.0, 1.0, 0.0, 1.0, 0.0, 0.0),
         (31.194181, 0.0, 0.0, 0.0, 1.0, 0.0)], 
         ...
        dtype=[('A', '
  
  <p>I want to get the feature names from the file without reading it twice!</p>
  
  <p>Thanks for your assistance!</p>
  
  <p>Ps: Thnaks to "Cyborg" I got this far!</p>