title: How To Solve KeyError: u"None of [Index([..], dtype='object')] are in the [columns]"
body: <p>I'm trying to create a SVM model from what I found in github <a href="https://github.com/reshu-b7/Sign-Language-Glove" rel="noreferrer">here</a>, but it keeps returning this error.</p>
  
  <pre><code>Traceback (most recent call last):
    File "C:\Users\Me\Documents\#e\projects\Sign-Language-Glove-master\modeling.py", line 22, in &lt;module&gt;
      train_features = train[['F1','F2','F3','F4','F5','X','Y','Z','C1','C2']]
    File "C:\Python27\lib\site-packages\pandas\core\frame.py", line 2934, in __getitem__
      raise_missing=True)
    File "C:\Python27\lib\site-packages\pandas\core\indexing.py", line 1354, in _convert_to_indexer
      return self._get_listlike_indexer(obj, axis, **kwargs)[1]
    File "C:\Python27\lib\site-packages\pandas\core\indexing.py", line 1161, in _get_listlike_indexer
      raise_missing=raise_missing)
    File "C:\Python27\lib\site-packages\pandas\core\indexing.py", line 1246, in _validate_read_indexer
      key=key, axis=self.obj._get_axis_name(axis)))
  KeyError: u"None of [Index([u'F1', u'F2', u'F3', u'F4', u'F5', u'X', u'Y', u'Z', u'C1', u'C2'], dtype='object')] are in the [columns]"
  </code></pre>
  
  <p>This is my code.</p>
  
  <pre><code>import pandas as pd
  dataframe= pd.read_csv("lettera.csv", delimiter=',')
  df=pd.DataFrame(dataframe)
  
  from sklearn.model_selection import train_test_split
  train, test = train_test_split(df, test_size = 0.2)
  
  train_features = train[['F1','F2','F3','F4','F5','X','Y','Z','C1','C2']]
  </code></pre>
  
  <p>And these are the contents of the csv file.</p>
  
  <pre><code>LABEL, F1, F2, F3, F4, F5, X, Y, Z, C1, C2
  
  1, 631, 761, 739, 751, 743, 14120, -5320, 7404, 0, 0
  
  1, 632, 759, 740, 751, 744, 14108, -5276, 7444, 0, 0
  
  1, 630, 761, 740, 752, 743, 14228, -5104, 7680, 0, 0
  
  1, 630, 761, 738, 750, 743, 14256, -5148, 7672, 0, 0
  
  1, 632, 759, 740, 751, 744, 14172, -5256, 7376, 0, 0
  
  1, 632, 759, 742, 751, 746, 14288, -5512, 7412, 0, 0
  
  1, 632, 759, 742, 751, 744, 14188, -5200, 7416, 0, 0
  
  1, 634, 759, 738, 751, 743, 14252, -5096, 7524, 0, 0
  
  1, 630, 759, 739, 751, 743, 14364, -5124, 7612, 0, 0
  
  1, 630, 759, 740, 751, 744, 14192, -5316, 7424, 0, 0
  
  1, 631, 760, 739, 752, 743, 14292, -5100, 7404, 0, 0
  
  1, 634, 759, 738, 751, 742, 14232, -5188, 7468, 0, 0
  
  1, 632, 759, 740, 751, 744, 14288, -5416, 7552, 0, 0
  
  1, 630, 760, 739, 752, 743, 14344, -5072, 7816, 0, 0
  
  1, 631, 760, 739, 752, 743, 14320, -4992, 7444, 0, 0
  
  1, 630, 762, 739, 751, 746, 14220, -5172, 7544, 0, 0
  
  1, 630, 759, 739, 751, 742, 14280, -5176, 7416, 0, 0
  
  1, 630, 760, 738, 752, 740, 14360, -5028, 7468, 0, 0
  
  1, 632, 759, 738, 752, 741, 14384, -5108, 7364, 0, 0
  
  1, 629, 757, 737, 751, 741, 14224, -5108, 7536, 0, 0
  
  1, 629, 758, 740, 751, 744, 14412, -5136, 7956, 0, 0
  
  1, 629, 761, 740, 750, 744, 14468, -4868, 7100, 0, 0
  
  1, 629, 760, 738, 752, 741, 14504, -4964, 6600, 0, 0
  
  1, 629, 758, 738, 749, 741, 14440, -5112, 6828, 0, 0
  
  1, 629, 760, 738, 752, 741, 14484, -5016, 7556, 0, 0
  </code></pre>
  
  <p>Thank you.</p>