title: Python pandas Filtering out nan from a data selection of a column of strings
body: <p>Without using <code>groupby</code> how would I filter out data without <code>NaN</code>?</p>
  <p>Let say I have a matrix where customers will fill in <code>'N/A','n/a'</code> or any of its variations and others leave it blank:</p>
  <pre><code>import pandas as pd
  import numpy as np
  
  
  df = pd.DataFrame({'movie': ['thg', 'thg', 'mol', 'mol', 'lob', 'lob'],
                    'rating': [3., 4., 5., np.nan, np.nan, np.nan],
                    'name': ['John', np.nan, 'N/A', 'Graham', np.nan, np.nan]})
  
  nbs = df['name'].str.extract('^(N/A|NA|na|n/a)')
  nms=df[(df['name'] != nbs) ]
  </code></pre>
  <p>output:</p>
  <pre><code>&gt;&gt;&gt; nms
    movie    name  rating
  0   thg    John       3
  1   thg     NaN       4
  3   mol  Graham     NaN
  4   lob     NaN     NaN
  5   lob     NaN     NaN
  </code></pre>
  <p>How would I filter out <code>NaN</code> values so I can get results to work with like this:</p>
  <pre><code>  movie    name  rating
  0   thg    John       3
  3   mol  Graham     NaN
  </code></pre>
  <p>I am guessing I need something like <code>~np.isnan</code> but the tilda does not work with strings.</p>