title: Dropping NaN rows doesn't work in pandas
body: <p>I have a file with about 7k rows and 4 columns. A lot of the cells are empty and I have tried to drop them using a number of pandas functions but nothing seems to work. Functions I have tried and the code are below:</p>
  
  <p>What I have tried:</p>
  
  <pre><code>df = df.dropna(thresh=2) 
  </code></pre>
  
  <p>and</p>
  
  <pre><code>df.dropna(axis=0, how='all')
  </code></pre>
  
  <p>My code:</p>
  
  <pre><code>file = "pc-dirty-data.csv"
  path = root + file
  name_cols = ['GUID1', 'GUID2', 'Record ID', 'Name', 'Org Name', 'Title']
  pull_cols = ['Record ID', 'Name', 'Org Name', 'Title']
  df = df.dropna(thresh=2) 
  df.dropna(axis=0, how='all')
  df = pd.read_csv(path, header=None, encoding="ISO-8859-1", names=name_cols, usecols=pull_cols, index_col=False)
  df.info()
  </code></pre>
  
  <p>Dataframe:</p>
  
  <pre><code>RangeIndex: 6599 entries, 0 to 6598
  Data columns (total 4 columns):
  Record ID    5874 non-null float64
  Name         5874 non-null object
  Org Name     5852 non-null object
  Title        5615 non-null object
  dtypes: float64(1), object(3)
  </code></pre>