title: Remove any row with empty columns
body: <p>I have a CSV that looks like:</p>
  
  <pre><code>0             Local ID                  Sample ID   Rev Code 
  1                    4                       2949  GGTAGTGTGTATCAGTACATG
  50                 441                       1057  GGTAGAGACACGAGTCTAGAT
  51                                                                      
  52                                                                      
  53                                                                      
  54                                                                      
  </code></pre>
  
  <p>And I use the following to convert this into a dataframe:</p>
  
  <pre class="lang-py prettyprint-override"><code>reader = csv.DictReader(csv_to_use.splitlines())
  rows = [r for r in reader]
  df = pd.DataFrame(rows)
  </code></pre>
  
  <p>How can drop the rows where other columns are empty?</p>
  
  <p>I have tried doing <code>df.dropna(subset=['Rev Code'], inplace=True)</code> but it returns</p>
  
  <pre class="lang-py prettyprint-override"><code>Traceback (most recent call last):
    File "&lt;stdin&gt;", line 1, in &lt;module&gt;
    File "/Users/daudn/Documents/clean_space/env_tgs/lib/python3.7/site-packages/pandas/core/frame.py", line 4859, in dropna
      raise KeyError(list(np.compress(check, subset)))
  </code></pre>
  
  <p>How could I implement this?</p>