title: Pandas mean function returns all NaN
body: <p>I have this dataframe:</p>
  
  <pre><code>df = [{'A1':10, 'A2':''}, {'A1':11,'A2':110}, {'A1':12,'A2':120}]
  </code></pre>
  
  <p>And I'd like to average the different columns ignoring the '' (empty string) values.</p>
  
  <p>This is the desired output</p>
  
  <pre><code>df_AVG = [{'A1':10, 'A2':'','avg':10}, {'A1':11,'A2':110,'avg': 60.5}, {'A1':12,'A2':120,'avg':66}]
  </code></pre>
  
  <p>And I can do it with this code:</p>
  
  <pre><code>df['avg'] = df[['A1','A2']].mean(axis=1, numeric_only=True)
  </code></pre>
  
  <p>But when I modify the dataframe and it includes <strong>more than one</strong> blank space, like this</p>
  
  <pre><code>df = [{'A1':10, 'A2':''}, {'A1':'','A2':110}, {'A1':12,'A2':120}]
  </code></pre>
  
  <p>And I run the same code, the output is this. All 'avg' values are NaN, including the ones that previously worked:</p>
  
  <pre><code>df_AVG = [{'A1':10, 'A2':'','avg':NaN}, {'A1':11,'A2':110,'avg': NaN}, {'A1':12,'A2':120,'avg':NaN}]
  </code></pre>
  
  <p>Could you tell me what's wrong with this approach? Thanks!</p>