title: Pandas fillna() not working as expected
body: <p>I'm trying to replace NaN values in my dataframe with means from the same row.</p>
  
  <pre><code>sample_df = pd.DataFrame({'A':[1.0,np.nan,5.0],
                     'B':[1.0,4.0,5.0],
                     'C':[1.0,1.0,4.0],
                     'D':[6.0,5.0,5.0],
                     'E':[1.0,1.0,4.0],
                     'F':[1.0,np.nan,4.0]})
  
  sample_mean = sample_df.apply(lambda x: np.mean(x.dropna().values.tolist()) ,axis=1)
  </code></pre>
  
  <p>Produces:</p>
  
  <pre><code>0    1.833333
  1    2.750000
  2    4.500000
  dtype: float64
  </code></pre>
  
  <p>But when I try to use <code>fillna()</code> to fill the missing dataframe values with values from the series, it doesn't seem to work.</p>
  
  <pre><code>sample_df.fillna(sample_mean, inplace=True)
  
      A     B     C     D     E     F
  0   1.0   1.0   1.0   6.0   1.0   1.0
  1   NaN   4.0   1.0   5.0   1.0   NaN
  2   5.0   5.0   4.0   5.0   4.0   4.0
  </code></pre>
  
  <p>What I expect is:</p>
  
  <pre><code>    A     B     C     D     E     F
  0   1.0   1.0   1.0   6.0   1.0   1.0
  1   2.75  4.0   1.0   5.0   1.0   2.75
  2   5.0   5.0   4.0   5.0   4.0   4.0
  </code></pre>
  
  <p>I've reviewed the other similar questions and can't seem to uncover the issue. Thanks in advance for your help.</p>