title: pandas mean function returning NaN
body: <p>I know this may be a newbie question, so please forgive me, but I have not found an answer which seems to make sense to/help me. I am importing data from a .csv file and need to slice out a particular part. I have done that and when I print the data frame and all values I need are present.</p>
  
  <pre><code>    df = pd.read_csv('C:/Users/Owner/Desktop/df.csv')
      dfr = df[44:58] #rows I need
      dfrc = dfr[['1','2','3','4','5']] #columns I need
      dfrc.mean(axis=1 skipna=True) #there are some NaNs present in the last index
  </code></pre>
  
  <p>What is returned </p>
  
  <pre><code>    44   NaN
      ...
      57   NaN
      dtype: float64
  </code></pre>
  
  <p>I am not sure why that is, but I need the numerical value for the mean of the index/row. I was hoping someone on the forum would be able to help. Thank you. </p>