title: df.append is creating new columns instead of appending to existing ones
body: <p>im writing a program that calculates that creates a data frame from two variables that are calculated every minute as part of a loop. </p>
  
  <p>Here I created the initial entry to the dataframe:</p>
  
  <pre><code>columnsMA = ['Time', 'Fast MA:', 'Slow MA:']
  dfMA = pd.DataFrame([[datetime.now().strftime("%m/%d/%Y, %H: %M"), 
                        fastMA, slowMA]], columns=columnsMA)
  </code></pre>
  
  <p>Here is correct output for this first minute:</p>
  
  <pre><code>                 Time  Fast MA:  Slow MA:
  0  03/05/2019, 21: 40   3827.75    3826.9
  </code></pre>
  
  <p>A minute later I am appending the new minute's calculations of fast MA and Slow MA with these lines:</p>
  
  <pre><code>    seriesMA = [[datetime.now().strftime("%m/%d/%Y, %H: %M"), fastMA, 
                   slowMA]]
      dfMA = dfMA.append(seriesMA, ignore_index=True)
  </code></pre>
  
  <p>But the output after this is:</p>
  
  <pre><code>                    0       1       2  Fast MA:  Slow MA:                Time
  0                 NaN     NaN     NaN   3827.75    3826.9  03/05/2019, 21: 40
  1            03/05/2019, 21: 41  3828.5  3827.4       NaN       NaN                 NaN
  </code></pre>
  
  <p>I cannot figure out how to get this to stop appending to new columns instead of after the existing ones. If you can help thanks so much!</p>