title: Appending row to Pandas DataFrame adds 0 column
body: <p>I'm creating a Pandas DataFrame to store data. Unfortunately, I can't know the number of rows of data that I'll have ahead  of time. So my approach has been the following.</p>
  
  <p>First, I declare an empty DataFrame.</p>
  
  <pre><code>df = DataFrame(columns=['col1', 'col2'])
  </code></pre>
  
  <p>Then, I append a row of missing values.</p>
  
  <pre><code>df = df.append([None] * 2, ignore_index=True)
  </code></pre>
  
  <p>Finally, I can insert values into this DataFrame one cell at a time. (Why I have to do this one cell at a time is a long story.)</p>
  
  <pre><code>df['col1'][0] = 3.28
  </code></pre>
  
  <p>This approach works perfectly fine, with the exception that the append statement inserts an additional column to my DataFrame. At the end of the process the output I see when I type <code>df</code> looks like this (with 100 rows of data).</p>
  
  <pre><code>&lt;class 'pandas.core.frame.DataFrame'&gt;
  Data columns (total 2 columns):
  0            0  non-null values
  col1         100  non-null values
  col2         100  non-null values
  </code></pre>
  
  <p><code>df.head()</code> looks like this.</p>
  
  <pre><code>      0   col1   col2
  0  None   3.28      1
  1  None      1      0
  2  None      1      0
  3  None      1      0
  4  None      1      1
  </code></pre>
  
  <p><strong>Any thoughts on what is causing this <code>0</code> column to appear in my DataFrame?</strong></p>