title: DataFrame columns being dropped when data is inserted
body: <p>I'm trying to create a DataFrame with 3 columns, but for some reason - only one column is being added:</p>
  
  <pre><code># Create a new DataFrame from our transformed data
  stock_incident_df = pd.DataFrame(stock_incident_data, columns=['date', 'number_of_incidents', 'stock_price_close'])
  print(stock_incident_df.describe())
  
         number_of_incidents
  count          1551.000000
  mean            154.629916
  std              25.782985
  min              77.000000
  25%             137.000000
  50%             154.000000
  75%             171.000000
  max             342.000000
  </code></pre>
  
  <p>Even if I separate the constructor and appending the data, the issue comes up: </p>
  
  <pre><code>stock_incident_df = pd.DataFrame(columns=['date', 'number_of_incidents', 'stock_price_close'])
  
  print(stock_incident_df.describe())
  
  stock_incident_df = stock_incident_df.append(stock_incident_data)
  
  print(stock_incident_df.describe())
  
         date number_of_incidents stock_price_close
  count     0                   0                 0
  unique    0                   0                 0
  top     NaN                 NaN               NaN
  freq    NaN                 NaN               NaN
                   1
  count  1551.000000
  mean    154.629916
  std      25.782985
  min      77.000000
  25%     137.000000
  50%     154.000000
  75%     171.000000
  max     342.000000
  </code></pre>
  
  <p>My input data is a list of lists with the following format:</p>
  
  <pre><code>[
    [Timestamp('2014-01-02 00:00:00'), 119, 16441.35],
    [Timestamp('2014-01-03 00:00:00'), 124, 16469.99],
    [Timestamp('2014-01-06 00:00:00'), 100, 16425.11], 
    [Timestamp('2014-01-07 00:00:00'), 115, 16530.94]
  ]
  </code></pre>