title: Incremental addition of dictionary values to a pandas DataFrame. DataFrame with column names of dict keys
body: <p>Suppose I have a dict and create a pandas DataFrame as </p>
  
  <pre><code>dict = {'a':1,'b':2,'c':3}
  df = pd.DataFrame(columns = ['a','b','c'])
  </code></pre>
  
  <p>Every time I create a new dict with same keys I need to add the values as a row to <code>df</code>. Initially, <code>df</code> has no rows and no index assigned. What I am aware of is using </p>
  
  <pre><code>df.append(pd.Series(), ignore_index=True)
  </code></pre>
  
  <p>But, this keeps adding columns. Also, since dictionaries don't carry an order, would hard coding something like <code>list(dict.values())</code> randomize the order prior to inserting, the created list as a row to <code>df</code>, especially when I keep updating the <code>dict</code>?</p>