title: Append a list of arrays as column to pandas Data Frame with same column indices
body: <p>I have a list of arrays (one-dimensional numpy array) (a_) and a list (l_) and want to have a DataFrame with them as its columns. They look like this:</p>
  
  <pre><code>a_: [array([381]), array([376]), array([402]), array([400])...]
  l_: [1.5,2.34,4.22,...]
  </code></pre>
  
  <p>I can do it by:</p>
  
  <blockquote>
  <pre><code>df_l = pd.DataFrame(l_)
  df_a = pd.DataFrame(a_)
  df = pd.concat([df_l, df_a], axis=1)
  </code></pre>
  </blockquote>
  
  <p>Is there a <strong>shorter</strong> way of doing it? I tried to use <code>pd.append</code>:</p>
  
  <blockquote>
  <pre><code>df_l = pd.DataFrame(l_)
  df_l = df_l.append(a_)
  </code></pre>
  </blockquote>
  
  <p>However, because columns indices are both 0, it adds a_ to the end of the dataframe column, resulting in a single column. Is there something like this:</p>
  
  <blockquote>
    <p><code>l_ = l_.append(a_).reset(columns)</code></p>
  </blockquote>
  
  <p>that set a new column index for the appended array? well, obviously this does not work!</p>
  
  <p>the desired output is like:</p>
  
  <blockquote>
  <pre><code>  0       0
  0 1.50    381
  1 2.34    376
  2 4.22    402 
  </code></pre>
    
    <p>...</p>
  </blockquote>
  
  <p>Thanks.</p>