title: Concatenate (join) a NumPy array with a pandas DataFrame
body: <p>I have a pandas dataframe with 10 rows and 5 columns and a numpy matrix of zeros <code>np.zeros((10,3))</code>.</p>
  
  <p>I want to concat the numpy matrix to the pandas dataframe but I want to delete the last column from the pandas dataframe before concatenating the numpy array to it.</p>
  
  <p>So I will end up with a matrix of 10 rows and 5 - 1 + 3 = 7 columns.</p>
  
  <p>I guess I could use</p>
  
  <pre><code>new_dataframe = pd.concat([
      original_dataframe,
      pd.DataFrame(np.zeros((10, 3)), dtype=np.int)
  ], axis=1, ignore_index=True)
  </code></pre>
  
  <p>where <code>original_dataframe</code> has 10 rows and 5 columns.</p>
  
  <p>How do I delete the last column from <code>original_dataframe</code> before concatenating the numpy array? And how do I make sure I preserve all the data types?</p>