title: How to replace None only with empty string using pandas?
body: <p>the code below generates a <em>df</em>:</p>
  
  <pre><code>import pandas as pd
  from datetime import datetime as dt
  import numpy as np
  
  dates = [dt(2014, 1, 2, 2), dt(2014, 1, 2, 3), dt(2014, 1, 2, 4), None]
  strings1 = ['A', 'B',None, 'C']
  strings2 = [None, 'B','C', 'C']
  strings3 = ['A', 'B','C', None]
  vals = [1.,2.,np.nan, 4.]
  df = pd.DataFrame(dict(zip(['A','B','C','D','E'],
                             [strings1, dates, strings2, strings3, vals])))
  
  
  
  +---+------+---------------------+------+------+-----+
  |   |  A   |          B          |  C   |  D   |  E  |
  +---+------+---------------------+------+------+-----+
  | 0 | A    | 2014-01-02 02:00:00 | None | A    | 1   |
  | 1 | B    | 2014-01-02 03:00:00 | B    | B    | 2   |
  | 2 | None | 2014-01-02 04:00:00 | C    | C    | NaN |
  | 3 | C    | NaT                 | C    | None | 4   |
  +---+------+---------------------+------+------+-----+
  </code></pre>
  
  <p>I would like to replace all <code>None</code> (real <code>None</code> in python, not str) inside with <code>''</code>(empty string).</p>
  
  <p>The <strong>expected</strong> <em>df</em> is</p>
  
  <pre><code>+---+---+---------------------+---+---+-----+
  |   | A |          B          | C | D |  E  |
  +---+---+---------------------+---+---+-----+
  | 0 | A | 2014-01-02 02:00:00 |   | A | 1   |
  | 1 | B | 2014-01-02 03:00:00 | B | B | 2   |
  | 2 |   | 2014-01-02 04:00:00 | C | C | NaN |
  | 3 | C | NaT                 | C |   | 4   |
  +---+---+---------------------+---+---+-----+
  </code></pre>
  
  <hr>
  
  <p>what I did is</p>
  
  <p><code>df = df.replace([None], [''], regex=True)</code></p>
  
  <p>But I got</p>
  
  <pre><code>+---+---+---------------------+---+------+---+
  |   | A |          B          | C |  D   | E |
  +---+---+---------------------+---+------+---+
  | 0 | A | 1388628000000000000 |   | A    | 1 |
  | 1 | B | 1388631600000000000 | B | B    | 2 |
  | 2 |   | 1388635200000000000 | C | C    |   |
  | 3 | C |                     | C |      | 4 |
  +---+---+---------------------+---+------+---+
  </code></pre>
  
  <hr>
  
  <ol>
  <li>all the dates becomes big numbers</li>
  <li>Even <code>NaT</code> and <code>NaN</code> are replaced, which I don't want.</li>
  </ol>
  
  <p>How can I achieve that correctly and efficently?</p>