title: np.where() do nothing if condition fails
body: <p>I have a sample from my dataframe:</p>
  
  <pre><code>       Created      Insert Time   MatchKey              In Previous    New Type
  18593  2016-08-12   2018-02-19    LXGS090393APIN040640       No        New Existing
  5517   2016-08-12   2018-02-19    LIN380076CI166203726       No        New Existing
  2470   2018-02-12   2018-02-19    CI164414649APIN160672      No        New Existing
  13667  2016-08-12   2018-02-19    LIN257400APIN015446       Yes        New Existing
  10998  2016-08-12   2018-02-19    LXSV225786APIN158860      Yes        New Existing
  20149  2016-08-12   2018-02-19    LIN350167APIN158284       Yes        New Existing
  20143  2016-08-12   2018-02-19    LIN350167APIN161348       Yes        New Existing
  30252  2016-08-12   2018-02-19    LXGS120737APIN153339      Yes        New Existing
  12583  2016-08-09   2018-02-19    WIN556410APIN157186       Yes        New Existing
  28591  2018-05-03   2018-02-19    CI195705185APIN009076      No        New Created
  </code></pre>
  
  <p>I wanted to replace values in <strong>New Type</strong> column in a way that if the condition is failed the function does nothing:</p>
  
  <pre><code>current['New Type'] = np.where(current['In Previous']=='Yes','In Previous',pass)
  </code></pre>
  
  <p>but apparently it causes a syntax error as np.where() doesn't handle <strong>pass</strong>:</p>
  
  <pre><code>File "&lt;ipython-input-9-7f68cda12cbe&gt;", line 1
  current['New Type'] = np.where(current['In Previous']=='Yes','In Previous',pass)
  
                                                                            ^
  SyntaxError: invalid syntax
  </code></pre>
  
  <p>What would be an alternative to achieve the same?</p>