title: How to use np.where on list of Python objects to return inner objects matching condition?
body: <p>Trying to further master Python, I am struggling to implement what seems like a basic search task over a list in vectorized numpy.</p>
  
  <p>I have a list of dictionaries, and I want to select those dictionaries that have a certain key:value pair, which will be my truth condition. My intuition is to use <code>np.where</code> on the list, since this function gives back members of a list that match a specific condition. But <code>np.where</code> seemingly does not allow specifying any inner attributes/sublists of a member of the list.</p>
  
  <p>For example, the following code gives me a <code>TypeError</code> for the list indices,</p>
  
  <pre><code>dictionaries = [{'name':'Koko', 'value':1},
                  {'name':'Sam', 'value':2},
                  {'name':'Mike', 'value':3},
                  {'name':'Bob', 'value':4},
                  {'name':'Alex', 'value':5}]
  
  names_to_check = ['Koko', 'Bob']
  
  search_results = np.where(dictionaries['name'] in names_to_check)
  </code></pre>
  
  <p>I know I could always make a <code>for loop</code> to handle this problem manually.</p>
  
  <p>Am I right in using <code>np.where</code> here, or is there some better way to vectorize this task?</p>