title: Setting the values from a row in one dataframe equal to the values contained in a row from another dataframe
body: <p>I am attempting to reduce the complexity of my calculations by setting the values of a row in one dataframe to the values of a row in another dataframe. The empty dataframe I would like to populate is single index, the dataframe containing values is multi index. My objective is to execute an excel-like function where I can set the values of multiple cells contained in a table equal to the cells contained inside another table.</p>
  <p>The df's appear as follows:</p>
  <p>*Multi Index</p>
  <pre><code> ___________________________________________________________________________________________ 
  |Chan. | Duration   | Designation|    Manufact. |Total Purchases|  Sales      |   Cost      |
  |______|____________|____________|______________|_______________|_____________|_____________|
  |      | Month      | Special    |    Brand     |    153        |  5613.65    |    4756.46  |
  |      |            |            |______________|_______________|_____________|_____________|
  |      |            |            |    Generic   |    1567       | 16546.07    |   16000.00  |
  |Retail|____________|____________|______________|_______________|_____________|_____________|
  |      | Season     |Not Special |    Brand     |     351       | 13246.00    |   15086.26  |
  |      |            |            |______________|_______________|_____________|_____________|
  |      |            |            |    Generic   |     7653      | 165163.03   |  150065.41  |
  |______|____________|____________|______________|_______________|_____________|_____________|
  </code></pre>
  <p>*Single Index</p>
  <pre><code>____________________________________________________________________________
  |           Index                  | Total Purchases  | Sales    |  Cost   |
  |__________________________________|__________________|__________|_________|
  | Retail Month Special Brand       |     &lt;NA&gt;         |   &lt;NA&gt;   |   &lt;NA&gt;  |
  |__________________________________|__________________|__________|_________|
  | Retail Month Special Generic     |     &lt;NA&gt;         |   &lt;NA&gt;   |   &lt;NA&gt;  |
  |__________________________________|__________________|__________|_________|
  | Retail Season Not Special Brand  |     &lt;NA&gt;         |   &lt;NA&gt;   |   &lt;NA&gt;  |
  |__________________________________|__________________|__________|_________|
  | Retail Season Not Special Generic|     &lt;NA&gt;         |   &lt;NA&gt;   |   &lt;NA&gt;  |
  |__________________________________|__________________|__________|_________|
  </code></pre>
  <p>I want to populate the values from the first dataframe into the second dataframe. To do this I've attempted the following solution:</p>
  <pre><code>df.loc[('Retail Month Special Brand'), ['Total Purchases', 'Sales', 'Cost']] = multi_index.loc[('Retail', 'Month', 'Special', 'Brand'), ['Total Purchases', 'Sales', 'Cost']].values()
  </code></pre>
  <p>The end result should appear as follows:</p>
  <pre><code>____________________________________________________________________________
  |           Index                  | Total Purchases  | Sales    |  Cost   |
  |__________________________________|__________________|__________|_________|
  | Retail Month Special Brand       |     153          | 5613.65  | 4756.46 |
  |__________________________________|__________________|__________|_________|
  </code></pre>
  <p>However I received the following:</p>
  <pre><code>TypeError: 'numpy.ndarray' object is not callable.
  </code></pre>