title: Getting Scalar Value with pandas loc/iloc/at/iat/ix
body: <p>I have two dataframes: df1 and df2.  I am iterating through df1 using iterrows, and for a particular field in each line, I am looking into df2 for the line that matches that field, and trying to pull out a corresponding value from that line in df2 in a SCALAR format.  Every way I try to do this I end up with another dataframe or series and I can't use that value as a scalar.  Here is my latest attempt:</p>
  
  <pre><code>for index, row in df1.iterrows():
      a = row[0]
      b = df2.loc[(df2['name'] == a ), 'weight']
      c = row[1] - b   #this is where error happens
      df1.set_value(index,'wtdif',c)
  </code></pre>
  
  <p>I get an error because 'b' in this case is not a scalar, if i print it out here is an example of what it looks like.  The '24' here is the index of the row it was found in in df2.  The other confusing part about this is that I can't index 'b' in any way even though it is a series (i.e. b[0] creates an error, as does b['weight'], etc.)</p>
  
  <pre><code>Name: weight, dtype: float64
  24    141.5
  </code></pre>