title: update pandas by two other columns
body: <p>I have a data set with about 3000 entries and 10 columns so this is a much much simpler version</p>
  <pre><code>df =
     asset    tail    more_info
  0   x         a     this is a long text field that is right
  1   x         b     this is a long text field that is almost right
  2   y         a     this is right
  3   y         b     this is probably not right
  </code></pre>
  <p>desired result</p>
  <pre><code>df =
     asset    tail    more_info
  0   x         a     this is a long text field that is right
  1   x         b     this is a long text field that is right
  2   y         a     this is right
  3   y         b     this is right
  </code></pre>
  <p>so I'm trying to update my more_info field where the assets match and the tail equals 'a'
  in reality the data set is more complicated so I need to do it programmatically, this is where I'm drawing a blank in that logic</p>
  <pre><code>def my_func(x):
      if x.asset == x.asset and x.tail =='b':
          '''
          this would be where I'd set it to x.more_info where tail = 'a' maybe numpy where ??
          '''
          
  df['more_info'] = df['more_info'].apply(lambda x: my_func(x))
  </code></pre>