title: pandas comparison raises TypeError: cannot compare a dtyped [float64] array with a scalar of type [bool]
body: <p>I have the following structure to my dataFrame:</p>
  <pre><code>Index: 1008 entries, Trial1.0 to Trial3.84
  Data columns (total 5 columns):
  CHUNK_NAME                    1008  non-null values
  LAMBDA                        1008  non-null values
  BETA                          1008  non-null values
  HIT_RATE                      1008  non-null values
  AVERAGE_RECIPROCAL_HITRATE    1008  non-null values
  
  chunks=['300_321','322_343','344_365','366_387','388_408','366_408','344_408','322_408','300_408']
  lam_beta=[(lambda1,beta1),(lambda1,beta2),(lambda1,beta3),...(lambda1,beta_n),(lambda2,beta1),(lambda2,beta2)...(lambda2,beta_n),........]
  
  my_df.ix[my_df.CHUNK_NAME==chunks[0]&amp;my_df.LAMBDA==lam_beta[0][0]]
  </code></pre>
  <p>I want to get the rows of the DataFrame for a particular chunk lets say <code>chunks[0]</code> and particular <code>lambda</code> value. So in this case, the output should be all rows in the DataFrame having <code>CHUNK_NAME='300_321'</code> and <code>LAMBDA=lambda1</code>. There would be n rows one for each <code>beta</code> value that would be returned. But instead I get the following error. Any help in solving this problem would be appreciated.</p>
  <pre><code>TypeError: cannot compare a dtyped [float64] array with a scalar of type [bool]
  </code></pre>