title: Symmetric difference of two pandas dataframes
body: <p>I have two dataframes. The columns are: 'x', 'y', 'name'. </p>
  
  <p>They are the same for both of the two datasets.
  The x and y are lists of their own. This is what one dataframe looks like</p>
  
  <pre><code>x ----- y------- name
   0  [0.4752243077637221, 0.6520124241756947, 0.468...  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...  D 1#0 ξ:3τ:0.1
   1  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...  [0.38764437658969714, 0.5140357108089131, 0.75...  D 1#1 ξ:3τ:0.1
   2  [0.20785203454036535, 0.1204140394378531, 0.22...  [0.8566063230698455, 0.8234990482161559, 0.826...  D 2#0 ξ:3τ:0.1
   3  [0.4752243077637221, 0.6520124241756947, 0.585...  [0.38764437658969714, 0.5140357108089131, 0.62...  D 2#1 ξ:3τ:0.1
   4  [0.7019329992171317, 0.9106333194078352, 0.786...  [0.7054927087841893, 0.8111061879179277, 0.845...  D 2#2 ξ:3τ:0.1
  </code></pre>
  
  <p>The second dataframe might have more or less rows and the name will vary. I want to check which x-y-coordinates are in both dataframes, independent of the row - and delete if it is a duplicate.</p>
  
  <p>The goal is to depict the symmetric difference of a clustering algorithm</p>
  
  <p>I already tried:</p>
  
  <pre><code>difference = pd.concat([all_clusters_a, all_clusters_b]).drop_duplicates(keep=False, inplace=False)
      enter code here
  </code></pre>
  
  <p>Which leads to: TypeError: unhashable type: 'numpy.ndarray'</p>
  
  <p>and the same error with:</p>
  
  <pre><code>    all_clusters_a.iloc[1:4]= all_clusters_b[:3].values
  all_clusters_a['a']='a'
  all_clusters_a.set_index('a', append=True, inplace=True)
  all_clusters_b['b']='b'
  all_clusters_b.set_index('b', append=True, inplace=True)
  mergeda = all_clusters_a.append(all_clusters_b)
  mergeda = mergeda.drop_duplicates().sort_index()
  idx = pd.IndexSlice
  complement_BiA = mergeda.loc[idx[:,'a'],:]
  
  mergedb = all_clusters_b.append(all_clusters_b)
  mergedb = mergedb.drop_duplicates().sort_index()
  complement_AiB = mergedb.loc[idx[:,'b'],:]
  </code></pre>
  
  <p>the numpy.ndarray seems to hate the drop_duplicate()</p>