title: Equivalent of pandas.Series.value_counts for pandas.DataFrame
body: <p>I would like to count how many times tuples of data appear in a pandas DataFrame. For example, suppose my data looks like this:</p>
  
  <pre><code>    a  b
  0   0  0
  1   0  0
  2   1  0
  3   1  1
  4   1  1
  </code></pre>
  
  <p>I would like to get a "number of times each row occurs" output like this:</p>
  
  <pre><code>(0,0)    2
  (1,0)    1
  (1,1)    2
  dtype: int64
  </code></pre>
  
  <p>However, the closest thing that I know how to do is to do some arithmetic that merges the two columns into a series and then call <code>value_counts</code> on the series:</p>
  
  <pre><code>&gt;&gt;&gt; (df['a'] * 10 + df['b']).value_counts()
   0     2
  10     1
  11     2
  dtype: int64
  </code></pre>
  
  <p>I don't want to have to manually merge the columns to get these counts. But <code>DataFrame</code> doesn't seem to have a <code>value_counts</code> method:</p>
  
  <pre><code>&gt;&gt;&gt; df.value_counts()
  AttributeError: 'DataFrame' object has no attribute 'value_counts'
  </code></pre>
  
  <p>Is there an easy way to get the row count information from a dataframe?</p>