title: Python max() function fails when used on pandas columns and integer fails
body: <p>I'm trying to create a new pandas dataframe column by subtracting an existing dataframe column column from another. However, if the result is a negative number, the new column value should be set to zero.</p>
  
  <pre><code>import pandas as pd
  data = {'A': [1,2,3], 'B': [3,2,1]}
  df = pd.DataFrame(data)
  
  In [4]: df
  Out[4]: 
     A  B
  0  1  3
  1  2  2
  2  3  1
  </code></pre>
  
  <p>If I create a new dataframe column 'C' by subtracting 'B' from 'A', I get the right result.</p>
  
  <pre><code>df['C'] = df['A'] - df['B']
  
  In[8]: df
  Out[7]: 
     A  B  C
  0  1  3 -2
  1  2  2  0
  2  3  1  2
  </code></pre>
  
  <p>However, if I utilize the <code>max()</code> function to avoid results with a negative number, I get "ValueError: The truth value of a Series is ambiguous."</p>
  
  <pre><code>&gt;&gt;&gt; df['C'] = max(df['A'] - df['B'], 0)
  ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
  </code></pre>
  
  <p>The expected output is:</p>
  
  <pre><code>   A  B  C
  0  1  3  0
  1  2  2  0
  2  3  1  2
  </code></pre>
  
  <p>What am I doing wrong?</p>