title: pandas Series.cumsum() vs pandas.expanding_sum()
body: <p>assuming I have a pandas Series s, what is the difference between s.cumsum() and pd.expanding_sum(s)? (I guess the answer should be the same also for cummax()/cummin(), and pd.expanding_max()/pd.expanding_min())</p>
  
  <p>The docs say:</p>
  
  <blockquote>
    <p>Note The output of the rolling_ and expanding_ functions do not
    return a NaN if there are at least min_periods non-null values in the
    current window. This differs from cumsum, cumprod, cummax, and cummin,
    which return NaN in the output wherever a NaN is encountered in the
    input.</p>
  </blockquote>
  
  <p>Is this the only difference?</p>
  
  <p>(assuming this is the only difference I don't understand why there needs to be 2 different methods defined for this very similar functionality)</p>