title: Pandas Cumulative Sum in GroupBy
body: <p>I have a time series data with symbol and their respective values at a particular time.</p>
  
  <pre><code>index,symbol,value
  01:00,A,10
  01:00,B,15
  01:01,A,15
  01:01,B,25
  01:02,A,30
  01:02,B,45
  </code></pre>
  
  <p>Now I want create a 4th column, which has cumulative value on time series basis for each symbol but from each cumulative row, the first row value would be subtracted for each symbol respectively</p>
  
  <pre><code>index,symbol,value,adjustedCumulativeSum
  01:00,A,10,0
  01:00,B,15,0
  01:01,A,15,15
  01:01,B,25,25
  01:02,A,30,45
  01:02,B,45,70
  </code></pre>
  
  <p>I know how to do normal cumulative sum</p>
  
  <pre><code>df = df.reset_index().sort_values(['index','symbol'])
  df['cumlativesum'] = df.groupby('symbol')['value'].cumsum()
  df = df.set_index('index')
  </code></pre>
  
  <p>But do I deduct row 0 value from all cumulative sums? </p>