title: Cumulative sum only applying on 1 column python
body: <p>I would like to apply cumsum on 1 specific column only since I have got other values in different columns that must stay the same.</p>
  
  <p>This is the script that I have so far</p>
  
  <pre><code>df.groupby(by=['name','day']).sum().groupby(level=[0]).cumsum()
  </code></pre>
  
  <p>However this script results in that all of my columns in my pandas df will cumulate. The only column which must cumulate sum is <code>data</code>.</p>
  
  <p>As requested, here is some sample data:</p>
  
  <pre><code>df = pd.DataFrame({'ID': ["880022443344556677787", "880022443344556677782", "880022443344556677787",
                            "880022443344556677782", "880022443344556677787", "880022443344556677782",
                            "880022443344556677781"],
                     'Month': ["201701", "201701", "201702", "201702", "201703", "201703", "201703"],
                     'Usage': [20, 40, 100, 50, 30, 30, 2000],
                     'Sec': [10, 15, 20, 1, 5, 6, 30]})
  
                        ID   Month  Sec  Usage
  0  880022443344556677787  201701   10     20
  1  880022443344556677782  201701   15     40
  2  880022443344556677787  201702   20    100
  3  880022443344556677782  201702    1     50
  4  880022443344556677787  201703    5     30
  5  880022443344556677782  201703    6     30
  6  880022443344556677781  201703   30   2000
  </code></pre>
  
  <p>Desired output</p>
  
  <pre><code>                      ID   Month  Sec  Usage
  0  880022443344556677787  201701   10     20
  1  880022443344556677782  201701   15     40
  2  880022443344556677787  201702   20    120
  3  880022443344556677782  201702    1     90
  4  880022443344556677787  201703    5    150
  5  880022443344556677782  201703    6    120
  6  880022443344556677781  201703   30   2000
  </code></pre>