Applying cumulative mean function to a grouped object

Question

I have a DataFrame df where each record represents a soccer game. Teams will appear more than once. I need to compute some sort of a rolling mean for each team scores(well, not exactly the rolling mean to the letter).

     date           home           away       score_h  score_a
166  2013-09-01     Fulham         Chelsea       0      0
167  2013-09-03     Arsenal        Everton       0      2
164  2013-09-05     Arsenal        Swansea       5      1
165  2013-09-06     Fulham         Norwich       0      1
163  2013-09-18     Arsenal        Swansea       0      0

What I need to calculate, is the mean score for each team (home and away).

For brevity, let’s just do the home column:

grouped = df.groupby('home')
grouped = grouped.sort_index(by='date') # rows inside groups must be in asc order

This results in:

    date    home    away    score_h     score_a
home                        
Arsenal     167     2013-09-03  Arsenal     Everton     0   2
            164     2013-09-05  Arsenal     Swansea     5   1
            163     2013-09-18  Arsenal     Swansea     0   0
Fulham      166     2013-09-01  Fulham      Chelsea     0   0
            165     2013-09-06  Fulham      Norwich     0   1

Question starts here

Now, I need to compute “rolling mean” for teams. Let’s do it by hand for the group named Arsenal. At the end of this we should wind up with 2 extra columns, let’s call them: rmean_h and rmean_a. First record in the group (167) has scores of 0 and 2. The rmean of these is simply 0 and 2 respectively. For second record in the group (164), the rmeans will be (0+5)/2 = 2.5 and (2+1) / 2 = 1.5, and for the third record, (0+5+0)/3 = 1.66 and (2+1+0)/3 = 1.

Our DataFrame should now looks like this:

                    date       home         away    score_h score_a rmean_h rmean_a
home                        
Arsenal     167     2013-09-03  Arsenal     Everton     0  2    0       2
            164     2013-09-05  Arsenal     Swansea     5  1    2.5     1.5
            163     2013-09-18  Arsenal     Swansea     0  0    1.66    1
Fulham      166     2013-09-01  Fulham      Chelsea     0  0
            165     2013-09-06  Fulham      Norwich     0  1

I want to carry out these calculations for my data, do you have any suggestions please?

Asked By: nutship

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Source

Answer 1

You can apply an expanding_mean (see docs) to each group:

grouped = df.sort(columns='date').groupby('home')
grouped['score_h'].apply(pd.expanding_mean)

Answered By: joris

Answer 2

For pandas 1.4.3 you can use:

grouped = df.sort(columns='date').groupby('home')
grouped['score_h'].expanding().mean()

Read more on the docs: expanding and expanding window.

Answered By: Myst

Applying cumulative mean function to a grouped object

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