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pythonpandasgroup-bypivot-tablemean

group by in group by and average


I have a dataframe like this:

cluster  org      time
   1      a       8
   1      a       6
   2      h       34
   1      c       23
   2      d       74
   3      w       6 

I would like to calculate the average of time per org per cluster.

Expected result:

cluster mean(time)
1       15 #=((8 + 6) / 2 + 23) / 2
2       54 #=(74 + 34) / 2
3       6

I do not know how to do it in Pandas, can anybody help?


Solution

  • If you want to first take mean on the combination of ['cluster', 'org'] and then take mean on cluster groups, you can use:

    In [59]: (df.groupby(['cluster', 'org'], as_index=False).mean()
                .groupby('cluster')['time'].mean())
    Out[59]:
    cluster
    1          15
    2          54
    3           6
    Name: time, dtype: int64
    

    If you want the mean of cluster groups only, then you can use:

    In [58]: df.groupby(['cluster']).mean()
    Out[58]:
                  time
    cluster
    1        12.333333
    2        54.000000
    3         6.000000
    

    You can also use groupby on ['cluster', 'org'] and then use mean():

    In [57]: df.groupby(['cluster', 'org']).mean()
    Out[57]:
                   time
    cluster org
    1       a    438886
            c        23
    2       d      9874
            h        34
    3       w         6