Python Pandas : group by in group by and average?

问题

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?

回答1:

If you want to first take mean on ['cluster', 'org'] combination and then again take mean on cluster groups

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 wan't mean values by cluster only, then you could

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

You could groupby on ['cluster', 'org'] and then take 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

回答2:

I would simply do this, which literally follows what your desired logic was:

df.groupby(['org']).mean().groupby(['cluster']).mean()

来源：https://stackoverflow.com/questions/30328646/python-pandas-group-by-in-group-by-and-average