使用 Pandas 数据框聚合后无法对值进行排序

Question

I have the following dataframe:

df[['ID','Team']].groupby(['Team']).agg([('total','count')]).reset_index("total").sort_values("count")

I basically, need to count the number of IDs by Team and then sort by the total number of IDs.

The aggregation part it's good and it gives me the expected result. But when I try the sort part I got this:

KeyError: 'Requested level (total) does not match index name (Team)'

What I am doing wrong?

Answer 1

Use names aggregation for specify new columns names in aggregate function, remove total from DataFrame.reset_index :

df = pd.DataFrame({
        'ID':list('abcdef'),
        'Team':list('aaabcb')
})

df = df.groupby('Team').agg(count=('ID','count')).reset_index().sort_values("count") 
print (df)
  Team  count
2    c      1
1    b      2
0    a      3

Your solution should be changed by specify column after groupby for processing, then specify new column name with aggregate function in tuple and last also remove total from reset_index :

df = df.groupby('Team')['ID'].agg([('count','count')]).reset_index().sort_values("count")
print (df)
  Team  count
2    c      1
1    b      2
0    a      3