分组后取最大值对应记录

【问题】

I have an input file,

1A	Traes_1AS_6052071D9.1	99.01	101	99.0 
1A	Traes_1DS_6BA87D1DA.1	96.04	101	99.0 
1A	Traes_1BS_480915AD0.1	94.06	101	99.0 
1B	Traes_1AS_49D585BA6.2	99.01	101	72.0 
1B	Traes_1BS_47F027BBE.2	98.02	101	89.0 
1B	Traes_1DS_3F816B920.1	97.03	101	92.0 
1C	Traes_1AS_3451447E0.1	99.01	101	97.0
1C	Traes_1BS_9F243CEA6.2	92.93	99	97.0 
1C	Traes_1DS_2A6443F45.1	89.90	99	97.0 

I need to

1.     group and iterate inside each line[0],

2.     sort line[4] from lowest to highest value and take the highest value

3.     if they are similar, print the results choosing the one that has highest value in line[2], so that my output file looks like this:

Required output:

1A  Traes_1AS_6052071D9.1   99.01   101 99.0    
1B  Traes_1DS_3F816B920.1   97.03   101 92.0    
1C  Traes_1AS_3451447E0.1   99.01   101 97.0    

This is my try, but it only takes according to the highest line[4]:

import csv
from itertools import groupby
from operator import itemgetter
with open('my_file','rb') as f1:
with open('out_file', 'wb') as f2:
    reader = csv.reader(f1, delimiter='\t')
    writer1 = csv.writer(f2, delimiter='\t')
    for group, rows in groupby(reader, itemgetter(0)):
        seen = set()
        rows = sorted(rows, key=lambda r: float(r[4]))
        for row in rows:
            max(rows, key=lambda r: float(r[4]))
            writer1.writerow(row)

别人的回答：

Just have the key function for max return a tuple of (r[4], r[2])

Slightly simplified example (without output file)

with open('data.txt','rb') as f1:
    reader = csv.reader(f1, delimiter='\t')
    for group, rows in groupby(reader, itemgetter(0)):
        best = max(rows, key=lambda r: (float(r[4]), float(r[2])))
        print best

【回答】

建议用SPL来做，只要一句：

A1：#1表示第1列，~表示按#1分组后的每组数据，maxp返回字段求最大值对应的记录。