如何合并具有重复值的列并保留Python中不同列的最大值？

Question

我想查找“参考”列的重复值，然后保留仅复制来自“金额”列的最大金额列的找到的行。

电流：

+----------+---------------------+---------+ 
| reference | amount | column3 | column4 | 
+----------+---------------------+---------+ 
| test1 |  9 |  45 | ye  | 
| test1 |  200|  45 | agag | 
| test1 |  1 |  45 | aaa  | 
| test2 |  99 |  45 | bbab | 
| test1 |  11 |  45 | value | 
+----------+---------------------+----------+ 

期望：

+----------+---------------------+---------+ 
| reference | amount | column3 | column4 | 
+----------+---------------------+---------+ 
| test1 |  200|  45 | agag | 
| test2 |  99 |  45 | bbab | 

请分享对这种情况的线索。

Answer 1

类似以下内容将是一个良好的开端：

import csv, collections 

with open("mydata.csv", 'r') as f_input: 
    csv_input = csv.reader(f_input) 
    # Assuming the first row contains the heading names, otherwise remove. 
    headings = csv_input.next()  
    d_max_rows = collections.OrderedDict() 

    for cols in csv_input: 
     reference = cols[0] 
     if reference in d_max_rows: 
      cur_max = d_max_rows[reference] 
      if int(cols[1]) >= int(cur_max[1]): 
       d_max_rows[reference] = cols 
     else: 
      d_max_rows[reference] = cols 

lrows = [headings] + list(d_max_rows.itervalues()) 

for reference, amount, col3, col4 in lrows: 
    print "%-15s %-10s %-10s %-10s" % (reference, amount, col3, col4) 

这会给你以下的输出：

reference  amount  column3 column4 
test1   200  45   agag  
test2   99   45   bbab 

Answer 2

下面是一些代码，你想要做什么：

from collections import namedtuple 
import csv 

Record = namedtuple('Record', 'reference amount column3 column4') 

no_dups = {} 
with open('references.csv', 'r', newline='') as csvfile: 
    for rec in map(Record._make, csv.reader(csvfile)): 
     if (rec.reference not in no_dups or 
      int(no_dups[rec.reference].amount) < int(rec.amount)): 
      no_dups[rec.reference] = rec 

with open('references_out.csv', 'w', newline='') as csvfile: 
    csv.writer(csvfile).writerows(rec for rec in no_dups.values()) 

Answer 3

熊猫是一个非常棒的python模块，用于处理表格数据。它非常像R语言，并提供了一种内存数据库。为了您的例子是这样简单：

import pandas as pd 

df = pd.read_csv('test.csv') 
a = df.groupby('reference')[['amount']].max() 
answer = df.merge(a, on='amount') 

并将结果保存回CSV：

answer.to_csv('out.csv', index=False) 

假设test.csv是您的数据文件，像这样：

reference,amount,column3,column4 
test1,9,45,ye 
test1,200,45,agag 
test1,1,45,aaa 
test2,99,45,bbab 
test1,11,45,value