python读取csv文件作为字典并排序和增加计数器

jes516 发表于 Dev

jes516

我希望有人指出我正确的方向。从我的阅读中，我相信使用字典最适合这种需求，但是我绝不是一名熟练的程序员，我希望有人可以给我一些帮助。这是我拥有的CSV文件：

11362672,091914,100914,100.00,ITEM,11,N,U08
12093169,092214,101514,25.00,ITEM,11,N,U10
12162432,091214,101214,175.00,ITEM,11,N,U07
11362672,091914,100914,65.00,ITEM,11,N,U08
11362672,091914,100914,230.00,ITEM,11,N,U08

我想将第一列作为键，然后将第二列作为该键的值，以便：

按键对数据排序
应对事件
追加柜台

这是我想要获得的输出：

1,11362672,091914,100914,100.00,ITEM,11,N,U08 # occurrence 1 for key: 11362672
2,11362672,091914,100914,65.00,ITEM,11,N,U08 # occurrence 2 for key: 11362672
3,11362672,091914,100914,230.00,ITEM,11,N,U08 # occurrence 3 for key: 11362672
1,12093169,092214,101514,25.00,ITEM,11,N,U10 # occurrence 1 for key: 12093169
1,12162432,091214,101214,175.00,ITEM,11,N,U07 # occurrence 1 for key: 12162432

我需要保持每一行的完整性，这就是为什么我认为词典效果最好的原因。我没有很多，但这就是我开始的目的。这是我需要帮助进行排序，计数和附加计数器的地方。

import csv
with open('C:/Download/item_report1.csv', 'rb') as infile:
     reader = csv.reader(infile)
     dict1 = {row[0]:row[1:7] for row in reader}
     print dict1

给我：

{
'11362672': ['091914', '100914', '230.00', 'ITEM', '11', 'N'], 
'12093169': ['092214', '101514', '25.00', 'ITEM', '11', 'N'], 
'12162432': ['091214', '101214', '175.00', 'ITEM', '11', 'N']
}

马特

简要地说，您应该使用计数器来计算键值，并使用列表来存储行。

在您读取csv时，请跟踪您看到键值的次数，并在您读取键值时将其插入每行的开头。

读入文件后，可以首先按键值对其进行排序，然后按出现次数对它进行排序。

import csv

counter = {}
data = []

with open('report.csv','rb') as infile:
  for row in csv.reader(infile):
    key = row[0]
    if key not in counter:
      counter[key] = 1
    else:
      counter[key] += 1
    row.insert(0,counter[key])
    data.append(row)

for row in sorted(data,key=lambda x: (x[1],x[0])):
  print row

这又是同一回事，写的略有不同，按照官方的风格指南有4个空格，而不是我个人偏爱的两个。

import csv

# key function for sorting later
def second_and_first(x):
    return (x[1],x[0])

# dictionary to store key_fields and their counts
counter = {}
# list to store rows from the csv file
data = []

with open('report.csv','rb') as infile:
    for row in csv.reader(infile):
        # For convenience, assign the value of row[0] to key_field
        key_field = row[0]
        # if key_field is not in the dictionary counter. Add it with a value of 1
        if key_field not in counter:
            counter[key_field] = 1
        # otherwise, it is there, increment the value by one.
        else:
            counter[key_field] += 1
        # insert the value associated with key_field in the counter into the start of
        # the row
        row.insert(0,counter[key_field])
        # Append the row to 
        data.append(row)

for row in sorted(data,key=second_and_first):
    print row

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