python csv 列表比较和添加

Question

解析和添加客户端数据

Data:
('Client 1', '13.2')
('Client 1', '22.4')
('Client 1', '1.2')
('Client 2', '3.4')
('Client 3', '12.3')
('Client 3', '3.221')
('Client 4', '234.44')

尝试编写正确的循环并添加功能以获得正确的输出。

目标结果：

客户 1：36.8
客户 2：3.4
客户 3：15.521
客户 4：234.44

这是我最终正确列出数据的代码。我从这里去哪里才能得到结果。我尝试了很多不同的循环但都没有成功。

import csv

with open('clientdata.csv') as csvfile:
    reader = csv.DictReader(csvfile)
    numbers = []
    for row in reader:
       print(row['Client Name'], row['Earnings'])

Answer 1

您可以使用格式字符串（%.2f 将有 2 位小数）和记录谁赚了多少的字典来解决。

clients = {}
with open('clientdata.csv') as csvfile:
    reader = csv.DictReader(csvfile)
    numbers = []
    for row in reader:
       name = row['Client Name']
       earnings = float(row['Earnings'])
       if name in clients:
           clients[name] += earnings
       else:
           clients[name] = earnings
    for client in sorted(clients):
          print("%s:%.2f" % (client, clients[client]))

Answer 2

你应该创建一个包含所有客户端的字典，然后检查客户端是否已经在目录中。如果客户不是，则将他们与他们的收入相加。如果他们在其中，则只需将下一个收入添加到他们现有的收入中。

这是我将如何执行此操作的代码。希望这会有所帮助：

clientDirectory = {}
for row in reader:
    if row['Client Name'] not in clientDirectory:
        clientDirectory[row['Client Name']] = float(row['Earnings'])
    else:
        [row['Client Name']] += float(row['Earnings'])

for key in clientDirectory.keys():
    print("%s %f" %(key, clientDirectory[key]))

Answer 3

您可以使用字典来添加值

with open('clientdata.csv') as csvfile:
    reader = csv.DictReader(csvfile)
    results = {}

    # adding

    for row in reader:

       # default value for new client
       if row['Client Name'] not in results:
          results[row['Client Name']] = 0

       # add value
       results[row['Client Name']] += float(row['Earnings'])

    # showing

    for name, value in results.items():
        print("%s: %s" % (name,value))

但这可能是一个问题 - 字典不必保持顺序，您可以按不同的顺序查看结果。

Answer 4

假设您有这样一个数据文件：

$ cat /tmp/data.csv
'Client 1', '13.2'
'Client 1', '22.4'
'Client 1', '1.2'
'Client 2', '3.4'
'Client 3', '12.3'
'Client 3', '3.221'
'Client 4', '234.44'

您可以使用defaultdict 将文件中的浮点值相加：

from collections import defaultdict
import csv

dd=defaultdict(float)

with open('/tmp/data.csv') as data:
    for row in csv.reader(data, quotechar="'", skipinitialspace=True):
        dd[row[0]]+=float(row[1])

print '\n'.join(["{}: {}".format(k, dd[k]) for k in sorted(dd)])

打印：

Client 1: 36.8
Client 2: 3.4
Client 3: 15.521
Client 4: 234.44

（我使用的排序仅适用于客户端 1 - 客户端 9；之后你需要一个 natural sort 方法...）

Answer 5

$ cat test.csv
Client 1, 13.2
Client 1, 22.4
Client 1, 1.2
Client 2, 3.4
Client 3, 12.3
Client 3, 3.221
Client 4, 234.44

然后在Python:

from odo import odo
from pandas import DataFrame

clientDF = odo('test.csv', DataFrame)
print clientDF.groupby(['0']).sum()

python csv 列表比较和添加

python csv list compare and addition

python

csv

parsing

addition

目标结果：