Question

解析＆amp;添加客户数据

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。我从哪里可以获得结果。我尝试了许多不同的循环但没有成功。

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

你可以通过使用格式字符串（％。2f将有2个小数位）和字典跟踪谁做出多少来解决它。

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

您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在目录中。如果客户端没有，那么添加他们的收入。如果他们在其中，那么只需添加他们现有的收入即可获得下一次收入。

以下是我将如何进行此操作的代码。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

您可以使用词典添加值

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))

但它可能是一个问题 - 字典不必保持秩序，你可以看到不同顺序的结果。

Answer 4

假设你有一个这样的数据文件：

$ 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在文件中添加浮点值：

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;之后您需要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中：

from odo import odo
from pandas import DataFrame

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

python csv list比较和添加

目标结果：

5 个答案: