从列表

Question

我有一个CSV文件，我读作每行的字典列表。我想删除列表中具有'' EmailAddress的所有条目。我试过了：

#!/usr/bin/python
import csv


def import_users(location_of_file):
    with open(location_of_file, 'r', newline='', encoding='utf-8-sig') as openfile:
       reader = csv.DictReader(openfile)
       for row in reader:
            yield row

def save_csv(data, location):
   with open(location, 'w', newline='', encoding='utf-8-sig') as file:
       fieldnames = ['EmailAddress', 'GivenName', 'Surname', 'Company', 'Department']
       writer = csv.DictWriter(file, fieldnames=fieldnames)
       writer.writeheader()
       for item in data:
           writer.writerow(item)



if __name__ == '__main__':
    users = list(import_users('C:\Temp\Example.csv'))
    for user in users:
        if user['EmailAddress'] == '':
            del user
        else:
            pass
    save_csv(users, 'C:\Temp\Output.csv')

但我的结果仍然是没有电子邮件地址的条目。我做错了什么？

Answer 1

对正在修改的数据结构进行迭代是不好的做法（并且会导致超级烦人的错误）。因此，您应该制作另一个列表，其中只包含您想要的项目。你可以用循环来完成这个：

users = list(import_users('C:\Temp\Example.csv'))
filtered_users = []
for user in users:
    if user['EmailAddress'] == '':
        filtered_users.append(user)
save_csv(filtered_users, 'C:\Temp\Output.csv')

或使用pythons过滤功能：

users = list(import_users('C:\Temp\Example.csv'))
filtered_users = filter(lambda user: user.get('EmailAddress') != '', users)
save_csv(filtered_users, 'C:\Temp\Output.csv')

Answer 2

您不需要在内存中创建列表。您可以改为传递生成器和迭代器：

if __name__ == '__main__':
    users = import_users('C:/Temp/Example.csv')
    save_csv((user for user in users if user['EmailAddress'] != ''),
             'C:/Temp/Output.csv')

Answer 3

不要在刺激他们的情况下更改列表项目。

相反

<input type="hidden" name="business" value="peoplesroboticsfacilitator@outlook.com">

待办事项

for user in users:
    if user['EmailAddress'] == '':
        del user
     else:
        pass

Answer 4

你可能最好不要制作新的清单而不是删除项目：

users = [user for user in users if user['EmailAddress'] != '']

Answer 5

以下是使用pandas的解决方案：

示例数据：

import pandas as pd
#Read csv data
df = pd.read_csv('data.csv')
#Get only the rows having email address
dfo = df[pd.notnull(df['EmailAddress'])]
#Save to a file
dfo.to_csv('output.csv', index=False)

示例输出：