如何在 Pandas DataFrame 上动态添加同名列？

Question

I have a list of emails, phones and user info that I want to output in csv but I need to follow a format that contains duplicate columns.

email, email, phone, phone, phone, name, address
jo@doe.com, re@ko.com, 90192, 2980, 9203, John Doe, 82 High Street
re@doe.com, az@ko.com, 1341, 55, 665, Roe Jan, 11 Low Street
red@doe.com,,, 55, 111, Roe Jan, 11 Low Street

Is this possible in pandas? What is the best way of adding rows and columns with same name?

Answer 1

You could get it done using csv :

list.txt:

email, email, phone, phone, phone, name, address
jo@doe.com, re@ko.com, 90192, 2980, 9203, John Doe, 82 High Street
re@doe.com, az@ko.com, 1341, 55, 665, Roe Jan, 11 Low Street
red@doe.com,,, 55, 111, Roe Jan, 11 Low Street

and then:

import csv

with open('list.txt', 'r') as readFile:
    reader = csv.reader(readFile)
    lines = list(reader)

with open('people.csv', 'w') as writeFile:
    writer = csv.writer(writeFile)
    writer.writerows(lines)

readFile.close()
writeFile.close()

OUTPUT (people.csv):

Answer 2

使用不同的列名（email01，email02 ...）构建数据框，然后在输出中使用标题列表：

df.to_csv("file.csv",header=['email', 'email', 'phone', 'phone', 'phone', 'name', 'address'])

Answer 3

Use pd.conact to add columns with the same name:

df = pd.concat([df1, df2], axis=1)

It will concatenate all columns, even if some of them have the same name.