获取Pandas读取Excel后所有列名的几种方法

import pandas as pd

data = pd.read_excel(\'客户信息.xlsx\')
# 获取Pandas读取Excel后所有列名的几种方法
print(list(data))                              # 0. 直接使用 list 关键字，返回一个list
columns_name1 = [column for column in data]    # 1.链表推倒式_获取Pandas列名的几种方法
columns_name2 = data.columns.values            # 2.通过columns字段获取，返回一个numpy型的array
columns_name3 = data.columns.tolist()          # 4.df.columns 返回Index，可以通过 tolist(), 或者 list（array） 转换为list

print(\'*\' * 10)
print(columns_name1)
print(\'*\' * 20)
print(columns_name2, type(columns_name2))
print(\'*\' * 30)
print(columns_name3, type(columns_name2))
print(\'*\' * 40)
print(list(columns_name3))

PyDev console: starting.
Python 3.9.0 (tags/v3.9.0:9cf6752, Oct  5 2020, 15:34:40) [MSC v.1927 64 bit (AMD64)] on win32
runfile(\'D:/pyexcel/temppandas.py\', wdir=\'D:/pyexcel\')
[\'id\', \'customer_code\', \'customer_name\', \'delivery_address\', \'purchasing_agency\', \'contact_phone\', \'contact_tel\', \'contact_fax\', \'qq\', \'wechat\', \'email\', \'director\', \'director_iphone\', \'director_telephone\', \'director_fax\', \'registered_address\', \'bank\', \'account_number\', \'creation_date\', \'unified_social_credit_code\', \'Unnamed: 20\', \'office_address\', \'remarks\', \'creation_date.1\', \'note_appended\', \'client\', \'credit_line\', \'use_line\']
**********
[\'id\', \'customer_code\', \'customer_name\', \'delivery_address\', \'purchasing_agency\', \'contact_phone\', \'contact_tel\', \'contact_fax\', \'qq\', \'wechat\', \'email\', \'director\', \'director_iphone\', \'director_telephone\', \'director_fax\', \'registered_address\', \'bank\', \'account_number\', \'creation_date\', \'unified_social_credit_code\', \'Unnamed: 20\', \'office_address\', \'remarks\', \'creation_date.1\', \'note_appended\', \'client\', \'credit_line\', \'use_line\']
********************
[\'id\' \'customer_code\' \'customer_name\' \'delivery_address\'
 \'purchasing_agency\' \'contact_phone\' \'contact_tel\' \'contact_fax\' \'qq\'
 \'wechat\' \'email\' \'director\' \'director_iphone\' \'director_telephone\'
 \'director_fax\' \'registered_address\' \'bank\' \'account_number\'
 \'creation_date\' \'unified_social_credit_code\' \'Unnamed: 20\'
 \'office_address\' \'remarks\' \'creation_date.1\' \'note_appended\' \'client\'
 \'credit_line\' \'use_line\'] <class \'numpy.ndarray\'>
******************************
[\'id\', \'customer_code\', \'customer_name\', \'delivery_address\', \'purchasing_agency\', \'contact_phone\', \'contact_tel\', \'contact_fax\', \'qq\', \'wechat\', \'email\', \'director\', \'director_iphone\', \'director_telephone\', \'director_fax\', \'registered_address\', \'bank\', \'account_number\', \'creation_date\', \'unified_social_credit_code\', \'Unnamed: 20\', \'office_address\',