请参阅这篇文章其中建议如下：

see this post which suggests something like the following:

header = ['User_ID','--Date','0Num_1','0Num_2','Com_ID']
writer = csv.DictWriter(outcsv, fieldnames = header)
writer.writeheader()
writer.writerows({col: row} for row, col in zip(header, p))

从系统参数解析额外的列use sys.argv

to parse the extra columns from the system arguments use sys.argv

import sys

extra_headers = sys.argv
header.extend(sys.argv)
n = len(sys.argv)

writer = csv.DictWriter(outcsv, fieldnames = header)
writer.writeheader()

col_fill = ''
# extend p with two columns of blank data
writer.writerows({col: row_item} for row in p for row_item,col in zip(row+[col_fill]*n,header))

这里我遍历每一行，然后创建一个字典，按顺序将数据分配给每一列。注意 [col_fill] * n 这会创建一个等于 col_fill 的相同项目的列表，

here I iterate through each row, I then crate a dictionary to allocate data to each column in order. Notice [col_fill]*n this creates a list of identical items equal to col_fill that will be used to fill the additional columns parsed in via command line arguments.

在此示例中，命令行参数将被解析为：

In this example the command line arguments would be parsed as:

$ python script_name.py Dept_ID Location

/ p>

and would create:

User_ID,--Date,0Num_1,0Num_2,Com_ID,Dept_ID,Location
000101,04-13-2015,000012,000021,001011,,
000102,04-03-2014,000001,000007,001002,,
000103,06-05-2013,000003,000004,000034,,
000104,12-31-2012,000004,000009,001023,,
000105,09-09-2011,000009,000005,000104,,