另一种方法，你可以在pandas中使用DataFrame: 它可以很容易地将数据转储到csv，就像下面的代码:

import pandas
df = pandas.DataFrame(data={"col1": list_1, "col2": list_2})
df.to_csv("./file.csv", sep=',',index=False)

import csv

with open(..., 'wb') as myfile:
    wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
    wr.writerow(mylist)

编辑:这只适用于python 2.x。

让它与python 3一起工作。x用w代替wb(见这个SO答案)

with open(..., 'w', newline='') as myfile:
     wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
     wr.writerow(mylist)

以下是Alex Martelli的安全版本:

import csv

with open('filename', 'wb') as myfile:
    wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
    wr.writerow(mylist)

下面是Python 3的复制粘贴示例。使用选项定义自己的分隔符和引号字符。

import csv

mylist = ['value 1', 'value 2', 'value 3']

with open('employee_file.csv', mode='w') as employee_file:
    employee_writer = csv.writer(employee_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_ALL)
    employee_writer.writerow(mylist)

这会生成employee_file.csv，如下所示:

"value 1","value 2","value 3"

NOTE: If quoting is set to csv.QUOTE_MINIMAL, then .writerow() will quote fields only if they contain the delimiter or the quotechar. This is the default case. If quoting is set to csv.QUOTE_ALL, then .writerow() will quote all fields. If quoting is set to csv.QUOTE_NONNUMERIC, then .writerow() will quote all fields containing text data and convert all numeric fields to the float data type. If quoting is set to csv.QUOTE_NONE, then .writerow() will escape delimiters instead of quoting them. In this case, you also must provide a value for the escapechar optional parameter.

你当然应该使用CSV模块，但你可能需要编写unicode。对于那些需要编写unicode的人，这是来自示例页面的类，您可以将其用作util模块:

import csv, codecs, cStringIO

class UTF8Recoder:
    """
    Iterator that reads an encoded stream and reencodes the input to UTF-8
    """
    def __init__(self, f, encoding):
        self.reader = codecs.getreader(encoding)(f)

def __iter__(self):
    return self

def next(self):
    return self.reader.next().encode("utf-8")

class UnicodeReader:
    """
    A CSV reader which will iterate over lines in the CSV file "f",
    which is encoded in the given encoding.
    """

def __init__(self, f, dialect=csv.excel, encoding="utf-8", **kwds):
    f = UTF8Recoder(f, encoding)
    self.reader = csv.reader(f, dialect=dialect, **kwds)

def next(self):
    row = self.reader.next()
    return [unicode(s, "utf-8") for s in row]

def __iter__(self):
    return self

class UnicodeWriter:
    """
    A CSV writer which will write rows to CSV file "f",
    which is encoded in the given encoding.
"""

def __init__(self, f, dialect=csv.excel, encoding="utf-8", **kwds):
    # Redirect output to a queue
    self.queue = cStringIO.StringIO()
    self.writer = csv.writer(self.queue, dialect=dialect, **kwds)
    self.stream = f
    self.encoder = codecs.getincrementalencoder(encoding)()

def writerow(self, row):
    self.writer.writerow([s.encode("utf-8") for s in row])
    # Fetch UTF-8 output from the queue ...
    data = self.queue.getvalue()
    data = data.decode("utf-8")
    # ... and reencode it into the target encoding
    data = self.encoder.encode(data)
    # write to the target stream
    self.stream.write(data)
    # empty queue
    self.queue.truncate(0)

def writerows(self, rows):
    for row in rows:
        self.writerow(row)

创建并写入csv文件

下面的示例演示创建和写入csv文件。 要使一个动态文件写入器，我们需要导入一个包import csv，然后需要创建一个文件引用的文件实例 Ex:-使用open("D:\sample.csv"，"w"，newline="")作为文件写入器

here if the file does not exist with the mentioned file directory then python will create a same file in the specified directory, and "w" represents write, if you want to read a file then replace "w" with "r" or to append to existing file then "a". newline="" specifies that it removes an extra empty row for every time you create row so to eliminate empty row we use newline="", create some field names(column names) using list like fields=["Names","Age","Class"], then apply to writer instance like writer=csv.DictWriter(file_writer,fieldnames=fields) here using Dictionary writer and assigning column names, to write column names to csv we use writer.writeheader() and to write values we use writer.writerow({"Names":"John","Age":20,"Class":"12A"}) ,while writing file values must be passed using dictionary method , here the key is column name and value is your respective key value

import csv 

with open("D:\\sample.csv","w",newline="") as file_writer:

   fields=["Names","Age","Class"]

   writer=csv.DictWriter(file_writer,fieldnames=fields)

   writer.writeheader()

   writer.writerow({"Names":"John","Age":21,"Class":"12A"})