你可以用绳子。方法。

为了清晰起见，分成几行——这是一个交互式会话

>>> a = ['a','b','c']
>>> first = '", "'.join(a)
>>> second = '"%s"' % first
>>> print second
"a", "b", "c"

或者是一条直线

>>> print ('"%s"') % '", "'.join(a)
"a", "b", "c"

然而，你可能有一个问题是你的字符串有嵌入引号。如果是这种情况，你需要决定如何逃离它们。

CSV模块可以为您处理所有这些，允许您在各种引用选项(所有字段，仅包含引号和分隔符的字段，仅包含非数字字段，等等)之间进行选择，以及如何转义控制字符(双引号，或转义字符串)。如果你的值是简单的，字符串。join可能没问题，但如果你必须管理大量的边缘情况，使用可用的模块。

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)

使用python的csv模块来读写逗号或制表符分隔的文件。csv模块是首选，因为它可以很好地控制引用。

例如，下面是你的工作示例:

import csv
data = ["value %d" % i for i in range(1,4)]

out = csv.writer(open("myfile.csv","w"), delimiter=',',quoting=csv.QUOTE_ALL)
out.writerow(data)

生产:

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

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)

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)

我发现最好的选择是使用numpy模块中的savetxt:

import numpy as np
np.savetxt("file_name.csv", data1, delimiter=",", fmt='%s', header=header)

以防你有多个需要堆叠的列表

np.savetxt("file_name.csv", np.column_stack((data1, data2)), delimiter=",", fmt='%s', header=header)

下面是另一个不需要csv模块的解决方案。

print ', '.join(['"'+i+'"' for i in myList])

例子:

>>> myList = [u'value 1', u'value 2', u'value 3']
>>> print ', '.join(['"'+i+'"' for i in myList])
"value 1", "value 2", "value 3"

但是，如果初始列表包含一些“，则不会转义。如果需要，可以调用一个函数像这样转义它:

print ', '.join(['"'+myFunction(i)+'"' for i in myList])

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)

木星笔记本

假设你的列表名是A

然后您可以编写以下代码，并将其作为csv文件(仅限列!)

R="\n".join(A)
f = open('Columns.csv','w')
f.write(R)
f.close()

这个解决方案听起来很疯狂，但效果非常好

import csv

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

文件是由csvwriter写入的，因此csv属性被维护，即逗号分隔。 分隔符通过每次将列表项移动到下一行来帮助主要部分。

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"})

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.

对于那些寻找简单解决方案的人。实际上，我发现了一个更简单的解决方案，可以完成类似的工作:

import pandas as pd
a = ['a','b','c'] 
df = pd.DataFrame({'a': a})
df= df.set_index('a').T
df.to_csv('list_a.csv', index=False)

希望这也能有所帮助。