You could use the string.join method in this case.

Split over a few of lines for clarity – here’s an interactive session

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

Or as a single line

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

However, you may have a problem is your strings have got embedded quotes. If this is the case you’ll need to decide how to escape them.

The CSV module can take care of all of this for you, allowing you to choose between various quoting options (all fields, only fields with quotes and seperators, only non numeric fields, etc) and how to esacpe control charecters (double quotes, or escaped strings). If your values are simple, string.join will probably be OK but if you’re having to manage lots of edge cases, use the module available.

Use python’s csv module for reading and writing comma or tab-delimited files. The csv module is preferred because it gives you good control over quoting.

For example, here is the worked example for you:

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)

Produces:

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

Here is a secure version of Alex Martelli’s:

import csv

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

you should use the CSV module for sure , but the chances are , you need to write unicode . For those Who need to write unicode , this is the class from example page , that you can use as a util module:

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)

The best option I’ve found was using the savetxt from the numpy module:

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

In case you have multiple lists that need to be stacked

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

Here is another solution that does not require the csv module.

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

Example :

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

However, if the initial list contains some “, they will not be escaped. If it is required, it is possible to call a function to escape it like that :

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

For another approach, you can use DataFrame in pandas:
And it can easily dump the data to csv just like the code below:

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

Jupyter notebook

Let’s say that your list name is A

Then you can code the following and you will have it as a csv file (columns only!)

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

This solutions sounds crazy, but works smooth as honey

import csv

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

The file is being written by csvwriter hence csv properties are maintained i.e. comma separated.
The delimiter helps in the main part by moving list items to next line, each time.

To create and write into a csv file

The below example demonstrate creating and writing a csv file.
to make a dynamic file writer we need to import a package import csv, then need to create an instance of the file with file reference
Ex:- with open(“D:sample.csv”,”w”,newline=””) as file_writer

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"})

Here is working copy-paste example for Python 3.x with options to define your own delimiter and quote char.

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)

This will generate employee_file.csv that looks like this:

"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.

For those looking for less complicated solution. I actually find this one more simplisitic solution that will do similar job:

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)

Hope this helps as well.