我必须在我的csv文件中为特定单元格（比如第8个单元格）写一个值。
我可以看到有一个csvwriter.writerow(row)方法来编写整行，但我没有看到任何东西要写一个特定单元格的值。
答案 0 :(得分：10)
csv module提供了读取和写入csv文件的工具，但不允许修改特定的单元格。
即使您在问题中突出显示的csvwriter.writerow(row)方法也不允许您识别和覆盖特定行。而是将row参数写入编写器的文件对象，实际上它只是附加了与编写器关联的csv文件的行。
不要被劝阻使用csv module，它使用起来很简单，只要您可以相对轻松地实现您正在寻找的更高级别的功能。
例如，请查看以下csv文件：
1,2,3,four,5
1,2,3,four,5
1,2,3,four,5
单词four在第3列（第四列，但是一行只是一个列表，因此索引基于零），这可以很容易地更新为包含数字4以及以下内容程序：
import csv
in_file = open("d:/in.csv", "rb")
reader = csv.reader(in_file)
out_file = open("d:/out.csv", "wb")
writer = csv.writer(out_file)
for row in reader:
row[3] = 4
writer.writerow(row)
in_file.close()
out_file.close()
导致输出：
1,2,3,4,5
1,2,3,4,5
1,2,3,4,5
当然，创建一些允许识别和更新特定行和列的通用函数是一项更多工作，但在Python中操作csv文件只是操作一系列列表。
答案 1 :(得分：1)
我同意，这很烦人。我结束了csv.DictReader的子类化。这允许在适当的位置进行基于单元格的查找编辑和转储。我在activestate上发布了代码：In place csv lookup, manipulation and export
import csv, collections, copy
"""
# CSV TEST FILE 'test.csv'
TBLID,DATETIME,VAL
C1,01:01:2011:00:01:23,5
C2,01:01:2012:00:01:23,8
C3,01:01:2013:00:01:23,4
C4,01:01:2011:01:01:23,9
C5,01:01:2011:02:01:23,1
C6,01:01:2011:03:01:23,5
C7,01:01:2011:00:01:23,6
C8,01:01:2011:00:21:23,8
C9,01:01:2011:12:01:23,1
#usage (saving this cose as CustomDictReader.py)
>>> import CustomDictReader
>>> import pprint
>>> test = CustomDictReader.CSVRW()
>>> success, thedict = test.createCsvDict('TBLID',',',None,'test.csv')
>>> pprint.pprint(dict(thedict))
{'C1': OrderedDict([('TBLID', 'C1'), ('DATETIME', '01:01:2011:00:01:23'), ('VAL', '5')]),
'C2': OrderedDict([('TBLID', 'C2'), ('DATETIME', '01:01:2012:00:01:23'), ('VAL', '8')]),
'C3': OrderedDict([('TBLID', 'C3'), ('DATETIME', '01:01:2013:00:01:23'), ('VAL', '4')]),
'C4': OrderedDict([('TBLID', 'C4'), ('DATETIME', '01:01:2011:01:01:23'), ('VAL', '9')]),
'C5': OrderedDict([('TBLID', 'C5'), ('DATETIME', '01:01:2011:02:01:23'), ('VAL', '1')]),
'C6': OrderedDict([('TBLID', 'C6'), ('DATETIME', '01:01:2011:03:01:23'), ('VAL', '5')]),
'C7': OrderedDict([('TBLID', 'C7'), ('DATETIME', '01:01:2011:00:01:23'), ('VAL', '6')]),
'C8': OrderedDict([('TBLID', 'C8'), ('DATETIME', '01:01:2011:00:21:23'), ('VAL', '8')]),
'C9': OrderedDict([('TBLID', 'C9'), ('DATETIME', '01:01:2011:12:01:23'), ('VAL', '1')])}
>>> thedict.keys()
['C1', 'C2', 'C3', 'C4', 'C5', 'C6', 'C7', 'C8', 'C9']
>>> thedict['C2']['VAL'] = "BOB"
>>> pprint.pprint(dict(thedict))
{'C1': OrderedDict([('TBLID', 'C1'), ('DATETIME', '01:01:2011:00:01:23'), ('VAL', '5')]),
'C2': OrderedDict([('TBLID', 'C2'), ('DATETIME', '01:01:2012:00:01:23'), ('VAL', 'BOB')]),
'C3': OrderedDict([('TBLID', 'C3'), ('DATETIME', '01:01:2013:00:01:23'), ('VAL', '4')]),
'C4': OrderedDict([('TBLID', 'C4'), ('DATETIME', '01:01:2011:01:01:23'), ('VAL', '9')]),
'C5': OrderedDict([('TBLID', 'C5'), ('DATETIME', '01:01:2011:02:01:23'), ('VAL', '1')]),
'C6': OrderedDict([('TBLID', 'C6'), ('DATETIME', '01:01:2011:03:01:23'), ('VAL', '5')]),
'C7': OrderedDict([('TBLID', 'C7'), ('DATETIME', '01:01:2011:00:01:23'), ('VAL', '6')]),
'C8': OrderedDict([('TBLID', 'C8'), ('DATETIME', '01:01:2011:00:21:23'), ('VAL', '8')]),
'C9': OrderedDict([('TBLID', 'C9'), ('DATETIME', '01:01:2011:12:01:23'), ('VAL', '1')])}
>>> test.updateCsvDict(thedict)
>>> test.createCsv('wb')
"""
class CustomDictReader(csv.DictReader):
"""
override the next() function and use an
ordered dict in order to preserve writing back
into the file
"""
def __init__(self, f, fieldnames = None, restkey = None, restval = None, dialect ="excel", *args, **kwds):
csv.DictReader.__init__(self, f, fieldnames = None, restkey = None, restval = None, dialect = "excel", *args, **kwds)
def next(self):
if self.line_num == 0:
# Used only for its side effect.
self.fieldnames
row = self.reader.next()
self.line_num = self.reader.line_num
# unlike the basic reader, we prefer not to return blanks,
# because we will typically wind up with a dict full of None
# values
while row == []:
row = self.reader.next()
d = collections.OrderedDict(zip(self.fieldnames, row))
lf = len(self.fieldnames)
lr = len(row)
if lf < lr:
d[self.restkey] = row[lf:]
elif lf > lr:
for key in self.fieldnames[lr:]:
d[key] = self.restval
return d
class CSVRW(object):
def __init__(self):
self.file_name = ""
self.csv_delim = ""
self.csv_dict = collections.OrderedDict()
def setCsvFileName(self, name):
"""
@brief stores csv file name
@param name- the file name
"""
self.file_name = name
def getCsvFileName(self):
"""
@brief getter
@return returns the file name
"""
return self.file_name
def getCsvDict(self):
"""
@brief getter
@return returns a deep copy of the csv as a dictionary
"""
return copy.deepcopy(self.csv_dict)
def clearCsvDict(self):
"""
@brief resets the dictionary
"""
self.csv_dict = collections.OrderedDict()
def updateCsvDict(self, newCsvDict):
"""
creates a deep copy of the dict passed in and
sets it to the member one
"""
self.csv_dict = copy.deepcopy(newCsvDict)
def createCsvDict(self,dictKey, delim, handle = None, name = None, readMode = 'rb', **kwargs):
"""
@brief create a dict from a csv file where:
the top level keys are the first line in the dict, overrideable w/ **kwargs
each row is a dict
each row can be accessed by the value stored in the column associated w/ dictKey
that is to say, if you want to index into your csv file based on the contents of the
third column, pass the name of that col in as 'dictKey'
@param dictKey - row key whose value will act as an index
@param delim - csv file deliminator
@param handle - file handle (leave as None if you wish to pass in a file name)
@param name - file name (leave as None if you wish to pass in a file handle)
@param readMode - 'r' || 'rb'
@param **kwargs - additional args allowed by the csv module
@return bool - SUCCESS|FAIL
"""
self.csv_delim = delim
try:
if isinstance(handle, file):
self.setCsvFileName(handle.name)
reader = CustomDictReader(handle, delim, **kwargs)
else:
if None == name:
name = self.getCsvFileName()
else:
self.setCsvFileName(name)
reader = CustomDictReader(open(name, readMode), delim, **kwargs)
for row in reader:
self.csv_dict[row[dictKey]] = row
return True, self.getCsvDict()
except IOError:
return False, 'Error opening file'
def createCsv(self, writeMode, outFileName = None, delim = None):
"""
@brief create a csv from self.csv_dict
@param writeMode - 'w' || 'wb'
@param outFileName - file name || file handle
@param delim - csv deliminator
@return none
"""
if None == outFileName:
outFileName = self.file_name
if None == delim:
delim = self.csv_delim
with open(outFileName, writeMode) as fout:
for key in self.csv_dict.values():
fout.write(delim.join(key.keys()) + '\n')
break
for key in self.csv_dict.values():
fout.write(delim.join(key.values()) + '\n')
答案 2 :(得分：1)
使用xlwt模块，可以对电子表格执行多项操作。可以写入Excel中的特定或特定单元格。
require_once(__DIR__.'/core/file.php');
答案 3 :(得分：0)
假设您有一个名为mylist.csv的csv文件，其中包含以下行：
a, b, c, d
e, f, g, h
i, j, k, l
如果要修改'h'成为'X'，可以使用此代码，需要导入csv模块：
f = open('mylist.csv', 'r')
reader = csv.reader(f)
mylist = list(reader)
f.close()
mylist[1][3] = 'X'
my_new_list = open('mylist.csv', 'w', newline = '')
csv_writer = csv.writer(my_new_list)
csv_writer.writerows(mylist)
my_new_list.close()
如果要修改每一行的特定列，只需添加for循环即可迭代。