使用Python的csv模块写入特定单元格

Question

我需要在我的csv文件中写入一个特定单元格的值（比如第8个单元格）。我看到有一个 csvwriter.writerow(row) 方法可以写入整行数据，但我没有找到可以直接写入特定单元格值的方法。

Answer 1

我同意，这确实让人烦恼。我最后选择了继承csv.DictReader这个类。这样可以在单元格中直接查找、编辑和导出数据。我把代码放在了activestate上，链接是：直接在csv中查找、操作和导出

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')

Answer 2

假设你有一个叫做 mylist.csv 的文件，里面有以下几行内容：

a, b, c, d

e, f, g, h

i, j, k, l

如果你想把 'h' 改成 'X'，可以使用下面的代码，但需要先导入 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()

如果你想修改每一行的某一列，只需添加一个循环来逐行处理。

Answer 3

csv模块可以用来读写csv文件，但它不支持直接修改特定的单元格。

即使是你提到的csvwriter.writerow(row)方法，也不能让你选择并覆盖某一特定的行。这个方法只是把row参数写入到文件中，实际上它只是把一行数据添加到与这个写入器相关的csv文件里。

不过，不要因此而放弃使用csv模块，它使用起来很简单，利用它提供的基本功能，你可以相对容易地实现你想要的更高级的功能。

比如，看看下面这个csv文件：

1,2,3,four,5
1,2,3,four,5
1,2,3,four,5

在这个文件中，单词four在第三列（第四列，但行就像一个列表，所以索引是从零开始的），我们可以用下面的程序轻松地把它更新为数字4：

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()

这样就会得到以下输出：

1,2,3,4,5
1,2,3,4,5
1,2,3,4,5

当然，创建一个通用的函数来识别和更新特定的行和列会稍微复杂一些，但其实并不难，因为在Python中操作csv文件就是在操作一个列表的序列。