在python中使用csv模塊寫入特定單元格

[英]Writing to a particular cell using csv module in python


I have to write a value to a particular cell (say the 8th cell) in my csv file. I can see there is a csvwriter.writerow(row) method to write an entire row, but I am not seeing anything to write a value to a particular cell.

我必須在我的csv文件中為特定單元格(比如第8個單元格)寫一個值。我可以看到有一個csvwriter.writerow(row)方法來寫一整行,但我沒有看到任何東西要寫一個特定的單元格的值。

3 个解决方案

#1


11  

The csv module provides facilities to read and write csv files but does not allow the modification specific cells in-place.

csv模塊提供了讀取和寫入csv文件的工具,但不允許在適當位置修改特定單元。

Even the csvwriter.writerow(row) method you highlight in your question does not allow you to identify and overwrite a specific row. Rather it writes the row parameter to the writer’s file object, in effect it simply appends a row the csv file associated with the writer.

即使您在問題中突出顯示的csvwriter.writerow(行)方法也不允許您識別和覆蓋特定行。而是將row參數寫入writer的文件對象,實際上它只是在一行中附加與writer關聯的csv文件。

Do not be dissuaded from using the csv module though, it is simple to use and with the primitives provided you could implement the higher level functionality you are looking for relatively easily.

不要勸阻使用csv模塊,它使用起來很簡單,如果你可以相對容易地實現你正在尋找的更高級別的功能。

For example take a look at the following csv file:

例如,看看以下csv文件:

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

The word four is in column 3 (the fourth column but a row is just a list so the indexing is zero based), this can be easily updated to contain the digit 4 with the following program:

單詞4在第3列(第四列,但是一行只是一個列表,因此索引基於零),這可以很容易地更新為包含帶有以下程序的數字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()

Resulting in the output:

導致輸出:

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

Granted creating some generic function that allows specific rows and columns to be identified and updated is a little more work, but not much more as manipulating a csv file in Python is just manipulating a sequence of lists.

授予創建一些通用函數,允許識別和更新特定的行和列是一項更多的工作,但在Python中操縱csv文件只是操作一系列列表。

#2


1  

I agree, this is annoying. I wound up subclassing csv.DictReader. This allows for cell based lookup edit in place, and dump. I have the code posted on activestate: In place csv lookup, manipulation and export

我同意,這很煩人。我結束了csv.DictReader的子類化。這允許在適當位置進行基於單元格的查找編輯和轉儲。我在activestate上發布了代碼:就地csv查找,操作和導出

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')

#3


0  

suppose you have a csv file called mylist.csv with following lines:

假設您有一個名為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

if you want to modify 'h' to become 'X', can use this code, need to import csv module:

如果要修改'h'成為'X',可以使用此代碼,需要導入csv模塊:

    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()

If you want to modify a particular column for each row, just add the for loop to iterate.

如果要修改每行的特定列,只需添加for循環以進行迭代。


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