在Python中使用csv模塊寫入特定單元格

Question

我必須在我的csv文件中爲特定單元格寫入一個值（比如第8個單元格）。 我可以看到有一個csvwriter.writerow(row)方法來寫整行，但我沒有看到任何東西寫入一個特定的單元格的值。

Answer 1

csv module提供了讀寫csv文件的工具，但不允許修改特定的單元格就地。

即使您在問題中突出顯示的csvwriter.writerow(row)方法也不允許您識別並覆蓋特定的行。而是將row參數寫入作者的文件對象，實際上它只是將與作者相關聯的csv文件附加到一行。

不要被勸阻使用csv module雖然它使用起來很簡單，並且提供的原語可以實現您比較容易找到的更高級別的功能。

例如看看下面的CSV文件：

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

字four是第3列（第四列，但一排就是這麼的索引是從零開始的列表），這樣可以能夠容易地更新爲包含數字4與以下程序：

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() 

在輸出所得：

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

授予創建一些通用函數，允許識別和更新特定的行和列是多一點工作，但沒有太多更多，因爲在Python中操作csv文件只是操縱一系列列表。

Answer 2

我同意，這很煩人。我完成了csv.DictReader的子類化。這允許基於單元格的查找編輯和轉儲。我已經張貼在ActiveState公司代碼：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') 

Answer 3

假設你有一個名爲mylist.csv csv文件具有以下行：

a, b, c, d 

e, f, g, h 

i, j, k, l 

，如果你想修改「H」，成爲「X」 ，可以使用此代碼，需要將導入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() 

如果要修改於各行的特定列，只需添加for循環迭代。