如何使用Python清理大型格式错误的CSV文件

2024-06-01 14:49:10 发布

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我正在尝试使用Python2.7.5清理格式错误的CSV文件。CSV文件相当大(超过1GB)。文件的第一行正确地列出了列标题,但之后每个字段都在一个新行上(除非它是空的),有些字段是多行的。多行字段不被引号包围,但在输出中需要被引号包围。列的数目是静态的和已知的。提供的示例输入中的模式在整个文件长度内重复。

输入文件(示例):

Hostname,Username,IP Addresses,Timestamp,Test1,Test2,Test3
my_hostname
,my_username
,10.0.0.1
192.168.1.1
,2015-02-11 13:41:54 -0600
,,true
,false
my_2nd_hostname
,my_2nd_username
,10.0.0.2
192.168.1.2
,2015-02-11 14:04:41 -0600
,true
,,false

期望输出:

Hostname,Username,IP Addresses,Timestamp,Test1,Test2,Test3
my_hostname,my_username,"10.0.0.1 192.168.1.1",2015-02-11 13:41:54 -0600,,true,false
my_2nd_hostname,my_2nd_username,"10.0.0.2 192.168.1.2",2015-02-11 14:04:41 -0600,true,,false

我走了两条路,解决了其中一个问题,但我发现它不能处理格式错误的数据的另一个方面。如果有人能帮我找出一个有效的方法来清理这个文件,我将不胜感激。

谢谢

编辑

我从不同的路径得到了一些代码片段,但这里是当前的迭代。这不漂亮,只是一堆黑客试图解决这个问题。

import csv

inputfile = open('input.csv', 'r')
outputfile_1 = open('output.csv', 'w')

counter = 1
for line in inputfile:
    #Skip header row
    if counter == 1:
        outputfile_1.write(line)
        counter = counter + 1
    else:
        line = line.replace('\r', '').replace('\n', '')
        outputfile_1.write(line)

inputfile.close()
outputfile_1.close()

with open('output.csv', 'r') as f:
    text = f.read()

    comma_count = text.count(',') #comma_count/6 = total number of rows

    #need to insert a newline after the field contents after every 6th comma
    #unfortunately the last field of the row and the first field of the next row are now rammed up together becaue of the newline replaces above...
    #then process as normal CSV

    #one path I started to go down... but this isn't even functional
    groups = text.split(',')

    counter2 = 1
    while (counter2 <= comma_count/6):
        line = ','.join(groups[:(6*counter2)]), ','.join(groups[(6*counter2):])
        print line
        counter2 = counter2 + 1

编辑2

感谢@DSM和@Ryan Vincent让我走上正轨。利用他们的想法,我做了下面的代码,这似乎纠正了我错误的CSV格式。我相信还有很多地方需要改进,我很乐意接受。

import csv
import re

outputfile_1 = open('output.csv', 'wb')
wr = csv.writer(outputfile_1, quoting=csv.QUOTE_ALL)

with open('input.csv', 'r') as f:
    text = f.read()
    comma_indices = [m.start() for m in re.finditer(',', text)] #Find all the commas - the fields are between them

    cursor = 0
    field_counter = 1
    row_count = 0
    csv_row = []

    for index in comma_indices:
        newrowflag = False

        if "\r" in text[cursor:index]:
            #This chunk has two fields, the last of one row and first of the next
            next_field=text[cursor:index].split('\r')
            next_field_trimmed = next_field[0].replace('\n',' ').rstrip().lstrip()
            csv_row.extend([next_field_trimmed]) #Add the last field of this row

            #Reset the cursor to be in the middle of the chuck (after the last field and before the next)
            #And set a flag that we need to start the next csvrow before we move on to the next comma index
            cursor = cursor+text[cursor:index].index('\r')+1
            newrowflag = True
        else:
            next_field_trimmed = text[cursor:index].replace('\n',' ').rstrip().lstrip()
            csv_row.extend([next_field_trimmed])

            #Advance the cursor to the character after the comma to start the next field
            cursor = index + 1

        #If we've done 7 fields then we've finished the row
        if field_counter%7==0:
            row_count = row_count + 1
            wr.writerow(csv_row)

            #Reset
            csv_row = []

            #If the last chunk had 2 fields in it...
            if newrowflag:
                next_field_trimmed = next_field[1].replace('\n',' ').rstrip().lstrip()
                csv_row.extend([next_field_trimmed])
                field_counter = field_counter + 1

        field_counter = field_counter + 1
    #Write the last row
    wr.writerow(csv_row)

outputfile_1.close()

# Process output.csv as normal CSV file...    

Tags: ofcsvthetextfieldindexmycount
2条回答

这是关于我将如何处理这个问题的评论。

对于每一行:

我可以很容易地识别某些组的开始和结束:

  • 主机名-只有一个
  • 用户名-阅读这些直到遇到不象用户名的内容(逗号分隔)
  • ip地址-读取这些直到您遇到一个时间戳-用模式匹配标识-请注意这些是用空格而不是逗号分隔的。组的结尾由后面的逗号标识。
  • 时间戳-易于识别模式匹配
  • test1,test2,test3-一定要以逗号分隔字段的形式出现

注:我会使用“模式”匹配,使我能够确定我在正确的地方有正确的东西。它可以更快地发现错误。

从您的数据摘录看来,任何以逗号开头的行都需要连接到前一行,任何以逗号以外的任何行都将标记新行。

如果是这种情况,那么可以使用以下代码清理CSV文件,以便标准库csv解析器可以处理它。

#!/usr/bin/python
raw_data = 'somefilename.raw'
csv_data = 'somefilename.csv'
with open(raw_data, 'Ur') as inp, open(csv_data, 'wb') as out:
    row = list()
    for line in inp:
        line.rstrip('\n')
        if line.startswith(','):
            row.append(line)
        else:
            out.write(''.join(row)+'\n')
            row = list()
            row.append(line))
    # Don't forget to write the last row!
    out.write(''.join(row)+'\n')

这是一个微型的国家机器。。。将行累加到每一行,直到找到一行不以逗号开头,然后写入前一行,依此类推。

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