使用Python根据特定列拆分CSV文件

Act*_*ary 4 python csv

我是Python初学者,并且已经编写了一些基本脚本。我的最新挑战是根据每行中特定变量的值,将一个非常大的csv文件(10gb +)分成多个较小的文件。

例如,该文件可能如下所示:

Category,Title,Sales
"Books","Harry Potter",1441556
"Books","Lord of the Rings",14251154
"Series", "Breaking Bad",6246234
"Books","The Alchemist",12562166
"Movie","Inception",1573437
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我想将文件拆分为单独的文件:Books.csv,Series.csv,Movie.csv

实际上,将有数百种类别,并且不会对其进行排序。在这种情况下,它们位于第一列,但将来可能不在。

我在网上找到了一些解决方案,但是在Python中却没有。有一个非常简单的AWK命令可以在一行中完成此操作,但是我无法在工作中访问AWK。

我编写了以下有效的代码,但我认为它可能效率很低。有人可以建议如何加快速度吗?

import csv

#Creates empty set - this will be used to store the values that have already been used
filelist = set()

#Opens the large csv file in "read" mode
with open('//directory/largefile', 'r') as csvfile:

    #Read the first row of the large file and store the whole row as a string (headerstring)
    read_rows = csv.reader(csvfile)
    headerrow = next(read_rows)
    headerstring=','.join(headerrow) 

    for row in read_rows:

        #Store the whole row as a string (rowstring)
        rowstring=','.join(row)

        #Defines filename as the first entry in the row - This could be made dynamic so that the user inputs a column name to use
        filename = (row[0])

        #This basically makes sure it is not looking at the header row.
        if filename != "Category":

            #If the filename is not in the filelist set, add it to the list and create new csv file with header row.
            if filename not in filelist:    
                filelist.add(filename)
                with open('//directory/subfiles/' +str(filename)+'.csv','a') as f:
                    f.write(headerstring)
                    f.write("\n")
                    f.close()    
            #If the filename is in the filelist set, append the current row to the existing csv file.     
            else:
                with open('//directory/subfiles/' +str(filename)+'.csv','a') as f:
                    f.write(rowstring)
                    f.write("\n")
                    f.close()
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谢谢!

小智 6

我面临着同样的问题,这让我进入了这份问卷,我能够在 Pandas 中提供它。

逻辑:

  1. 从要拆分的列中提取所有唯一项目。
  2. 将数组转换为列表。
  3. 使用 enumerate 函数遍历列表。https://www.w3schools.com/python/ref_func_enumerate.asp

请检查一次这是否适用于您的情况:

    import pandas as pd

    data = pd.read_csv(**filename**)

    data_category_range = data['Category'].unique()
    data_category_range = data_category_range.tolist()

    for i,value in enumerate(data_category_range):
        data[data['Category'] == value].to_csv(r'Category_'+str(value)+r'.csv',index = False, na_rep = 'N/A')
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Jon*_*nts 5

一种内存有效的方法,一种避免将重新打开文件追加到此处的方法(只要您不打算生成大量打开的文件句柄),就是使用一种dict将类别映射到fileobj。在尚未打开该文件的地方,然后创建它并写入标题,然后始终将所有行写入相应的文件,例如:

import csv

with open('somefile.csv') as fin:    
    csvin = csv.DictReader(fin)
    # Category -> open file lookup
    outputs = {}
    for row in csvin:
        cat = row['Category']
        # Open a new file and write the header
        if cat not in outputs:
            fout = open('{}.csv'.format(cat), 'w')
            dw = csv.DictWriter(fout, fieldnames=csvin.fieldnames)
            dw.writeheader()
            outputs[cat] = fout, dw
        # Always write the row
        outputs[cat][1].writerow(row)
    # Close all the files
    for fout, _ in outputs.values():
        fout.close()
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