Question

我是Python初学者，并制作了一些基本脚本。我的最新挑战是采用一个非常大的csv文件（10gb +）并根据每行中特定变量的值将其拆分为许多较小的文件。

例如，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

我想将文件拆分为单独的文件： Books.csv，Series.csv，Movie.csv

实际上会有数百个类别，并且不会对它们进行排序。在这种情况下，它们位于第一列，但将来它们可能不是。

我在网上找到了一些解决方案，但在Python中却没有。有一个非常简单的AWK命令可以在一行中执行此操作，但我无法在工作中访问AWK。

我已经编写了以下可行的代码，但我认为这可能非常低效。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()

谢谢！

Answer 1

我正面临着同样的问题，这使我无法参加这份问卷，并且能够在大熊猫中提供。

逻辑：

从您要拆分的列中提取所有唯一项。
将数组转换为列表。
使用枚举功能遍历列表。 https://www.w3schools.com/python/ref_func_enumerate.asp

请检查一次是否适合您的情况：

    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')

Answer 2

一种内存有效的方法和避免重新打开要附加的文件的方法（只要你不打算生成大量的打开文件句柄）就是使用dict映射类别到fileobj。如果该文件尚未打开，则创建它并编写标题，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()

使用Python基于特定列拆分csv文件

2 个答案: