使用 Python 3 将大型 CSV 文件转换为 excel

Question

这是我将 CSV 文件隐蔽到 .xlsx 文件的代码，对于小尺寸 CSV 文件，此代码工作正常，但当我尝试处理大尺寸 CSV 文件时，它显示错误。

import os
import glob
import csv
from xlsxwriter.workbook import Workbook

for csvfile in glob.glob(os.path.join('.', 'file.csv')):
    workbook = Workbook(csvfile[:-4] + '.xlsx')
    worksheet = workbook.add_worksheet()
    with open(csvfile, 'r', encoding='utf8') as f:
        reader = csv.reader(f)
        for r, row in enumerate(reader):
            for c, col in enumerate(row):
                worksheet.write(r, c, col)
    workbook.close()

错误是

File "CsvToExcel.py", line 12, in <module>
for r, row in enumerate(reader):
_csv.Error: field larger than field limit (131072)
Exception ignored in: <bound method Workbook.__del__ of 
<xlsxwriter.workbook.Workbook object at 0x7fff4e731470>>
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/xlsxwriter/workbook.py", line 
153, in __del__
Exception: Exception caught in workbook destructor. Explicit close() may be 
required for workbook.

Answer 1

在使用大文件时，最好使用“constant_memory”来控制内存使用，例如：

workbook = Workbook(csvfile + '.xlsx', {'constant_memory': True}).

参考：xlsxwriter.readthedocs.org/en/latest/working_with_memory.htm‌​l

Answer 2

我发现了带有熊猫包的新代码，这个代码现在可以正常工作了

import pandas
data = pandas.read_csv('Documents_2/AdvMedcsv.csv') 
data = data.groupby(lambda x: data['research_id'][x]).first() 
writer = pandas.ExcelWriter('Documents_2/AdvMed.xlsx',engine='xlsxwriter')data.to_excel(writer) 
writer.save()