如何在Python中从CSV文件中删除空的双引号？

Question

如何使用Python从CSV文件中删除空的双引号？

这是文件的当前外观：

"text","more text","","other text","","text"

这是我想要的样子：

"text","more text",,"other text",,"text"

Answer 1

我认为最好的解决方案是使用csv.reader中的quotechar选项，然后过滤空白字段：

import csv

with open('test.csv', newline='') as csvf:
    for row in csv.reader(csvf, delimiter=',', quotechar='"'):
        row = filter(lambda v: v, row)
        # Now row is just an iterator containing non-empty strings
        # You can use it as you please, for example: 
        print(', '.join(row))

如果不是要删除空字段，您需要将它们替换为给定值（例如None）：

import csv

def read(file, placeholder=None):
    with open(file, newline='') as csvf:
        for row in csv.reader(csvf, delimiter=',', quotechar='"'):
            yield [v if v else placeholder for v in row]

for row in read('test.csv'):
    pass # Do something with row

例如，如果您需要使用双引号将其打印到标准输出（这是一个愚蠢的示例）：

for row in read('test.csv'):
    print(', '.join(f'"{v}"' if v else '' for v in row))

Answer 2

您可以尝试：

>>> s=""""text","more text","","other text","","text" """
>>> s
'"text","more text","","other text","","text" '
>>> s.replace('""','')
'"text","more text",,"other text",,"text" '

Answer 3

lambda函数和一些熊猫魔术的组合将大大提高速度，一旦加载了DataFrame，您将获得类似的东西

然后，您只需要编写一个lambda函数

replacer = lambda x: x.replace('""','')
df = df.apply(replacer)

您正在寻找哪个操作并给您

然后只需使用df.to_csv(filepathAsStr)将更改保存到磁盘上或继续进行所需的操作，df.apply()即可跨数据帧并行化，因此与简单的str.replace或任何其他dotnet new angular -o myproj使用串行计算的方法。