熊猫引用参数

Question

我试图确切地了解pandas.read_csv模块中quoting和doublequote的含义。假设我有以下数据：

['name' ,'age' ,'position']
['tom', 14, 'vp']
['jared', 100, 'head, sales']

熊猫有三个quoting选项：

1. QUOTE_MINIMAL（0）[默认]

2. QUOTE_ALL（1）

3. QUOTE_NONNUMERIC（2）

4. QUOTE_NONE（3）

https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html

如果quotechar是"，以上四个参数将如何解释以上数据？

Answer 1

您可以尝试执行以下操作，以与csv作家进行测试：

import csv
DATA = [
    ['name' ,'age' ,'position'],
    ['tom', 14, 'vp'],
    ['jared', 100, 'head, sales'],
]

with open('test_min.csv', 'w') as csvfile:
    writer = csv.writer(csvfile, delimiter=',',quotechar='"', quoting=csv.QUOTE_MINIMAL)
    for row in DATA:
        writer.writerow(row)

with open('test_all.csv', 'w') as csvfile:
    writer = csv.writer(csvfile, delimiter=',',quotechar='"', quoting=csv.QUOTE_ALL)
    for row in DATA:
        writer.writerow(row)

with open('test_nonnumeric.csv', 'w') as csvfile:
    writer = csv.writer(csvfile, delimiter=',',quotechar='"', quoting=csv.QUOTE_NONNUMERIC)
    for row in DATA:
        writer.writerow(row)

with open('test_quotenone.csv', 'w') as csvfile:
    writer = csv.writer(csvfile, delimiter=',',quotechar='"', quoting=csv.QUOTE_NONE)
    for row in DATA:
        writer.writerow(row)

这是您将看到的：

1. QUOTE_NONE

   name,age,position tom,14,vp

   注释：无效的输出，将需要一个转义字符集。

2. QUOTE_NONNUMERIC

   "name","age","position" "tom",14,"vp" "jared",100,"head, sales"

   注意事项：请注意，14和100并未转义。

3. QUOTE_MINIMUM

   name,age,position tom,14,vp jared,100,"head, sales"

   注释：仅引用head, sales，因为它是有问题的字段。

4. QUOTE_ALL

   "name","age","position" "tom","14","vp" "jared","100","head, sales"

   注释：无论类型如何，所有内容都被引用。