熊猫引证

Question

我正试图准确地理解quoting和doublequote在pandas.read_csv模块中的含义。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)

csv.html

如果quotechar是"，那么上述四个参数将如何解释上述数据？

Answer 1

您可以尝试这样做来对csv作者进行测试：

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)

下面是你会看到的：

1. QUOTE_NONE name,age,position tom,14,vp Notes：无效输出，将需要转义字符集。
2. QUOTE_NONNUMERIC "name","age","position" "tom",14,"vp" "jared",100,"head, sales" Notes：注意14和100没有转义。
3. QUOTE_MINIMUM name,age,position tom,14,vp jared,100,"head, sales" Notes：将只引用head, sales，因为它是违规字段。
4. QUOTE_ALL "name","age","position" "tom","14","vp" "jared","100","head, sales" Notes：所有内容都引用，不管类型如何。