如何从未处理的 text/data 中提取人的年龄和性别？

Question

我有一个包含文本列表（带行的列）的 CSV 文件，我想从每一行中提取患者的年龄，我不能用 "is digit" 因为还有文本中的一些其他数字。我怎么能做这样的事？谢谢

EXTRA：我也想提取性别 - 患者有时被称为 male/female，有时被称为 man/woman，有时被称为 gentleman/lady。

有没有一种方法可以编写 findall，例如，如果文本是 17 岁，如果后跟 -year-old，请打印我的数字

re.findall("[\d].", '-year-old')

文本中的行示例：

This 23-year-old white female presents with...

...pleasant gentleman who is 42 years old...

...The patient is a 10-1/2-year-old born with...

...A 79-year-old Filipino woman...

Patient, 37,...

我怎样才能得到 age/gender

的列表

即：

Age:

    ['23','42','79','37'...]

Gender:

    ['female','male','male','female','male'...]

Answer 1

您可以使用 regex（正则表达式）轻松做到这一点。

import re

# returns all numbers
age = re.findall("[\d].", your_text)

# returns all words related to gender
gender = re.findall("female|gentleman|woman", your_text)

你可以用字典来处理的性别部分得到你的正确答案

gender_dict = {"male": ["gentleman", "man", "male"],
               "female": ["female", "woman", "girl"]}
gender_aux = []
for g in gender:
    if g in gender_dict['male']:
        gender_aux.append('male')
    elif g in gender_dict['female']:
        gender_aux.append('female')

Answer 2

re_list = [
    '\d*\-year-old',
    '\d*\ year old'
]

matches = []
for r in re_list:
    matches += re.findall( r, 'pleasant gentleman who is 42 years old, This 23-year-old white female presents with')
print(matches)

打印出来：

['23-year-old', '42 year old']

如何从未处理的 text/data 中提取人的年龄和性别？

How to extract age and gender of the person from unprocessed text/data?

python

nlp

pandas

data-science

python-re