RegEx将地址分为三个不同的系列[第1部分] [英] RegEx to split address into three distinct Series [Part 1]
问题描述
我正在使用包含客户信息的数据集进行实验/学习Python.
I'm experimenting/learning Python with a data set containing customers information.
DataFrame结构如下(这些都是记录):
The DataFrame structure is the following (these are made up records):
import pandas as pd
import numpy as np
df = pd.DataFrame({'cus_name' : ['James', 'Mary', 'David', 'Linda', 'George', 'Jennifer', 'John', 'Maria', 'Charles', 'Helen'],
'address' : ['Main St 59', 'Yellow Av 11 b.F1', 'Terrazzo Way 100-102', np.nan, 'Hamilton St 159 b.A/B', np.nan, 'Henry St 7 D', 'Mc-Kenzie Av 40P b.1', 'Neptune Av 14 15 b.G', np.nan ],
'postal_code' : [1410, 1210, 1020, np.nan, 1310, np.nan, 1080, 1190, 1040, np.nan],
})
print(df)
cus_name address postal_code
0 James Main St 59 1410.0
1 Mary Yellow Av 11 b.F1 1210.0
2 David Terrazzo Way 100-102 1020.0
3 Linda NaN NaN
4 George Hamilton St 159 b.A/B 1310.0
5 Jennifer NaN NaN
6 John Henry St 7 D 1080.0
7 Maria Mc-Kenzie Av 40P b.1 1190.0
8 Charles Neptune Av 14 15 b.G 1040.0
9 Helen NaN NaN
我对address系列特别感兴趣.具体来说，我的目标是将街道，数字和盒子的信息拆分"为三个不同的系列.
I'm particularly interested in the address Series. Specifically, my goal is to "split" the information of the street, number, and box into three distinct Series.
例如，转换后，第一个和第七个记录/行应如下所示:
For instance, after the transformation, the first and seventh record/row should look like this:
| cus_name | street | number | box | postal_code |
|----------|--------------|--------|-----|-------------|
| James | Main St | 59 | NaN | 1410 |
| Maria | Mc-Kenzie Av | 40P | 1 | 1190.0 |
起初，我不知道如何解决这个问题.在这里进行了一些研究之后，我发现了一些有趣的，使用正则表达式的相关文章.
At first, I had no idea how to tackle this problem. After doing some research here, I found some interesting related posts that use regular expressions.
由于我不是Python专家(也不是正则表达式)，所以我认为我可以从确定address系列中的模式开始.实际上，每个地址都有以下模式:
Since I'm no expert in Python (nor regular expressions), I thought I could start by identifying the pattern in the address Series. In fact, each address has the following pattern:
-
位于字符串开头的街道部分.它由一个或多个用空格字符或破折号分隔的单词组成(例如
Mc-Kenzie Av)；
The street part which is located at the beginning of the string. It is composed of one or more words separated by a white-space character or a dash (e.g.
Mc-Kenzie Av);
位于字符串中间的 number 部分.它由一个或多个字母数字单词组成，这些单词由空格字符或破折号分隔(例如100-102，7 D)；
The number part which is located in the middle of the string. It is composed of one or more alpha-numeric words separated by a white-space character or a dash (e.g. 100-102, 7 D);
位于字符串末尾的框部分.它始终紧随b.个字符，由一个包含字母数字字符以及可能包含某些特殊字符(例如A/B，F1)的单词组成.
The box part which is located at the end of the string. It always immediately follows the b.characters and is composed of one word containing alpha-numeric characters and possibly some special characters (e.g. A/B, F1).
我正在寻求帮助，以使用正则表达式(如果正则表达式是解决方案)实现期望的目标.
I'm asking for help to achieve my desired goal using regular expressions (if regex is the solution).
推荐答案
另一种正则表达式方法:
Another regex approach:
In [913]: df[['street', 'number', 'box']] = df.address.str.extract(r'(\D+)\s+(\d+[\s-]?(?!b)\w*)(?:\s+b\.)?(\S+)?', expand=True)
In [914]: df
Out[914]:
cus_name address postal_code street number box
0 James Main St 59 1410.0 Main St 59 NaN
1 Mary Yellow Av 11 b.F1 1210.0 Yellow Av 11 F1
2 David Terrazzo Way 100-102 1020.0 Terrazzo Way 100-102 NaN
3 Linda NaN NaN NaN NaN NaN
4 George Hamilton St 159 b.A/B 1310.0 Hamilton St 159 A/B
5 Jennifer NaN NaN NaN NaN NaN
6 John Henry St 7 D 1080.0 Henry St 7 D NaN
7 Maria Mc-Kenzie Av 40P b.1 1190.0 Mc-Kenzie Av 40P 1
8 Charles Neptune Av 14 15 b.G 1040.0 Neptune Av 14 15 G
9 Helen NaN NaN NaN NaN NaN
这篇关于RegEx将地址分为三个不同的系列[第1部分]的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
