Substring function 提取部分字符串

Question

data = {'desc': ['ADRIAN PETER - ANN 80020355787C - 11 Baillon Pass.pdf', 'AILEEN MARCUS - ANC 800E15432922 - 5 Mandarin Way.pdf',
               'AJITH SINGH - ANN 80020837750 - 11 Berkeley Loop.pdf', 'ALEX MARTIN-CURTIS - ANC 80021710355 - 26 Dovedale St.pdf',
               'Alice.Smith\Jodee - Karen - ANE 80020428377 - 58 Harrisdale Dr.pdf']}
df = pd.DataFrame(data, columns = ['desc'])
df

From the data frame, I want to create a new column called ID, and in that ID, I want to have only those values starting after ANN, ANC or ANE. So I am expecting a result as below.

ID
80020355787C 
800E15432922 
80020837750 
80021710355 
80020428377 

I tried running the code below, but it did not get the desired result. Appreciate your help on this.

df['id'] = df['desc'].str.extract(r'\-([^|]+)\-')

Answer 1

You can use - AN[NCE] (800[0-9A-Z]+) - , where:

• AN[NCE] matches literally AN followed by N or C or E ;
• 800[0-9A-Z]+ matches literally 800 followed by one or more characters between 0 and 9 or between A and Z .

>>> df['desc'].str.extract(r'- AN[NCE] (800[0-9A-Z]+) -')
              0
0  80020355787C
1  800E15432922
2   80020837750
3   80021710355
4   80020428377

If not all your ids start with "800", you can just remove it from the pattern.