使用正则表达式从字符串列表中提取信息。

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英文:

Extracting information from a list of strings using regex

问题

  1. 提取信息：
  2.  层级    金额   最低费用 子基金              账户维护
  3. 0.09%  第一个 GBP£250 百万   GBP£22,000  GBP£2,750   £00 每年 
  4.                                                      每位投资者 GBPL£25 
  5.                                                      手动 GBPE£25 
  6.                                                    自动GBPE£S5 
  8. 0.08%   下一个 GBP£250 百万                   GBPE£L,500
  9. 0.06%   下一个 GBP£500 百万                   GBP£3,000
英文:

I have a list of strings from which I wish to extract information around amount, percentages etc. Being new to regex I have been struggling with the process. Below are my input & desired output & the piece of code that I tried using.

Input list:

  1. ['0.09% of the first GBP£250 million of the Company’s Net Asset Value;', '0.08% of the next GBP£250 million of the Company’s Net Asset Value;', "0.06% of the next GBP£500 million of the Company's Net Asset Value; and", 'e GBP£22,000 in respect of cach of (he Company’s Sub-Funds which shall be accrued for on a daily basis', 'in accordance with the formula GBP£22,000 + 365, Minimum fee to be levied at a Company level,', 'e Preparation of fund interim and annual financial statements... GBP£2,750 per sub-fund pa', 'e UK Tax Reporting... ww. GBPE£L,500 per sub-fund pa', 'BUSD Tax Reporting’ v GBP£3,000 per sub-find pa', '© Account maintenance £00 sess resect GBPL£25 per investor pa', '» Manual .. GBPE£25 per transaction', '"Automated GBPE£S5 per Gransaction', 'e Investor registration and AML {ce GBP£50 per new investor account,', '« Fund distribution/dividend fee GBP£750 per distribution/dividend per sub fund.']

Code:

  1. import re
  3. def extract_pounds(text):
  4.     regex = "£(\w+)"
  5.     return re.findall(regex, str(text))
  8. for word in empty_df:
  9.     pounds = extract_pounds(word)
  10.     print(pounds)

I am getting the following output which is far from being close to my desired output:

  1. ['250']
  2. ['250']
  3. ['500']
  4. ['22']
  5. ['22']

Desired output:

  1.  Tier    Amount   Minimum Fee Sub-Fund               AccountMaintain
  2.  0.09%   first GBP£250 million   GBP£22,000  GBP£2,750   £00 sess 
  3.                                                        resect GBPL£25 
  4.                                                        Manual GBPE£25 
  5.                                                      AutomatedGBPE£S5 
  7.  0.08%   next GBP£250 million                        GBPE£L,500
  8.  0.06%   next GBP£500 million                        GBP£3,000

答案1

得分: 1

  1. 使用[tag:pandas]，你可以尝试以下代码：
  3.     import re
  4.     import pandas 
  6.     pat = r"([\d.]+%) of the (\w+ GBP£\d+ \w+)"
  7.     df = pd.Series(lst[:-1]).str.extract(pat).set_axis(["Tier", "Amount"], axis=1)
  8.     ​
  9.     df.loc[0, "Minimum Fee"] = re.search("GBP£\d+,\d+", lst[-1]).group(0)
  10.     
  11. 输出：
  13.     print(df)
  14.     ​
  15.         Tier                 Amount Minimum Fee
  16.     0  0.09%  first GBP£250 million  GBP£22,000
  17.     1  0.08%   next GBP£250 million         NaN
  18.     2  0.06%   next GBP£500 million         NaN
  20. ***更新：***
  22. 根据你的更新的问题/列表，使用以下代码：
  24.     ​pat1 = r"([\d.]+%) of the (\w+ GBP£\d+ \w+)"
  25.     df = pd.Series(lst).str.extract(pat1).set_axis(["Tier", "Amount"], axis=1).dropna()
  26.     ​
  27.     pat2 = r"(GBP£\d+,\d+).*Minimum fee"
  28.     result = re.search(pattern, " ".join(lst))
  29.     mfee = result.group(1) if result else None
  30.         
  31.     df.loc[0, "Minimum Fee"] = mfee
  32.     
  33. 输出：
  35.     print(df)
  36.     
  37.         Tier                 Amount Minimum Fee
  38.     0  0.09%  first GBP£250 million  GBP£22,000
  39.     1  0.08%   next GBP£250 million         NaN
  40.     2  0.06%   next GBP£500 million         NaN
英文:

With [tag:pandas], you can try something like this :

  1. import re
  2. import pandas 
  4. pat = r"([\d.]+%) of the (\w+ GBP£\d+ \w+)"
  5. df = pd.Series(lst[:-1]).str.extract(pat).set_axis(["Tier", "Amount"], axis=1)
  6. ​
  7. df.loc[0, "Minimum Fee"] = re.search("GBP£\d+,\d+", lst[-1]).group(0)

Output :

  1. print(df)
  2. ​
  3.     Tier                 Amount Minimum Fee
  4. 0  0.09%  first GBP£250 million  GBP£22,000
  5. 1  0.08%   next GBP£250 million         NaN
  6. 2  0.06%   next GBP£500 million         NaN

UPDATE :

Based on your updated question/list, use this :

  1. ​pat1 = r"([\d.]+%) of the (\w+ GBP£\d+ \w+)"
  2. df = pd.Series(lst).str.extract(pat1).set_axis(["Tier", "Amount"], axis=1).dropna()
  3. ​
  4. pat2 = r"(GBP£\d+,\d+).*Minimum fee"
  5. result = re.search(pattern, " ".join(lst))
  6. mfee = result.group(1) if result else None
  7.     
  8. df.loc[0, "Minimum Fee"] = mfee

Output :

  1. print(df)
  3.     Tier                 Amount Minimum Fee
  4. 0  0.09%  first GBP£250 million  GBP£22,000
  5. 1  0.08%   next GBP£250 million         NaN
  6. 2  0.06%   next GBP£500 million         NaN

huangapple
  • 本文由 发表于 2023年4月19日 16:14:56
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  • python
  • regex
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