文本处理：如何从字符串列表中提取正确的字段？

如何解决文本处理：如何从字符串列表中提取正确的字段？

我想从 content_list 中提取六个字段并将它们放入一个数据帧中。这些字段是：Seq. #、Name、Coding Instructions、Target Value、Selections 和 Supporting Definitions。但是，我必须获取元数据对象的正则表达式没有为列表中的每个项目提供 Seq. #，并且缺少其他一些项目，因此当我对其进行子集化时，它给了我一个索引范围误差。我不确定我做错了什么。你能帮助我吗？谢谢！

import re 
import pandas as pd

content_list = ['\nSeq. #:\n2031','Name:\nSSN N/A\nThe value on arrival at this facility\nTarget Value:\nSelection Text\nDefinition\nNo\nYes\nSelections:\n(none)\nSupporting Definitions:\nIndicate the number created and automatically inserted by the software that uniquely identifies this patient.\nCoding Instructions:\nOnce assigned to a patient at the participating facility,this number will never be changed or reassigned to a different patient. If the \npatient returns to the same participating facility or for followup,they will receive this same unique patient identifier.\nNote(s):','\nSeq. #:\n2040','Name:\nNCDR Patient ID\nThe value on arrival at this facility\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\nAn optional patient identifier,such as Medical Record Number,that can be associated with the patient.\nCoding Instructions:\nThis element is referenced in The Joint Commission AMI Core Measures,AMI-1 through AMI-5. AMI-7,7a,8,8a and AMI-9.\nNote(s):','\nSeq. #:\n2045',"Name:\nOther ID\nN/A\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\nIndicate the patient's date of birth.\nCoding Instructions:\nThis element is referenced in The Joint Commission AMI Core Measures,8a and AMI-9.\nNote(s):",'\nSeq. #:\n2050',"Name:\nBirth Date\nThe value on arrival at this facility\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\n© 2007,American College of Cardiology Foundation\n3/31/2014\nPage 2 of 137\nEffective for Patient Discharges January 01,2015\nCoder's Data Dictionary\nNCDR® ACTION Registry®-GWTGŽ v2.4\nA. Demographics\nIndicate the patient's sex at birth.\nCoding Instructions:\nThis element is referenced in The Joint Commission AMI Core Measures,'\nSeq. #:\n2060','Name:\nSex\nThe value on arrival at this facility\nTarget Value:\nSelection Text\nDefinition\nMale\nFemale\nSelections:\n(none)\nSupporting Definitions:\nIndicate if the patient is White.\nCoding Instructions:\nIf the patient has multiple race origins,specify them using the other race selections in addition to this one.\nThis element is referenced in The Joint Commission AMI Core Measures,'\nSeq. #:\n2070','Name:\nRace - White\nThe value on arrival at this facility\nTarget Value:\nSelection Text\nDefinition\nNo\nYes\nSelections:\nWhite (race)\n:\nHaving origins in any of the original peoples of Europe,the Middle East,or North Africa.\nSource:\nU.S. Office of Management and Budget. Classification of Federal Data on Race and Ethnicity\nSupporting Definitions:\nIndicate if the patient is Black or African American.\nCoding Instructions:\nIf the patient has multiple race origins,'\nSeq. #:\n1040','Name:\nTransmission Number\nN/A\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\nVendor Identification (agreed upon by mutual selection between the vendor and the NCDR) to identify software vendor. Vendors \nmust use consistent name identification across sites. Changes to Vendor Name Identification must be approved by the NCDR.\nCoding Instructions:','\nSeq. #:\n1050',"Name:\nVendor Identifier\nN/A\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\nVendor's software product name and version number identifying the software which created this record (assigned by vendor). \nVendor controls the value in this field. Version passing certification/harvest testing will be noted at the NCDR.\nCoding Instructions:",'\nSeq. #:\n1060',"Name:\nVendor Software Version\nN/A\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\n© 2007,American College of Cardiology Foundation\n3/31/2014\nPage 136 of 137\nEffective for Patient Discharges January 01,2015\nCoder's Data Dictionary\nNCDR® ACTION Registry®-GWTGŽ v2.4\nZ. Administration\nThe NCDR Registry Identifier describes the data registry to which these records apply. It is implemented in the software at the time \nthe data is collected and the records are created. This is entered into the schema automatically by software.\nCoding Instructions:",'\nSeq. #:\n1070','Name:\nRegistry Identifier\nN/A\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\nRegistry Version describes the version number of the Data Specifications/Dictionary,to which each record conforms. It identifies \nwhich fields should have data,and what are the valid data for each field. It is the version implemented in the software at the time \nthe data is collected and the records are created. This is entered into the schema automatically by software.\nCoding Instructions:','\nSeq. #:\n1080','Name:\nRegistry Version\nN/A\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\nReserved for future use.\nCoding Instructions:','\nSeq. #:\n1200',"Name:\nAuxiliary 0\nN/A\nTarget Value:\n(none)\nSelections:\n(none)\nSupporting Definitions:\n© 2007,American College of Cardiology Foundation\n3/31/2014\nPage 137 of 137\nEffective for Patient Discharges January 01,2015\nCoder's Data Dictionary\nNCDR® ACTION Registry®-GWTGŽ v2.4\nZ. Administration"]

sequence_list = []
metadata = []
for i in content_list:
    metadata = list(filter(None,re.split("\s*(?:Seq. #:|Name:|Coding Instructions:|Target Value:|Selections:|Supporting Definitions:)\s*",i)))
    sequence_list.append([metadata[0],metadata[1],metadata[2],metadata[3],metadata[4],metadata[5]])

df = pd.DataFrame(sequence_list,columns = ['Seq #:','Name','Coding Instructions','Target Value','Supporting Definitions','Selections'])
df['Seq #:'] = df['Seq #:'].astype(int)
df.head()

解决方法

您可以使用换行符连接 content_list 中的项目，然后使用双换行符分割结果字符串以获取段落，您可以稍后使用匹配的正则表达式进行解析，例如

pattern = r'(?s)^Seq\. #:\s*(.*?)\nName:\s*(.*?)\nTarget Value:\s*(.*?)\nSelections:\s*(.*?)\nSupporting Definitions:\s*(.*?)(?:\nCoding Instructions:\s*(.*))?$'

参见regex demo。似乎 Coding Instructions 可能会丢失，因此它在正则表达式中是可选的。

Python 演示：

sequence_list = []
pattern = r'^Seq\. #:\s*(.*?)\nName:\s*(.*?)\nTarget Value:\s*(.*?)\nSelections:\s*(.*?)\nSupporting Definitions:\s*(.*?)(?:\nCoding Instructions:\s*(.*))?$'
for i in re.split(r'\n{2,}','\n'.join(content_list)):
    m = re.match(pattern,i.strip(),re.S)
    if m:
        sequence_list.append(m.groups())
df = pd.DataFrame(sequence_list,columns = ['Seq #:','Name','Coding Instructions','Target Value','Supporting Definitions','Selections'])

请注意，每个段落仅在正则表达式匹配时才被解析，如果匹配，则匹配 .groups() 数据用于稍后填充数据框。