我有一个 Excel 文件列表，其名称格式类似。我需要使用它们名称中的信息作为 pandas Dataframe 中的列。我对正则表达式不太熟悉，但我使用谷歌和堆栈溢出来弄清楚如何做我需要的事情。但是，有一些边缘情况需要我帮助解决。
这是我拥有的前 40 个文件的名称列表，它可以帮助展示我面临的挑战:
Maker Month Wise Data of VADAKARA RTO - KL18 , Kerala (2020).xlsx
Maker Month Wise Data of KATHUA RTO - JK8 , Jammu & Kashmir (2020).xlsx
Maker Month Wise Data of KANCHEEPURAM RTO - TN21 , Tamil Nadu (2020).xlsx
Maker Month Wise Data of KANJIRAPPALLY SRTO - KL34 , Kerala (2020).xlsx
Maker Month Wise Data of PATHANKOT SDM - PB35 , Punjab (2020).xlsx
Maker Month Wise Data of Chiplun Chiplun Track - MH202 , Maharashtra (2020).xlsx
Maker Month Wise Data of ZUNHEBOTO DTO - NL6 , Nagaland (2020).xlsx
Maker Month Wise Data of MAJITHA SDM - PB81 , Punjab (2020).xlsx
Maker Month Wise Data of Adinath Fitness Center - RJ260 , Rajasthan (2020).xlsx
Maker Month Wise Data of MUMBAI (EAST) - MH3 , Maharashtra (2020).xlsx
Maker Month Wise Data of CHIDAMBARAM RTO - TN544 , Tamil Nadu (2020).xlsx
Maker Month Wise Data of PUDUCHERRY - PY1 , Puducherry (2020).xlsx
Maker Month Wise Data of RANIPET RTO - TN73 , Tamil Nadu (2020).xlsx
Maker Month Wise Data of RTA, HISAR - HR39 , Haryana (2020).xlsx
Maker Month Wise Data of AIZAWL RURAL DTO - MZ9 , Mizoram (2020).xlsx
Maker Month Wise Data of ANANDPUR SAHIB SDM - PB16 , Punjab (2020).xlsx
Maker Month Wise Data of PEN (RAIGAD) - MH6 , Maharashtra (2020).xlsx
Maker Month Wise Data of PEHOWA - HR41 , Haryana (2020).xlsx
Maker Month Wise Data of AKOLA - MH30 , Maharashtra (2020).xlsx
Maker Month Wise Data of CANACONA RTO - GA10 , Goa (2020).xlsx
Maker Month Wise Data of Hooghly RTO - WB15 , West Bengal (2020).xlsx
Maker Month Wise Data of DEVIKULAM SRTO - KL68 , Kerala (2020).xlsx
Maker Month Wise Data of KUTTANADU SRTO - KL66 , Kerala (2020).xlsx
Maker Month Wise Data of CHENNAI (NORTH-EAST) RTO - TN3 , Tamil Nadu (2020).xlsx
Maker Month Wise Data of RLA SHILLAI - HP85 , Himachal Pradesh (2020).xlsx
Maker Month Wise Data of Baloda Bazar DTO - CG22 , Chhattisgarh (2020).xlsx
Maker Month Wise Data of TC OFFICE - STA OFFICE - KL99 , Kerala (2020).xlsx
Maker Month Wise Data of NANDURBAR - MH39 , Maharashtra (2020).xlsx
Maker Month Wise Data of KHETRI DTO - RJ53 , Rajasthan (2020).xlsx
Maker Month Wise Data of AHMEDGARH SDM - PB82 , Punjab (2020).xlsx
Maker Month Wise Data of Alipurduar RTO - WB69 , West Bengal (2020).xlsx
Maker Month Wise Data of RLA GOHAR - HP32 , Himachal Pradesh (2020).xlsx
Maker Month Wise Data of KOLHAPUR - MH9 , Maharashtra (2020).xlsx
Maker Month Wise Data of SILVASSA - DD1 , UT of DNH and DD (2020).xlsx
Maker Month Wise Data of MANNARGHAT SRTO - KL50 , Kerala (2020).xlsx
Maker Month Wise Data of SRIVILLIPUTHUR RTO - TN605 , Tamil Nadu (2020).xlsx
Maker Month Wise Data of ZONAL OFFICE, SOUTH WEST DELHI,DWARKA - DL9 , Delhi (2020).xlsx
Maker Month Wise Data of BUDGAM ARTO - JK4 , Jammu & Kashmir (2020).xlsx
Maker Month Wise Data of Kolar RTO - KA7 , Karnataka (2020).xlsx
Maker Month Wise Data of Singtam, East Sikkim - SK8 , Sikkim (2020).xlsx
这是使用正则表达式从这些文件名中提取信息的代码片段:
# Add RTO column - WORKS
rto = re.search('\s\sof\s(.*)\s\-', file_name)
df['RTO'] = rto.group(1)
# Add registration number column - NEEDS TO BE CORRECTED - See match 27
registration_number = re.search('\s\-(.*)\s\,', file_name)
df['Registration Number'] = registration_number.group(1)
# Add state column - NEEDS TO BE CORRECTED - See match 14, 34, 37
state = re.search('\,\s(.*)\s\(', file_name)
df['State'] = state.group(1)
# Add year column - NEEDS TO BE CORRECTED - See match 10, 17, 24,
year = re.search('\((.*)\)', file_name)
df['Year'] = year.group(1)
RTO 的正则表达式似乎工作正常，但有一些边缘情况需要针对注册号、州和年份进行修复。我在代码注释中突出显示了正则表达式错误行。如果我可以提供任何其他意见，请告诉我。
如果我能得到任何帮助来解决这个问题，我将不胜感激!
最佳答案
我认为你可以稍微修改一下之前的解决方案
pattern = r'\s+of\s+(.*?)\s+-\s+(.*?)\s+,\s+(.*?)\s+\((\d{4})\)'
df[['RTO', 'Registration Number', 'State','Year']] = df['Maker'].str.extract(pattern, expand=True)
请参阅regex demo .
如果注册号只能包含大写字母和数字，您可以将 (.*?) 替换为 ([A-Z0-9]+) 并使用\s+of\s+(.*?)\s+-\s+([A-Z0-9]*)\s+,\s+(.*?)\s+\((\d{4})\).
详细信息:
\s+- 一个或多个空格of- 一个词of\s+一个或多个空格(.*?)- 第 1 组:除了换行符之外的任何零个或多个字符，尽可能少\s+,\s+- 包含 1 个以上空格的逗号(.*?)- 第 2 组:除了换行符之外的任何零个或多个字符，尽可能少\s+,\s+- 包含 1 个以上空格的逗号(.*?)- 第 3 组:除了换行符之外的任何零个或多个字符，尽可能少(或者，如果[A-Z0-9]+使用任何一个或多个大写 ASCII 字母或数字)\s+- 1 个以上空格\(- 一个(char(\d{4})- 第 3 组:四位数字\)- 一个)字符。
关于regex - 需要修复正则表达式语句才能从 Excel 文件名中获取正确的信息，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/66436442/