我有一个如下的数据集；
"birth_date_1:25 birth_date_2:august birth_date_3:1945 birth_place_1:france death_date:<none> "
"birth_date_1:14 birth_date_2:june birth_date_3:1995 birth_place_1:dvůr birth_place_2:králové birth_place_3:nad birth_place_4:labem birth_place_5:, birth_place_6:czech birth_place_7:republic "
"birth_date_1:21 birth_date_2:february birth_date_3:1869 birth_place_1:blackburn birth_place_2:, birth_place_3:england death_date_1:12 death_date_2:march death_date_3:1917 "
"birth_date_1:07 birth_date_2:july birth_date_3:1979 birth_place_1:ghana birth_place_2:, birth_place_3:accra "
"birth_date_1:27 birth_date_2:february birth_date_3:1979 birth_place_1:durban birth_place_2:, birth_place_3:south birth_place_4:africa "
"birth_date_1:1989 birth_place_1:lima birth_place_2:, birth_place_3:peru "
"birth_date_1:5 birth_date_2:september birth_date_3:1980 birth_place_1:angola death_date:<none> "
"birth_date_1:1 birth_date_2:february birth_date_3:1856 birth_place_1:hampstead birth_place_2:, birth_place_3:london death_date_1:14 death_date_2:august death_date_3:1905 "
"birth_date_1:28 birth_date_2:december birth_date_3:1954 birth_place_1:hickory birth_place_2:, birth_place_3:north birth_place_4:carolina death_date:<none> "
"birth_date:<none> "
"birth_date:<none> birth_place:<none> death_date:<none> "
"birth_date:<none> birth_place_1:belfast birth_place_2:, birth_place_3:northern birth_place_4:ireland "
"birth_date:<none> birth_place:<none> death_date:<none> "
"birth_date_1:28 birth_date_2:february birth_date_3:1891 birth_place_1:carberry birth_place_2:, birth_place_3:manitoba death_date_1:20 death_date_2:september death_date_3:1968 "
"birth_date_1:4 birth_date_2:november birth_date_3:1993 birth_place_1:portim√£o birth_place_2:, birth_place_3:portugal "
在这些数据集中，我尝试提取以下信息；
25.08.1945 \t France \t NA
14.06.1995 \t Dvůr Králové nad Labem,Czech Republic \t
21.02.1896 \t Blackburn,England \t 12.03.1917
.
.
.
1989 \t Lima,Peru \t NA
.
.
.
NA \t NA \t NA
NA \t NA \t NA
NA \t Belfast, Northern Ireland \t NA
.
.
04.11.1993 \t Portimeo,Portugal \t NA
我写了下面的代码来实现这一目标，但是由于我在数据集中会遇到几种情况，例如birth_date_1信息可能为null，月名或年份，所以我想出的下面的循环感觉会失败某个地方，将是不可行的。
outputfile = open('ornek_box_seperated_update.csv','w',encoding="utf-8")
inputfile = open('ornek_box_seperated.csv','r',encoding="utf-8")
import numpy as np
birthDatePlace = [[ np.nan for i in range(9) ] for j in range(20000)]
for line in inputfile:
d = line.split(":")
print(d)
d = line.split(d)
d = "\t".join(d)
print(d)
if(d[1]<40 and d[1]>0):
birthDatePlace[line,1] = d[1]
elif(d[1]<2020):
birthDatePlace[line,3] = d[1]
if(d[1]<40 and d[1]>0 and isinstance(d[3])==str):
birthDatePlace[line,2] = d[3]
elif(d[1]<2020 and isinstance(d[3])==int):
birthDatePlace[line,4] = d[3]
# this code planned to continue from here until cover the all birth place and death date information in required format
outputfile.write(d)
outputfile.write('\n')
outputfile.close()
感谢您提供的任何帮助。我是python的新手，尤其是正则表达式或字符串提取方法。
预先感谢您的支持。
答案 0 :(得分：0)
如果要避免代码损坏，最好进行显式检查。请检查下面的代码。我已经解析了信息并将其存储在一个类对象中。该类具有一些帮助程序功能来修改已解析的数据。
# -*- coding: utf-8 -*-
# Class for storing parsed information
class Info(object):
def __init__(self, birth_date_1, birth_date_2, birth_date_3, birth_place, death_date_1, death_date_2, death_date_3):
if not (birth_date_1 or birth_date_2 or birth_date_3):
self.birth_date = "NA"
else:
if birth_date_2 and birth_date_2.isalpha():
birth_date_2 = self.month_string_to_number(birth_date_2)
self.birth_date = '.'.join([birth_date_1, birth_date_2, birth_date_3]).strip(".")
self.birth_place = birth_place if birth_place.strip(",") else "NA"
if not (death_date_1 or death_date_2 or death_date_3):
self.death_date = "NA"
else:
if death_date_2 and death_date_2.isalpha():
death_date_2 = self.month_string_to_number(death_date_2)
self.death_date = '.'.join([death_date_1, death_date_2, death_date_3]).strip(".")
self.sanitize()
def print_req_format(self):
print '\t'.join([self.birth_date, self.birth_place, self.death_date])
def sanitize(self):
if "<none>" in self.birth_date:
self.birth_date = "NA"
if "<none>" in self.birth_place:
self.birth_place = "NA"
if "<none>" in self.death_date:
self.death_date = "NA"
def month_string_to_number(self, month):
m = {
'jan': 1,
'feb': 2,
'mar': 3,
'apr': 4,
'may': 5,
'jun': 6,
'jul': 7,
'aug': 8,
'sep': 9,
'oct': 10,
'nov': 11,
'dec': 12
}
s = month.strip()[:3].lower()
try:
out = m[s]
return str(out)
except:
return ""
dataset = [
"birth_date_1:25 birth_date_2:august birth_date_3:1945 birth_place_1:france death_date:<none>",
"birth_date_1:14 birth_date_2:june birth_date_3:1995 birth_place_1:dvůr birth_place_2:králové birth_place_3:nad birth_place_4:labem birth_place_5:, birth_place_6:czech birth_place_7:republic",
"birth_date_1:21 birth_date_2:february birth_date_3:1869 birth_place_1:blackburn birth_place_2:, birth_place_3:england death_date_1:12 death_date_2:march death_date_3:1917",
"birth_date_1:07 birth_date_2:july birth_date_3:1979 birth_place_1:ghana birth_place_2:, birth_place_3:accra",
"birth_date_1:27 birth_date_2:february birth_date_3:1979 birth_place_1:durban birth_place_2:, birth_place_3:south birth_place_4:africa",
"birth_date_1:1989 birth_place_1:lima birth_place_2:, birth_place_3:peru",
"birth_date_1:5 birth_date_2:september birth_date_3:1980 birth_place_1:angola death_date:<none>",
"birth_date_1:1 birth_date_2:february birth_date_3:1856 birth_place_1:hampstead birth_place_2:, birth_place_3:london death_date_1:14 death_date_2:august death_date_3:1905",
"birth_date_1:28 birth_date_2:december birth_date_3:1954 birth_place_1:hickory birth_place_2:, birth_place_3:north birth_place_4:carolina death_date:<none>",
"birth_date:<none>",
"birth_date:<none> birth_place:<none> death_date:<none>",
"birth_date:<none> birth_place_1:belfast birth_place_2:, birth_place_3:northern birth_place_4:ireland",
"birth_date:<none> birth_place:<none> death_date:<none>",
"birth_date_1:28 birth_date_2:february birth_date_3:1891 birth_place_1:carberry birth_place_2:, birth_place_3:manitoba death_date_1:20 death_date_2:september death_date_3:1968",
"birth_date_1:4 birth_date_2:november birth_date_3:1993 birth_place_1:portim√£o birth_place_2:, birth_place_3:portugal",
]
for line in dataset:
split_data_line = line.split()
birth_date_1 = birth_date_2 = birth_date_3 = birth_place = death_date_1 = death_date_2 = death_date_3 = ""
for data in split_data_line:
split_data = data.split(":")
if len(split_data) < 2:
continue
val = split_data[1]
if data.startswith("birth_date_1"):
birth_date_1 = val
elif data.startswith("birth_date_2"):
birth_date_2 = val
elif data.startswith("birth_date_3"):
birth_date_3 = val
elif data.startswith("birth_place"):
if not birth_place or val == ",":
birth_place += val
else:
birth_place += " " + val
elif data.startswith("death_date_1"):
death_date_1 = val
elif data.startswith("death_date_2"):
death_date_2 = val
elif data.startswith("death_date_3"):
death_date_3 = val
info = Info(birth_date_1, birth_date_2, birth_date_3, birth_place, death_date_1, death_date_2, death_date_3)
info.print_req_format()
根据您提供的数据，此代码的输出为：
25.8.1945 france NA
14.6.1995 dvůr králové nad labem, czech republic NA
21.2.1869 blackburn, england 12.3.1917
07.7.1979 ghana, accra NA
27.2.1979 durban, south africa NA
1989 lima, peru NA
5.9.1980 angola NA
1.2.1856 hampstead, london 14.8.1905
28.12.1954 hickory, north carolina NA
NA NA NA
NA NA NA
NA belfast, northern ireland NA
NA NA NA
28.2.1891 carberry, manitoba 20.9.1968
4.11.1993 portim√£o, portugal NA
该代码非常简单易懂。希望这对您有用。干杯。
答案 1 :(得分：0)
import csv
FIELDNAMES = ('birth_date', 'birth_place', 'death_date')
with open('infile', 'r') as f:
result = []
for line in f:
record = {k: '' for k in FIELDNAMES}
for kv in line.strip('" \n').split():
k, v = kv.split(':')
if v == '<none>':
continue
key = k.rstrip('_0123456789')
value = ' ' + v if record[key] and v != ',' else v
record[key] += value
result.append(record)
with open('outfile.csv', 'w') as f:
writer = csv.DictWriter(f, fieldnames=FIELDNAMES)
writer.writeheader()
writer.writerows(result)
'outfile.csv'：
birth_date,birth_place,death_date
25 august 1945,france,
14 june 1995,"dvůr králové nad labem, czech republic",
21 february 1869,"blackburn, england",12 march 1917
07 july 1979,"ghana, accra",
27 february 1979,"durban, south africa",
1989,"lima, peru",
5 september 1980,angola,
1 february 1856,"hampstead, london",14 august 1905
28 december 1954,"hickory, north carolina",
,,
,,
,"belfast, northern ireland",
,,
28 february 1891,"carberry, manitoba",20 september 1968
4 november 1993,"portim√£o, portugal",