我有以下文字，我想抓取数据项并将它们保存在excel中。有没有办法在Python中执行此操作？
text = """
ANNUAL COMPENSATION LONG-TERM COMPENSATION
--------------------------------------- -------------------------------------
AWARDS PAYOUTS
-------------------------- ----------
SECURITIES
OTHER RESTRICTED UNDERLYING ALL OTHER
NAME AND PRINCIPAL ANNUAL STOCK OPTIONS/ LTIP COPMPENSA-
POSITION YEAR SALARY ($) BONUS ($) COMPENSATION ($) AWARD(S) ($)(1) SAR'S (#) PAYOUTS($) TION($)(3)
------------------ ---- ---------- --------- ---------------- --------------- ---------- ---------- ----------
JOHN W. WOODS 1993 $595,000 $327,250 There is no $203,190.63 18,000 $ 29,295
Chairman, President, & 1992 $545,000 $245,250 compensation 166,287.50 18,825 (2) Not $ 29,123
Chief Executive Officer 1991 $515,000 $283,251 required to be 45,000 Applicable
of AmSouth & AmSouth disclosed in
Bank N.A. this column.
C. STANLEY BAILEY 1993 $266,667(4) $133,333 117,012.50 4,500 $ 11,648
Vice Chairman, AmSouth 1992 $210,000 $ 84,000 42,400.00 4,800 $ 12,400
& AmSouth Bank N.A. 1991 $186,750 $ 82,170 161,280.00 9,750
C. DOWD RITTER 1993 $266,667(4) $133,333 117,012.50 4,500 $ 13,566
Vice Chairman, AmSouth 1992 $210,000 $ 84,000 42,400.00 4,800 $ 12,920
& AmSouth Bank N.A. 1991 $188,625 $ 82,995 161,280.00 9,750
WILLIAM A. POWELL, JR. 1993 $211,335 $ 95,101 11,000 $124,548
President, AmSouth 1992 $330,000 $132,000 98,050.00 11,100 $ 22,225
and Vice Chairman, 1991 $308,000 $169,401 24,000
AmSouth Bank N.A.
Retired in 1993
A. FOX DEFUNIAK, III 1993 $217,000 $ 75,950 52,971.88 4,500 $ 11,122
Senior Executive Vice 1992 $200,000 $ 62,000 42,400.00 4,800 $ 11,240
President, Birmingham 1991 $177,500 $ 78,100 161,280.00 9,750
Banking Group,
AmSouth Bank N.A.
E. W. STEPHENSON, JR. 1993 $177,833 $ 71,133 52,971.88 3,400 $ 9,256
Senior Executive Vice 1992 $150,000 $ 45,000 27,825.00 3,150 $ 8,560
President, AmSouth 1991 $140,000 $ 52,488 107,520.00 6,750
and Chairman & Chief
Executive Officer,
AmSouth Bank of Florida
"""
现在，我只想尝试以'|'的csv样式格式用于分隔数据项的符号，然后手动将数据提取到excel：
tmp = open('tmp.txt','w')
tmp.write(text)
tmp.close()
data1 = []
for line in open('tmp.txt'):
line = line.lower()
if 'SALARY' in line:
line = line.replace(' ','|')
line = line.replace('--', '')
line = line.replace('- -', '')
line = line.replace('- -', '')
line = line.replace('(1)', '')
line = line.replace('(2)', '')
line = line.replace('(3)', '')
line = line.replace('(4)', '')
line = line.replace('(5)', '')
line = line.replace('(6)', '')
line = line.replace('(7)', '')
line = line.replace('(8)', '')
line = line.replace('(9)', '')
line = line.replace('(10)', '')
line = line.replace('(11)', '')
line = line.replace('(S)', '')
line = line.replace('($)', '')
line = line.replace('(#)', '')
line = line.replace('$', '')
line = line.replace('-0-', '0')
line = line.replace(')', '|')
line = line.replace('(', '|-')
line = re.sub(r'\s(\d)', '|\\1', line)
line = line.replace(' ', '')
line = line.replace('||', '|')
data1.append(line)
data = ''.join(data1)
问题是我必须做几千次这样做，并且需要永远地通过每个表并保存我需要的物品。有没有办法创建一个字典，可以跟踪最左列中列出的每个人的年份，工资，奖金，其他年度报酬等内容？
答案 0 :(得分：3)
以下是一些可以帮助您入门的代码：
text = """JOHN ...""" # text without the header
# These can be inferred if necessary
cols = [0, 24, 29, 39, 43, 52, 71, 84, 95, 109, 117]
db = []
row = []
for line in text.strip().split("\n"):
data = [line[cols[i]:cols[i+1]] for i in xrange((len(cols)-1))]
if data[0][0] != " ":
if row:
db.append(row)
row = map(lambda x: [x], data)
else:
for i, c in enumerate(data):
row[i].append(c)
print db
这将产生一个每人都有一个元素的数组。每个元素都是所有列的数组，并且将包含所有行的数组。通过这种方式，您可以轻松访问不同年份，或者执行诸如连接此人的标题之类的事情：
for person in db:
print "Name:", person[0][0]
print " ".join(s.strip() for s in person[0][1:])
print
将屈服：
Name: JOHN W. WOODS
Chairman, President, & Chief Executive Officer of AmSouth & AmSouth Bank N.A.
Name: C. STANLEY ...
答案 1 :(得分：2)
您需要编写一系列生成器来对数据进行连续传递，以降低噪声和复杂性。
这是不在任何编程语言中都难以解决的问题。
def strip_top( source_text ):
src= iter( source_text )
for line in src:
if line.rstrip().startswith("AWARDS"):
next( src )
break
for line in src:
yield line
def columnize( source_text ):
"""Assumes strip_top or similar to remove confusing extra headers"""
for line in src:
yield line[0:24], line[25:30], ... for each coumn
def collapse_headers( source_text ):
"""Assumes columnize( strip_top())."""
src= iter( source_text )
headings= [ [] for i in range(9) ]
for line in src:
if line[0] == "------------------":
break
for col in range(9):
headings[col].append(line[col].strip())
yield [ " ".join(h) for h in headings ]
for line in src:
yield line
etc.
然后，您的“主”程序将这些转换组装成一个管道。
with open("some file","r") as text:
for line in collapse_headers( columnize( strip_top( text ) ) ):
# further cleanup?
# actual processing
这允许您分别“调整”每个转换序列。
答案 2 :(得分：1)
好吧，分离列很容易，它们是固定的宽度，所以你可以这样做：
cells = [rowtext[0:24], rowtext[25:29], ...]
分隔行有点困难。看起来你可以单独处理标题，然后检查
cells[0] == cells[0].upper()
查看是否应该开始一个新的行块（即当行中的第一个单元格是块大小写时）。当然，我假设您的数千个文件都具有完全相同的格式。
一旦您将数据转换为可用格式，就可以轻松地将其整理到Python中。您可以将它全部放在字典中，或者如果它太大，可以将其作为大型CSV文件或sqlite数据库写入磁盘。