<p>你是如何清理数据的?可以使用'\r\n'作为分隔符来分解您拥有的示例数据。您可以根据列表中的字符串是否为空来筛选拆分后的列表。这可以作为一个基本的数据清理过程来完成。你自己决定的与之相关的部分。你知道吗</p>
<p>清洁的基本代码可以是:</p>
<pre><code>mystr = '\r\nContact Imported:\r\nBusinessPhone : 9547711900 Line1 : 2440 East Commercial Blvd.\r\n City : Ft. Lauderdale\r\n State : FL\r\n PostalCode : 33308\r\n\r\nArt Womack recommends Steve Paul Dentist on Commercial Blvd area.\r\nA_womack@me.com>\r\nBond? Crowns? Veneer?\r\n\r\n\r\n'
data = mystr.split('\r\n')
data_filtered = list(filter(lambda x: x, data))
for d in data_filtered:
print(d.strip())
</code></pre>
<p>这将输出:</p>
<pre><code>Contact Imported:
BusinessPhone : 9547711900 Line1 : 2440 East Commercial Blvd.
City : Ft. Lauderdale
State : FL
PostalCode : 33308
Art Womack recommends Steve Paul Dentist on Commercial Blvd area.
A_womack@me.com>
Bond? Crowns? Veneer?
</code></pre>
<p>你仍然需要弄清楚什么是重要的。你知道吗</p>
<p>编辑:根据给定的字符串,您可以使用:</p>
<pre><code>def convert(x):
d = x.split(':')
newlist = []
if len(d) > 2:
# Hack will work only in few cases, including this case
vals = d[1].strip().split(' ')
newlist.append(f'{d[0]}:{vals[0]}')
newlist.append(f'{vals[1]}:{d[2]}')
return newlist
return [x]
mystr = '\r\nContact Imported:\r\nBusinessPhone : 9547711900 Line1 : 2440 East Commercial Blvd.\r\n City : Ft. Lauderdale\r\n State : FL\r\n PostalCode : 33308\r\n\r\nArt Womack recommends Steve Paul Dentist on Commercial Blvd area.\r\nA_womack@me.com>\r\nBond? Crowns? Veneer?\r\n\r\n\r\n'
data = mystr.split('\r\n')
data_filtered = list(filter(lambda x: x, data))
data_filtered_2 = list((map(lambda x: convert(x), data_filtered)))
data_combined = []
for i in data_filtered_2:
data_combined += i
for d in data_combined:
print(d.strip())
</code></pre>