blocks|key|3050368|text|你可以用一个带正则表达式的字典理解来重写键。回复+python模块使用sub命令来执行此任务。替换键如下所示：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3050369|import+re
dealer+=+{re.sub(r'(\W)[0-9]%2B',r'\1',k).strip():dealer[k]+for+k+in+dealer}|code-block|syntax|javascript|3050370|整个例子给出：|3050371|import+re
dealer+=+{
++++'ESSELUNGA':+'Spesa',
++++'DECATHLON+00000120':+'Sport',
++++'LEROY+MERLIN':+'Casa',
++++'CONAD+8429':+'Spesa',
++++'IKEA':+'Casa',
++++'F.LLI+MADAFFARI':+'Spesa',
++++'SUPERMERCATO+IL+GIGANT':+'Spesa',
++++'NATURASI+SPA':+'Spesa',
++++'ESSELUNGA+SETTIMO+MILANE':+'Spesa'
}
dealer+=+{re.sub(r'(\W)[0-9]%2B',r'\1',k).strip():dealer[k]+for+k+in+dealer}|3050372|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.python.org/2/library/re.html^0|Z|3|M|2|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@$9|X|A|Y|B|C]]|D|@$9|Z|A|10|1|11]]|E|$]]|$1|F|3|G|5|H|7|12|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|13|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|14|8|@]|D|@]|E|$I|J]]|$1|O|3|-4|5|6|7|15|8|@]|D|@]|E|$]]]|P|$Q|$5|R|S|T|E|$U|V]]]]

One can use a dict comprehension with a regular expression to rewrite key.
The <a href="https://docs.python.org/2/library/re.html" rel="nofollow">re</a> python module is used to perform this task, with the command <code>sub</code>. The substitution key looks like:

<pre><code>import re
dealer = {re.sub(r'(\W)[0-9]+',r'\1',k).strip():dealer[k] for k in dealer}
</code></pre>

The whole example gives:

<pre><code>import re
dealer = {
 'ESSELUNGA': 'Spesa',
 'DECATHLON 00000120': 'Sport',
 'LEROY MERLIN': 'Casa',
 'CONAD 8429': 'Spesa',
 'IKEA': 'Casa',
 'F.LLI MADAFFARI': 'Spesa',
 'SUPERMERCATO IL GIGANT': 'Spesa',
 'NATURASI SPA': 'Spesa',
 'ESSELUNGA SETTIMO MILANE': 'Spesa'
}
dealer = {re.sub(r'(\W)[0-9]+',r'\1',k).strip():dealer[k] for k in dealer}
</code></pre>

blocks|key|710206|text|为什么不使用apply和修改过的字典查找：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|710207|In+[14]:+[dname+for+dname+in+dealer+if+'DECATHLON'+in+dname]
Out[14]:+['DECATHLON+00000120']|code-block|syntax|javascript|710208|然后，像这样应用它-|710209|df['Commerciante']+=+df['Commerciante'].apply(lambda+v:+[dname+for+dname+in+dealer+if+dname.startswith('DECATHLON')][0])|710210|entityMap^0|6|5|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@$9|R|A|S|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|T|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|U|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|V|8|@]|D|@]|E|$I|J]]|$1|O|3|-4|5|6|7|W|8|@]|D|@]|E|$]]]|P|$]]

Why don't you use <code>apply</code> and on a modified dictionary lookup:

<pre><code>In [14]: [dname for dname in dealer if 'DECATHLON' in dname]
Out[14]: ['DECATHLON 00000120']
</code></pre>

And, apply it like this - 

<pre><code>df['Commerciante'] = df['Commerciante'].apply(lambda v: [dname for dname in dealer if dname.startswith('DECATHLON')][0])
</code></pre>

blocks|key|3050422|text|我认为你的问题是你试图一步一步地做两件事。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3050423|首先清理你的数据，然后映射它。|3050424|熊猫系列拥有许多不错的字符串功能，可以方便地清理您的数据。下面是对string方法的良好引用。|offset|length|3050425|一旦使用了string方法来清理数据，映射就很容易了。|3050426|entityMap|0|LINK|mutability|MUTABLE|url|http://pandas.pydata.org/pandas-docs/stable/text.html^0|0|0|T|H|0|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|S|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|T|8|@]|9|@$F|U|G|V|1|W]]|A|$]]|$1|H|3|I|5|6|7|X|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|K|$L|$5|M|N|O|A|$P|Q]]]]

I think your problem is that you are trying to do two things in one step.

First clean your data, then map it.

pandas Series holds lots of nice string functions which can come in handy for cleaning your data. <a href="http://pandas.pydata.org/pandas-docs/stable/text.html" rel="nofollow">Here is a good reference to the string methods</a>.

Once you have used the string methods for cleaning your data, mapping it will be easy as pie.

blocks|key|710282|text|谢谢你们所有人。我用你的建议来解决我的问题。我定义了一个新函数：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|710283|def+dealer_replace(dealer_dict,+text):

++++regex+=+re.compile("(%25s)"+%25+"%7C".join(map(re.escape,+dealer_dict.keys())))

++++if+regex.search(text):
++++++++ret+=+regex.search(text)
++++++++return+dealer_dict[ret.group()]
++++else:
++++++++return+None|code-block|syntax|javascript|710284|并与apply一起使用|710285|entries['Categoria']+=+entries['Commerciante'].apply(lambda+v:+dealer_replace(dealer,+str(v)))|710286|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

Thank you to all of you. I used your suggestions to resolve my problem. I defined a new function:

<pre><code>def dealer_replace(dealer_dict, text):

 regex = re.compile("(%s)" % "|".join(map(re.escape, dealer_dict.keys())))

 if regex.search(text):
 ret = regex.search(text)
 return dealer_dict[ret.group()]
 else:
 return None
</code></pre>

And use it with apply

<pre><code>entries['Categoria'] = entries['Commerciante'].apply(lambda v: dealer_replace(dealer, str(v)))
</code></pre>

I have a dict:

<pre><code>dealer = {
 'ESSELUNGA': 'Spesa',
 'DECATHLON 00000120': 'Sport',
 'LEROY MERLIN': 'Casa',
 'CONAD 8429': 'Spesa',
 'IKEA': 'Casa',
 'F.LLI MADAFFARI': 'Spesa',
 'SUPERMERCATO IL GIGANT': 'Spesa',
 'NATURASI SPA': 'Spesa',
 'ESSELUNGA SETTIMO MILANE': 'Spesa'
}
</code></pre>

and I want to map it to a pandas df:

<pre><code>entries.Categoria = entries.Commerciante.map(dealer)
</code></pre>

Is there a way to use regex to match map on "Commerciante" column? In this way I can rewrite dealer as this:

<pre><code>dealer = {
 'ESSELUNGA': 'Spesa',
 'DECATHLON': 'Sport',
 'LEROY MERLIN': 'Casa',
 'CONAD': 'Spesa',
 'IKEA': 'Casa',
 'F.LLI MADAFFARI': 'Spesa',
 'SUPERMERCATO IL GIGANT': 'Spesa',
 'NATURASI SPA': 'Spesa',
 'ESSELUNGA SETTIMO MILANE': 'Spesa'
}
</code></pre>

and match both "DECATHLON" and "DECATHLON 00000120"

python pandas use map with regular expressions

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我有个白痴：dealer = {    'ESSELUNGA': 'Spesa',    'DECATHLON 00000120': 'Sport',    'LEROY MERLIN': 'Casa',    'CONAD 8429': 'Spesa',    'IKEA': 'Casa',    'F.LLI MA...

问python熊猫使用带正则表达式的map
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