entityMap|0|type|LINK|mutability|MUTABLE|data|url|http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.replace.html|blocks|key|a24i9|text|编辑:正确的答案是：|unstyled|depth|inlineStyleRanges|entityRanges|2sr5r|df+=+df.replace(r'\n','+',+regex=True)+|code-block|syntax|javascript|70irv|我觉得你需要replace|offset|length|style|CODE|4os7a|df+=+df.replace('\n','',+regex=True)|2hi1u|或者：|8oqbm|df+=+df.replace('\n','+',+regex=True)|4cj34|8it4t|df+=+df.replace(r'\\n','+',+regex=True)|6703r|示例：|ev4t2|text+=+'''hands-on\ndev+nologies\nrelevant+scripting\nlang
'''
df+=+pd.DataFrame({'A':[text]})
print+(df)
+++++++++++++++++++++++++++++++++++++++++++++++++++A
0++hands-on\ndev+nologies\nrelevant+scripting\nla...

df+=+df.replace('\n','+',+regex=True)
print+(df)
++++++++++++++++++++++++++++++++++++++++++++++++A
0++hands-on+dev+nologies+relevant+scripting+lang+|1bvth^0|0|0|6|7|6|7|0|0|0|0|0|0|0|0|0^^$0|$1|$2|3|4|5|6|$7|8]]]|9|@$A|B|C|D|2|E|F|17|G|@]|H|@]|6|$]]|$A|I|C|J|2|K|F|18|G|@]|H|@]|6|$L|M]]|$A|N|C|O|2|E|F|19|G|@$P|1A|Q|1B|R|S]]|H|@$P|1C|Q|1D|A|1E]]|6|$]]|$A|T|C|U|2|K|F|1F|G|@]|H|@]|6|$L|M]]|$A|V|C|W|2|E|F|1G|G|@]|H|@]|6|$]]|$A|X|C|Y|2|K|F|1H|G|@]|H|@]|6|$L|M]]|$A|Z|C|W|2|E|F|1I|G|@]|H|@]|6|$]]|$A|10|C|11|2|K|F|1J|G|@]|H|@]|6|$L|M]]|$A|12|C|13|2|E|F|1K|G|@]|H|@]|6|$]]|$A|14|C|15|2|K|F|1L|G|@]|H|@]|6|$L|M]]|$A|16|C|-4|2|E|F|1M|G|@]|H|@]|6|$]]]]

EDIT: the correct answer to this is:
<pre><code>df = df.replace(r'\n',' ', regex=True) 
</code></pre>
I think you need <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.replace.html" rel="noreferrer"><code>replace</code></a>:
<pre><code>df = df.replace('\n','', regex=True)
</code></pre>
Or:
<pre><code>df = df.replace('\n',' ', regex=True)
</code></pre>
Or:
<pre><code>df = df.replace(r'\\n',' ', regex=True)
</code></pre>
Sample:
<pre><code>text = '''hands-on\ndev nologies\nrelevant scripting\nlang
'''
df = pd.DataFrame({'A':[text]})
print (df)
 A
0 hands-on\ndev nologies\nrelevant scripting\nla...

df = df.replace('\n',' ', regex=True)
print (df)
 A
0 hands-on dev nologies relevant scripting lang 
</code></pre>

entityMap|blocks|key|36ku|text|在乱七八糟的数据中，删除所有空格df.replace(r'\s',+'',+regex+=+True,+inplace+=+True)可能是个好主意。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|5tbmr^0|G|1F|0^^$0|$]|1|@$2|3|4|5|6|7|8|H|9|@$A|I|B|J|C|D]]|E|@]|F|$]]|$2|G|4|-4|6|7|8|K|9|@]|E|@]|F|$]]]]

in messy data it might to be a good idea to remove all whitespaces <code>df.replace(r'\s', '', regex = True, inplace = True)</code>.

entityMap|blocks|key|892u|text|+++df+=+'Sarah+Marie+Wimberly+So+so+beautiful!!!\nAbram+Staten+You+guys+look+good+man.\nTJ+Sloan+I+miss+you+guys\n'

+++df+=+df.replace(r'\\n','+',+regex=True)|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|ahv2c|这对我拥有的杂乱的数据起作用了。|unstyled|f4nul^0|0|0^^$0|$]|1|@$2|3|4|5|6|7|8|I|9|@]|A|@]|B|$C|D]]|$2|E|4|F|6|G|8|J|9|@]|A|@]|B|$]]|$2|H|4|-4|6|G|8|K|9|@]|A|@]|B|$]]]]

<pre><code> df = 'Sarah Marie Wimberly So so beautiful!!!\nAbram Staten You guys look good man.\nTJ Sloan I miss you guys\n'

 df = df.replace(r'\\n',' ', regex=True)
</code></pre>

This worked for the messy data I had.

entityMap|0|type|LINK|mutability|MUTABLE|data|url|https://gist.github.com/smram/d6ded3c9028272360eb65bcab564a18a|blocks|key|8purp|text|df.replace(to_replace=[r"\\t%7C\\n%7C\\r",+"\t%7C\n%7C\r"],+value=["",""],+regex=True,+inplace=True)|code-block|depth|inlineStyleRanges|entityRanges|syntax|javascript|3epug|对我很管用。|unstyled|clvhu|来源：|9s804|offset|length|6ahs^0|0|0|0|0|1Q|0|0^^$0|$1|$2|3|4|5|6|$7|8]]]|9|@$A|B|C|D|2|E|F|T|G|@]|H|@]|6|$I|J]]|$A|K|C|L|2|M|F|U|G|@]|H|@]|6|$]]|$A|N|C|O|2|M|F|V|G|@]|H|@]|6|$]]|$A|P|C|8|2|M|F|W|G|@]|H|@$Q|X|R|Y|A|Z]]|6|$]]|$A|S|C|-4|2|M|F|10|G|@]|H|@]|6|$]]]]

<pre><code>df.replace(to_replace=[r&quot;\\t|\\n|\\r&quot;, &quot;\t|\n|\r&quot;], value=[&quot;&quot;,&quot;&quot;], regex=True, inplace=True)
</code></pre>
worked for me.
Source:
<a href="https://gist.github.com/smram/d6ded3c9028272360eb65bcab564a18a" rel="noreferrer">https://gist.github.com/smram/d6ded3c9028272360eb65bcab564a18a</a>

entityMap|blocks|key|9cjvc|text|要删除回车符(\r)，请换行符(\n)+%2B+tab+(\t)+)|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|9hhih|df+=+df.replace(r'\r%2B%7C\n%2B%7C\t%2B','',+regex=True)|code-block|syntax|javascript|3otn9^0|7|2|G|3|R|2|0|0^^$0|$]|1|@$2|3|4|5|6|7|8|M|9|@$A|N|B|O|C|D]|$A|P|B|Q|C|D]|$A|R|B|S|C|D]]|E|@]|F|$]]|$2|G|4|H|6|I|8|T|9|@]|E|@]|F|$J|K]]|$2|L|4|-4|6|7|8|U|9|@]|E|@]|F|$]]]]

To remove carriage return (<code>\r</code>), new line (<code>\n)</code> and tab (<code>\t</code>)
<pre><code>df = df.replace(r'\r+|\n+|\t+','', regex=True)
</code></pre>

I've used multiple ways of splitting and stripping the strings in my pandas dataframe to remove all the '\n'characters, but for some reason it simply doesn't want to delete the characters that are attached to other words, even though I split them. I have a pandas dataframe with a column that captures text from web pages using Beautifulsoup. The text has been cleaned a bit already by beautifulsoup, but it failed in removing the newlines attached to other characters. My strings look a bit like this:

"hands-on\ndevelopment of games. We will study a variety of software technologies\nrelevant to games including programming languages, scripting\nlanguages, operating systems, file systems, networks, simulation\nengines, and multi-media design systems. We will also study some of\nthe underlying scientific concepts from computer science and related\nfields including"

Is there an easy python way to remove these "\n" characters? 

Thanks in advance!

removing newlines from messy strings in pandas dataframe cells?

文件系统

 我使用了多种方法拆分和剥离我的pandas数据帧中的字符串，以删除所有‘\n’字符，但出于某种原因，它根本不想删除附加到其他单词的字符，即使我拆分了它们。我有一个熊猫数据框架，它有一个列，可以使用Beautifulsoup从网页中捕获文本。美汤已经清理了文本，但无法删除附加到其他字符的换行符。我的字符串看起来有点像这...

问从pandas dataframe单元格的乱七八糟的字符串中删除换行符？
EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问从pandas dataframe单元格的乱七八糟的字符串中删除换行符？EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问从pandas dataframe单元格的乱七八糟的字符串中删除换行符？
EN