removing newlines from messy strings in pandas dataframe cells?

Question

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!

Solution 1

EDIT: the correct answer to this is:

df = df.replace(r'\n',' ', regex=True) 

I think you need replace:

df = df.replace('\n','', regex=True)

Or:

df = df.replace('\n',' ', regex=True)

Or:

df = df.replace(r'\\n',' ', regex=True)

Sample:

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 

Solution 2

df.replace(to_replace=[r"\\t|\\n|\\r", "\t|\n|\r"], value=["",""], regex=True, inplace=True)

worked for me.

Source:

https://gist.github.com/smram/d6ded3c9028272360eb65bcab564a18a

Solution 3

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

Solution 4

To remove carriage return (\r), new line (\n) and tab (\t)

df = df.replace(r'\r+|\n+|\t+','', regex=True)

Solution 5

   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)

This worked for the messy data I had.

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