Split one colum into two by multiple delimiter characters in Python

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For a example dataframe has words column, I want to split each row by either llo or lut, into two columns: words1 and words2.

                 words
0           helloworld
1          hellomadame
2           salutmonde
3          salutmadame
4    englishhelloworld
5   englishhellomadame
6   francaissalutmonde
7  francaissalutmadame

How could I get the follow output? Thank you.

          words1  words2
0          hello   world
1          hello  madame
2          salut   monde
3          salut  madame
4   englishhello   world
5   englishhello  madame
6  francaissalut   monde
7  francaissalut  madame

I try with df.words.str.split('llo | lut', expand=True), but it doesn't work out. Someone could help? Many thanks.

                     0
0           helloworld
1          hellomadame
2           salutmonde
3          salutmadame
4    englishhelloworld
5   englishhellomadame
6   francaissalutmonde
7  francaissalutmadame

Use Series.str.replace with added space after strings llo or lut and then use Series.str.split:

df = df['words'].str.replace('(llo|lut)', r'\1 ', n=1).str.split(expand=True)
df.columns=['words1','words2']
print (df)
          words1           words2
0          hello            world
1          hello           madame
2          salut            monde
3          salut           madame
4   englishhello            world
5   englishhello           madame
6  francaissalut            monde
7  francaissalut           madame

Split string with multiple delimiters in Python, Luckily, Python has this built-in :) import re re.split('; |, ',str). Update: Following your comment: >>> a='Beautiful, is; better*than\nugly' >>> import� Often you may have a column in your pandas data frame and you may want to split the column and make it into two columns in the data frame. For example, one of the columns in your data frame is full name and you may want to split into first name and last name (like the figure shown below).

Not a very Pythonic and efficient solution, but this will do the job

df = df.words.str.split('(llo|lut)', expand=True)
df[0] = df[0] + df[1]
df = df.drop(1, axis = 1)
df = df.rename(columns = {0 : "words1", 2 : "words2"})

This will output

    words1             words2
0   hello              world
1   hello              madame
2   salut              monde
3   salut              madame
4   englishhello       world
5   englishhello       madame
6   francaissalut      monde
7   francaissalut      madame

In rename, the dictionary keys had to be 0 and 2, because after concatenation, the dataframe looks like

    0              1    2
0   hello          llo  world
1   hello          llo  madame
2   salut          lut  monde
3   salut          lut  madame
4   englishhello   llo  world
5   englishhello   llo  madame
6   francaissalut  lut  monde
7   francaissalut  lut  madame

And after dropping column 1, it becomes

    0               2
0   hello           world
1   hello           madame
2   salut           monde
3   salut           madame
4   englishhello    world
5   englishhello    madame
6   francaissalut   monde
7   francaissalut   madame

The column names are 0 and 2, hence renaming of 0 and 2 is done. Hope this helps!

how to split a string in python with multiple delimiters Code Example, Get code examples like "how to split a string in python with multiple delimiters" 1. str = 'Lorem; ipsum. dolor sit amet, consectetur adipiscing elit.' 2 split with two delimiters python � python split a string at either of 2 characters that merges multiple columns into a vector column � a list inside a list python� Python | Pandas Split strings into two List/Columns using str.split() Last Updated: 07-05-2019 Pandas provide a method to split string around a passed separator/delimiter.

Just use a single regex to split the column:

(?<=l(?:lo|ut))
(?<=llo|lut)

See the regex demo. The pattern is a positive lookbehind that matches a location that is immediately preceded with llo or lut.

Python demo:

import pandas as pd

df = pd.DataFrame({"words": ["helloworld","hellomadame","salutmonde","salutmadame","englishhelloworld","englishhellomadame","francaissalutmonde","francaissalutmadame"]})

df = df['words'].str.split(r'(?<=l(?:lo|ut))', expand=True)
df.columns=['words1','words2']

Output:

>>> df
          words1  words2
0          hello   world
1          hello  madame
2          salut   monde
3          salut  madame
4   englishhello   world
5   englishhello  madame
6  francaissalut   monde
7  francaissalut  madame

Python, Python | Pandas Split strings into two List/Columns using str.split() Pandas provide a method to split string around a passed separator/delimiter. as a list in a series or it can also be used to create multiple column data frames Python | Ways to split strings on Uppercase characters � Python | Split strings� Let’s see how to split a text column into two columns in Pandas DataFrame. Method #1 : Using Series.str.split() functions. Split Name column into two different columns. By default splitting is done on the basis of single space by str.split() function.

Python, This method finds all the matching instances and returns each of them in a list. This way of splitting is best used when you don't know the exact� Split by multiple different delimiters. The following two are useful to remember even if you are not familiar with regular expressions. Enclose a string with [] to match any single character in it. It can be used to split by multiple different characters.

Python string split() example, Python example to split string into tokens using the delimiters in the string. Learn to split string using single or multiple delimiters in python. 1. Split string.split() method. Easiest way to split a string using a delimiter is using string.split( 2. Split string with multiple delimiters. The split() method of string objects is really meant� String split the column of dataframe in pandas python: String split can be achieved in two steps (i) Convert the dataframe column to list and split the list (ii) Convert the splitted list into dataframe. Step 1: Convert the dataframe column to list and split the list: df1.State.str.split().tolist()

In real-time, you might get the data that has merged columns (one column with too much information). In that situation, you can use Power BI Split Columns option to split that column into multiple columns. This article shows you how to Split Columns in Power BI with example.

Comments
  • You may get the result using a single call to Series.str.split, see this answer.
  • @ahbon - it is reference to (llo|lut) - add space after llo or lut
  • @ahbon - I think problem should be multiple llo or lut, if want split by first llo or lut use df = df['words'].str.replace('(llo|lut)', r'\1 ', n=1).str.split(expand=True).add_prefix('words')
  • Get it, and how can I split and set names instead of add_prefix?
  • Sorry, in my data there are others columns besides words, so I don't want to set df['words'].str.replace('(llo|lut)', r'\1 ', n=1).str.split(expand=True) as df. Can I split words while keeping other columns?
  • @ahbon - Sure, use df[['words1','words2']] = df['words'].str.replace('(llo|lut)', r'\1 ', n=1).str.split(expand=True)