I have a column (stud_info) in the below format
stud_info = """Name: Mark
Address:
PHX, AZ
Hobbies:
1. Football
2. Programming
3. Squash"""
The column (stud_info) from raw data is stud_info which contains data as multiline text. I need to split it into 3 columns (Name, Address, and Hobbies). For a simple split, we can do it via lambda functions but this is a multiline split and the column names are also a part of the data. (ie the text Name, Address, and Hobbies should not be a part of the columns). The final columns should look like
Please suggest a way to do it using pandas.
Given:
df = pd.DataFrame({'stud_info': {0: 'Name: Mark\nAddress: \nPHX, AZ\nHobbies: \n1. Football\n2. Programming\n3. Squash'}})
We can define a Regex Expression for your particular formatting, and use the pd.Series.str.extract
method to break the groups into different columns. For an explanation of the pattern see Regexr .
import re
pattern = 'Name:\s(.+)\nAddress:\s\n(.+)\nHobbies:\s\n(.+)'
# We need flags=re.DOTALL to allow the final group to encompass multiple lines.
df[['Name', 'Address', 'Hobbies']] = df.stud_info.str.extract(pattern, flags=re.DOTALL)
print(df[['Name', 'Address', 'Hobbies']])
Output:
Name Address Hobbies
0 Mark PHX, AZ 1. Football\n2. Programming\n3. Squash
My solution:
import pandas as pd
import re
txt = """Name: Mark
Address:
PHX, AZ
Hobbies:
1. Football
2. Programming
3. Squash"""
pattern = re.compile('Name:\s(.+)\nAddress:\s\n(.+)\nHobbies:\s\n([\w\W]*)')
re_match = pattern.match(txt)
df = pd.DataFrame([list(re_match.groups())], columns=['Name', 'Address', 'Hobbies'])
df
Output:
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