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Suppose I have a pandas dataframe:

Id Book 
1 Harry Potter (1997)
2 Of Mice and Men (1937)
3 Babe Ruth Story, The (1948) Drama 948) Babe Ruth Story

How do I extract the year from the column?

Output should be:

Id Book Title Year
1 Harry Potter 1997
2 Of Mice and Men 1937
3 Babe Ruth Story, The 1948

So far I have tried:

movies['year'] = movies['title'].str.extract('([0-9(0-9)]+)', expand=False).str.strip()

and

books['year'] = books['title'].str[-5:-1]

I've messed around with some other things and haven't gotten it to work yet. Any suggestions?

How about a simple Regex:

text = 'Harry Potter (1997)'
re.findall('((d4))', text)
# ['1997'] Note that this is a list of "all" the occurrences.

With a Dataframe, it can be done like this:

text = 'Harry Potter (1997)'
df = pd.DataFrame('Book': text, index=[1])
pattern = '((d4))'
df['year'] = df.Book.str.extract(pattern, expand=False) #False returns a series

df
# Book year
# 1 Harry Potter (1997) 1997

Finally, if you actually want to separate the title and the data (taking the dataframe reconstruction from Philip in another answer):

df = pd.DataFrame(columns=['Book'], data=[['Harry Potter (1997)'],['Of Mice and Men (1937)'],['Babe Ruth Story, The (1948) Drama 948) Babe Ruth Story']])

sep = df['Book'].str.extract('(.*)((d4))', expand=False)

sep # A new df, separated into title and year
# 0 1 
# 0 Harry Potter 1997 
# 1 Of Mice and Men 1937
# 2 Babe Ruth Story, The 1948

Answer for the full series is actually this:

books['title'].str.findall('((d4))').str.get(0)

You could do the following.

import pandas as pd
df = pd.DataFrame(columns=['id','Book'], data=[[1,'Harry Potter (1997)'],[2,'Of Mice and Men (1937)'],[3,'Babe Ruth Story, The (1948) Drama 948) Babe Ruth Story']])

df['Year'] = df['Book'].str.extract(r'(?!()b(d+)1')

1. line: import pandas


2. line: create the dataframe for sake of understanding


3. line: create a new column 'Year', which is created from a string extraction on the column Book.

Use regex to find the digits. I use https://regex101.com/r/Bid0qA/1, which is a huge help in understanding how regex works.