Add new column to Panda dataframe based on other column

Question

I'm trying to add a new column to a Panda dataset. This new column df['Year_Prod'] is derived from another one df['title'] from which I am extracting the year.

Data example:

country    designation     title
Italy      Vulkà Bianco    Nicosia 2013 Vulkà Bianco (Etna)         
Portugal   Avidagos        Quinta dos Avidagos 2011 Avidagos Red (Douro)      

Code:

import re

import pandas as pd

df=pd.read_csv(r'test.csv', index_col=0)

df['Year_Prod']=re.findall('\\d+', df['title'])

print(df.head(10))

I am getting the following error:

 File "C:\Python37\lib\site-packages\pandas\core\frame.py", line 3119, in __setitem__self._set_item(key, value)

  File "C:\Python37\lib\site-packages\pandas\core\frame.py", line 3194, in _set_item value = self._sanitize_column(key, value)

  File "C:\Python37\lib\site-packages\pandas\core\frame.py", line 3391, in _sanitize_column value = _sanitize_index(value, self.index, copy=False)

  File "C:\Python37\lib\site-packages\pandas\core\series.py", line 4001, in _sanitize_index raise ValueError('Length of values does not match length of ' 'index')

**ValueError: Length of values does not match length of index**

Please let me know your thoughts on this, thanks.

Answer 1

You can use pandas str.extract

df['Year_Prod']= df.title.str.extract('(\d{4})')

    country     designation     title                                          Year_Prod
0   Italy       Vulkà Bianco    Nicosia 2013 Vulkà Bianco (Etna)                2013
1   Portugal    Avidagos        Quinta dos Avidagos 2011 Avidagos Red (Douro)   2011

Edit: As @Paul H. suggested in comments, the reason your code doesn't work is that re.findall expects a string but you are passing a series. It can be done using apply where at every row, the value passed is a string but doesn't make much sense as str.extract is more efficient.

df.title.apply(lambda x: re.findall('\d{4}', x)[0])