Creating New Column In Pandas Dataframe Using Regex

Question

I have a column in a pandas df of type object that I want to parse to get the first number in the string, and create a new column containing that number as an int.

For example:

Existing df

    col
    'foo 12 bar 8'
    'bar 3 foo'
    'bar 32bar 98'

Desired df

    col               col1
    'foo 12 bar 8'    12
    'bar 3 foo'       3
    'bar 32bar 98'    32

I have code that works on any individual cell in the column series

int(re.search(r'\d+', df.iloc[0]['col']).group())

The above code works fine and returns 12 as it should. But when I try to create a new column using the whole series:

df['col1'] = int(re.search(r'\d+', df['col']).group())

I get the following Error:

TypeError: expected string or bytes-like object

I tried wrapping a str() around df['col'] which got rid of the error but yielded all 0's in col1

I've also tried converting col to a list of strings and iterating through the list, which only yields the same error. Does anyone know what I'm doing wrong? Help would be much appreciated.

Solution

This will do the trick:

search = []    
for values in df['col']:
    search.append(re.search(r'\d+', values).group())

df['col1'] = search

the output looks like this:

            col    col1
0  foo 12 bar 8      12
1     bar 3 foo       3
2  bar 32bar 98      32

Comments

[RolfBly]

The list has the same name as the regex method (search), which I find a bit confusing. mylist = [], mylist.append... would imho make it a clearer example.