How do I split a Dataframe column in two but taking into account that sometimes there is nothing to split and the value belongs to the second column?

Question

Imagine I have:

          COLUMN A
0    00000-UNITED STATES
1    01000-ALABAMA
2    01001-Autauga County, AL
3    01003-Baldwin County, AL
4    Barbour County, AL

I want to split them in two columns but making sure that if the value in the last row is a string, it goes to the second column. If it's an int it goes to the first column. Eg with string:

          COLUMN B       COLUMN C
0          00000      UNITED STATES
1          01000         ALABAMA
2          01001     Autauga County, AL
3          01003     Baldwin County, AL
4                    Barbour County, AL

I tried this:

df[['B','C']] = df.A.str.split(" - ", n = 1, expand=True)

And it returned this obviously:

          COLUMN B       COLUMN C
0          00000      UNITED STATES
1          01000         ALABAMA
2          01001     Autauga County, AL
3          01003     Baldwin County, AL
4     Barbour County, AL

Answer 1

Try with extract and a regex to have the second capture group be the value after the optional - :

df[['B', 'C']] = df['A'].str.extract(r"(\d+$|\d+(?=\s*-))?(?:\s*-\s*)?(.+)?")

                          A       B                   C
0       00000-UNITED STATES   00000       UNITED STATES
1             01000-ALABAMA   01000             ALABAMA
2  01001-Autauga County, AL   01001  Autauga County, AL
3  01003-Baldwin County, AL   01003  Baldwin County, AL
4        Barbour County, AL     NaN  Barbour County, AL
5                     10234   10234                 NaN
6                32 Alabama     NaN          32 Alabama
7            432423 - state  432423               state

---

Complete Code:

import pandas as pd

df = pd.DataFrame({
    'A': ['00000-UNITED STATES', '01000-ALABAMA',
          '01001-Autauga County, AL', '01003-Baldwin County, AL',
          'Barbour County, AL', '10234', '32 Alabama', '432423 - state']
})

df[['B', 'C']] = df['A'].str.extract(r"(\d+$|\d+(?=\s*-))?(?:\s*-\s*)?(.+)?")

Answer 2

You could create two functions to extract the desired elements from COLUMN A and assign to COLUMN B and COLUMN C:

def get_col_b(item):
    if '-' in item:
        return item.split('-')[0]
    else:
        return ''

def get_col_c(item):
    if '-' in item:
        return item.split('-')[1]
    else:
        return item

Create the columns and then drop COLUMN A:

df['COLUMN B'] = df['COLUMN A'].apply(get_col_b)
df['COLUMN C'] = df['COLUMN A'].apply(get_col_c)
cols = ['COLUMN B', 'COLUMN C']
df = df[cols]