import pandas as pd
import seaborn as sns
import re

# leyendo archivo
df = pd.read_csv('Limpieza.csv')

df

	Id?empleado	Name	Apellido	birth_date	género	area	salary	star_date	finish_date	promotion_date	type
0	00-0037846	Kimmy	Walczynski	06/04/1991	hombre	Engineering	$77,719	1/20/2002	NaN	NaN	0
1	00-0041533	Ignatius	Springett	6/29/1984	hombre	Business Development	$135,189	04/08/2019	NaN	NaN	0
2	00-0045747	Corbie	Bittlestone	7/29/1989	hombre	Sales	$122,484	10/12/2010	NaN	NaN	1
3	00-0055274	Baxy	Matton	9/14/1982	mujer	Services	$82,100	04/10/2005	NaN	NaN	0
4	00-0076100	Terrell	Suff	04/11/1994	mujer	Product Management	$114,648	9/29/2010	2029-10-29 06:09:38 UTC	NaN	1
...	...	...	...	...	...	...	...	...	...	...	...
22218	00-0076100	Terrell	Suff	04/11/1994	mujer	Product Management	$114,648	9/29/2010	2029-10-29 06:09:38 UTC	NaN	1
22219	00-0116166	Kacie	Offiler	1/18/1971	hombre	Engineering	$121,044	09/01/2018	NaN	NaN	0
22220	00-0363185	Sandro	Admans	11/19/1979	hombre	Product Management	$174,195	11/08/2012	NaN	NaN	1
22221	00-0380704	Eugene	Lehrahan	10/14/1988	mujer	Engineering	$66,031	6/27/2007	NaN	NaN	1
22222	00-0381660	Wainwright	Corfield	12/13/1996	hombre	Engineering	$164,055	2/20/2001	2008-12-05 01:21:48 UTC	NaN	0

22223 rows × 11 columns

def capitalize_english(name):
        return re.sub(
            r"(\w)(\w*)", lambda m: m.group(1).upper() + m.group(2).lower(), name
        )