import pandas as pd
import numpy as np
from pandas import Series
from pandas import DataFrame

date_list = [{'yyyy-mm-dd': '2000-06-27'},
         {'yyyy-mm-dd': '2002-09-24'},
         {'yyyy-mm-dd': '2005-12-20'}]

df = pd.DataFrame(date_list, columns = ['yyyy-mm-dd'])

df
   yyyy-mm-dd
0  2000-06-27
1  2002-09-24
2  2005-12-20

‘-’를 기준으로 나눈 첫 번째 값인 yyyy의 값을 year라는 새로운 열을 만들어 넣는 과정

def extract_year(row):
    return row.split('-')[0]

df['year'] = df['yyyy-mm-dd'].apply(extract_year)
df
   yyyy-mm-dd  year
0  2000-06-27  2000
1  2002-09-24  2002
2  2005-12-20  2005

• apply 함수에 파라미터 전달하기

def extract_year(year, current_year):
    return current_year - int(year)

df['age'] = df['year'].apply(extract_year, current_year=2022)
df
   yyyy-mm-dd  year  age
0  2000-06-27  2000   22
1  2002-09-24  2002   20
2  2005-12-20  2005   17

def get_introduce(age, prefix, suffix):
    return prefix + str(age) + suffix

df['introduce'] = df['age'].apply(get_introduce, prefix="I am ", suffix=" years old")
df
   yyyy-mm-dd  year  age          introduce
0  2000-06-27  2000   22  I am 22 years old
1  2002-09-24  2002   20  I am 20 years old
2  2005-12-20  2005   17  I am 17 years old

• apply 함수에 여러개의 column 값 사용하기

def get_introduce2(row):
    return "I was born in "+str(row.year)+" my age is "+str(row.age)

df.introduce = df.apply(get_introduce2, axis=1)

df
   yyyy-mm-dd  year  age                        introduce
0  2000-06-27  2000   22  I was born in 2000 my age is 22
1  2002-09-24  2002   20  I was born in 2002 my age is 20
2  2005-12-20  2005   17  I was born in 2005 my age is 17