import pandas as pd

from lost_years import lost_years_hld, lost_years_ssa

Prepare example input in DataFrame

Please look at country codes here:- https://www.lifetable.de/cgi-bin/country_codes.php

data = [
    {"year": 2003, "country": "THA", "age": 70, "sex": "M"},
    {"year": 2004, "country": "BRA", "age": 50, "sex": "M"},
    {"year": 2005, "country": "PHL", "age": 30, "sex": "F"},
    {"year": 2006, "country": "USA", "age": 10, "sex": "F"},
]
df = pd.DataFrame(data)
df

	year	country	age	sex
0	2003	THA	70	M
1	2004	BRA	50	M
2	2005	PHL	30	F
3	2006	USA	10	F

Get Life expectancy data columns from SSA dataset

Please note that SSA dataset is specific for USA only

lost_years_ssa(df)

	year	country	age	sex	ssa_age	ssa_year	ssa_life_expectancy
0	2003	THA	70	M	70	2022	14.09
1	2004	BRA	50	M	50	2022	29.05
2	2005	PHL	30	F	30	2022	51.25
3	2006	USA	10	F	10	2022	70.72

Get Human Life Table data columns from HLD dataset

lost_years_hld(df)

	year	country	age	sex	hld_country	hld_age	hld_sex	hld_year	hld_life_expectancy
0	2003	THA	70	M	THA	70	M	2005	10.79
1	2004	BRA	50	M	BRA	50	M	2004	24.96
2	2005	PHL	30	F	PHL	30	F	2000	46.13
3	2006	USA	10	F	USA	10	F	2006	70.81