Command Line Interface¶
Installation¶
pip install lost-years
After installation, three command-line tools are available:
lost_years_ssa- US Social Security Administration datalost_years_hld- Human Life-Table Database (international)lost_years_who- World Health Organization data
Basic Usage¶
All commands follow a similar pattern:
lost_years_[source] input.csv -o output.csv
Where:
[source]isssa,hld, orwhoinput.csvis your input file with required columnsoutput.csvis the output file with appended life expectancy data
Commands¶
lost_years_ssa¶
Calculate expected years lost using US SSA data:
lost_years_ssa input.csv -o output.csv
Required columns in input file:
age- Age at death (0-119)sex- Sex (M/F)year- Year of death
Options:
-a, --age- Column name for age (default:age)-s, --sex- Column name for sex (default:sex)-y, --year- Column name for year (default:year)-o, --output- Output file path
Output columns added:
ssa_age- Matched age usedssa_year- Matched year usedssa_life_expectancy- Expected years remaining
lost_years_hld¶
Calculate expected years lost using international HLD data:
lost_years_hld input.csv -o output.csv
Required columns in input file:
country- Country code (e.g., BRA, CHE)age- Age at deathsex- Sex (M/F)year- Year of death
Options:
-c, --country- Column name for country (default:country)-a, --age- Column name for age (default:age)-s, --sex- Column name for sex (default:sex)-y, --year- Column name for year (default:year)-o, --output- Output file path--download-hld- Download latest HLD data
Output columns added:
hld_country- Country codehld_age- Matched agehld_year1- Matched yearhld_life_expectancy- Expected years remainingAdditional columns for sub-populations if available
lost_years_who¶
Calculate expected years lost using WHO data:
lost_years_who input.csv -o output.csv
Required columns in input file:
country- Country codeage- Age at deathsex- Sex (M/F)year- Year of death
Options:
-c, --country- Column name for country (default:country)-a, --age- Column name for age (default:age)-s, --sex- Column name for sex (default:sex)-y, --year- Column name for year (default:year)-o, --output- Output file path
Output columns added:
who_country- Country codewho_age- Matched agewho_year- Matched yearwho_sex- Sex code usedwho_life_expectancy- Expected years remaining
Examples¶
Example 1: US Data¶
Input file us_deaths.csv:
age,sex,year
65,M,2020
45,F,2019
80,M,2018
Command:
lost_years_ssa us_deaths.csv -o us_deaths_with_life_exp.csv
Example 2: International Comparison¶
Input file international.csv:
country,age,sex,year
BRA,65,M,2015
CHE,65,M,2015
JPN,65,M,2015
Command:
lost_years_hld international.csv -o comparison.csv
Example 3: Custom Column Names¶
Input file with non-standard column names:
nation,age_at_death,gender,death_year
USA,70,M,2020
Command:
lost_years_ssa input.csv \
-a age_at_death \
-s gender \
-y death_year \
-o output.csv
Data Coverage¶
SSA (United States)¶
Years: 1900-2100 (projected)
Ages: 0-119
Sex: Male/Female
HLD (International)¶
Countries: 40+ countries
Years: Varies by country (typically 1950-2020)
Ages: 0-110+
Additional dimensions for some countries
WHO (Global)¶
Countries: 180+ countries
Years: 2000-2019
Ages: 5-year bands
Sex: Male/Female/Both
Notes¶
The tools automatically match to the closest available year and age if exact matches aren’t found
The matched values are included in output columns so you can verify what data was used
HLD may return multiple rows per input if sub-populations are available
For US-specific analysis, SSA provides the most detailed data
For international comparisons, use HLD or WHO for consistency