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import numpy as np
import pandas as pds

h2015_data=pds.read_csv("../../data/raw/2015.csv")
h2016_data=pds.read_csv("../../data/raw/2016.csv")
h2017_data=pds.read_csv("../../data/raw/2017.csv")
h2018_data=pds.read_csv("../../data/raw/2018.csv")
h2019_data=pds.read_csv("../../data/raw/2019.csv")
hap_files=[h2015_data,h2016_data,h2017_data,h2018_data,h2019_data]

#Health Indicators
alco=pds.read_csv("../../data/raw/Alcohol_consumption_2015-2019.csv")
homi=pds.read_csv("../../data/raw/homicide_2015-2019.csv")
road=pds.read_csv("../../data/raw/road_traffic_incidence_2015-2019.csv")
smoke=pds.read_csv("../../data/raw/smoking_2015-2018.csv")
suic=pds.read_csv("../../data/raw/suicide_rates_2015-2019.csv")

#h2021_data=pds.read_csv("../../data/raw/world-happiness-report-2021.csv")
#print(h2019_data[["Country or region","Score","Healthy life expectancy"]])
alco[['Indicator']]

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