Datasets:

electricsheepafrica
/

Total-Alcohol-Per-Capita-15-Years-Of-Age-Consumption-for-African-Countries

Year stringdate 2000-01-01 00:00:00 2019-01-01 00:00:00	Algeria float64 0.21 0.33	Angola float64 3.28 5.01	Benin float64 1.57 4.55	Botswana float64 3.37 3.83	Burkina Faso float64 3.77 4.48	Burundi float64 2.35 4.18	Cabo Verde float64 3.02 3.7	Cameroon float64 5.73 7.03	Central African Republic float64 1.36 1.64	Chad float64 1.43 2.42	Comoros float64 0.14 0.27	Congo float64 1.91 3.78	Côte d'Ivoire float64 1.44 2.24	Democratic Republic of the Congo float64 1.57 5.04	Djibouti float64 0.27 0.39	Egypt float64 0.13 0.17	Equatorial Guinea float64 3.86 5.29	Eritrea float64 0.63 0.81	Eswatini float64 3.51 4.65	Ethiopia float64 0.75 1.69	Gabon float64 4.04 5.54	Gambia float64 0.69 2.06	Ghana float64 2.75 3.32	Guinea float64 0.25 0.35	Guinea-Bissau float64 2.02 2.36	Kenya float64 1.3 1.63	Lesotho float64 1.64 2.16	Liberia float64 2.19 2.65	Libya float64 0.03 0.05	Madagascar float64 0.69 0.98	Malawi float64 1.71 2.11	Mali float64 0.45 1.92	Mauritius float64 3.74 4.03	Morocco float64 0.26 0.33	Mozambique float64 0.71 1.18	Namibia float64 2.23 2.91	Niger float64 0.14 0.17	Nigeria float64 2.06 3.78	Rwanda float64 0.89 1.23	Sao Tome and Principe float64 3.04 4.37	Senegal float64 0.29 0.34	Seychelles float64 4.29 6.42	Sierra Leone float64 0.19 0.23	South Africa float64 4 4.31	Sudan float64 0 0.13	Togo float64 0.98 1.2	Tunisia float64 0.79 0.91	Uganda float64 6.61 9.15	Zambia float64 2 2.26	Zimbabwe float64 1.56 1.97
2000-01-01	0.21085	3.27894	1.6308	3.42227	3.82967	4.17502	3.01911	6.09112	1.54412	1.4273	0.14229	1.9128	2.23579	5.04185	0.38679	0.12704	4.50054	0.63299	4.65306	0.75116	5.53696	2.00203	3.32417	0.24854	2.26668	1.32623	1.8873	2.64543	0.02773	0.98208	1.71299	0.48517	4.03356	0.3086	0.72831	2.30304	0.13635	3.77651	1.04651	4.16081	0.33979	4.28665	0.18806	4.30975	0	1.06442	0.81084	9.15241	2.20062	1.65698
2005-01-01	0.28634	4.11417	1.56752	3.63756	3.96144	3.61563	3.18864	6.54081	1.55821	1.71782	0.2731	1.98826	2.2239	3.46405	0.38953	0.14417	5.29163	0.73505	4.04907	0.84117	5.0395	2.06493	3.14478	0.28371	2.36186	1.29503	1.82667	2.54916	0.05254	0.6855	1.86065	0.44803	3.92945	0.31022	0.70564	2.23227	0.14272	3.77536	1.03263	4.36934	0.34189	4.53021	0.1861	4.17304	0	1.16453	0.83822	8.84643	2.08131	1.55798
2010-01-01	0.27557	5.01013	3.74502	3.60922	3.77248	3.42234	3.43518	7.03467	1.63732	2.04561	0.16042	2.89659	1.5829	2.10093	0.38501	0.1669	5.25729	0.80955	3.51102	0.96118	4.9274	1.7284	3.28325	0.25873	2.02305	1.46891	1.72432	2.34258	0.02866	0.75987	2.10811	1.4666	3.87142	0.32652	0.79974	2.46232	0.15095	2.49256	0.88779	3.62498	0.31464	4.38572	0.2266	4.14929	0.04662	1.19598	0.78993	7.46453	2.00009	1.79566
2015-01-01	0.32507	4.62532	4.48948	3.36626	4.45975	2.37258	3.46353	6.11473	1.35907	2.4227	0.15461	3.40761	1.44203	1.72967	0.32751	0.15232	4.90462	0.75574	3.64169	1.31649	4.73888	1.14664	3.02813	0.35345	2.04633	1.58197	1.64419	2.19025	0.03534	0.72967	1.94665	1.92309	3.74479	0.25804	1.07225	2.90874	0.16867	2.20223	0.94155	3.55773	0.28772	6.4243	0.21823	4.11248	0.13315	1.15593	0.90779	7.06729	2.17279	1.97038
2019-01-01	0.32223	3.83557	4.55039	3.82688	4.48465	2.3506	3.70441	5.72871	1.37815	2.03441	0.18431	3.77515	1.59141	1.57265	0.2705	0.13563	3.8582	0.73388	3.71564	1.6905	4.03771	0.69431	2.74802	0.3387	2.11971	1.62852	2.1647	2.21599	0.03133	0.71288	1.97096	1.8392	3.81535	0.2967	1.17669	2.82853	0.13627	2.06143	1.23126	3.04279	0.30436	6.36394	0.20382	3.99561	0.02132	0.97614	0.91337	6.61456	2.25537	1.95997

Total alcohol per capita (>= 15 years of age) consumption (litres of pure alcohol) for African Countries

Dataset Description

This dataset contains 'Total alcohol per capita (>= 15 years of age) consumption (litres of pure alcohol)' data for all 54 African countries, sourced from the World Health Organization (WHO). The data is structured with years as rows and countries as columns, facilitating time-series analysis.

The data is measured in: >= 15 years of age.

Missing values have been handled using linear interpolation followed by forward and backward filling to ensure a complete dataset.

How to Use

You can load the data using pandas:

import pandas as pd

df = pd.read_csv('hf://datasets/electricsheepafrica/Total-Alcohol-Per-Capita-15-Years-Of-Age-Consumption-for-African-Countries/total_alcohol_per_capita_____15_years_of_age__consumption__litres_of_pure_alcohol_.csv')
print(df.head())

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