Overview

The UNAIDS Organization is an entity of the United Nations that looks to reduce the transmission of AIDS and provide resources to those currently affected by the disease. The following data set contains information on the number of those affected by the disease, new cases of the disease being reported, and AIDS-related deaths for a large set of countries over the course of 1990 - 2015.

http://aidsinfo.unaids.org/

Explore Structure




Index Type Example Value
0 dict { }
... ... ...
Key Type Example Value Comment
"Incidence Rate Among Adults" float 0.0017 The number of reported cases of AIDS in adults (15-49 years old).
"Adults" int 91 The number of reported cases of AIDS in all adults (15+ years old).
"All Ages" int 94 The total number of reported cases of AIDS in this year.
"Children" int 4 The number of reported cases of AIDS in children (0-14 years old).
"Female Adults" float 22.0 The number of reported cases of AIDS in female adults (15+ years old).
"Male Adults" int 69 The number of reported cases of AIDS in male adults (15+ years old).
Key Type Example Value Comment
"Adults" int 354 The number of Adults (greater than 15 years old) suffering from AIDS in this year.
"Total" int 361 The total number of people suffering from AIDS in this year.
"Male Adults" int 273 The number of Adult Men (greater than 15 years old) suffering from AIDS in this year.
"Female Adults" int 82 The number of Adult Women (greater than 15 years old) suffering from AIDS in this year.
"Children" int 7 The number of Children (less than 15 years old) suffering from AIDS in this year.
Key Type Example Value Comment
"Young Men" float 0.003 The percentage of the population of Young Men (15-24 years old) suffering from AIDS in this year.
"Adults" float 0.0061 The percentage of the population of Young Men (15-49 years old) suffering from AIDS in this year.
"Young Women" float 0.0019 The percentage of the population of Young Women (15-24 years old) suffering from AIDS in this year.
Key Type Example Value Comment
"Country" str "Afghanistan"
[Preview ]
The name of the country.
"Data" dict { }
"Year" int 1990 4-digit year
Value Count
"Botswana" 26
"Paraguay" 26
"Greece" 26
"Egypt" 26
"Mexico" 26
"Myanmar" 26
"Honduras" 26
"Guyana" 26
"South Sudan" 26
"Latvia" 26
"Trinidad and Tobago" 26
"Kyrgyzstan" 26
"Mauritania" 26
"Kazakhstan" 26
"Zimbabwe" 26
"Papua New Guinea" 26
"Zambia" 26
"Suriname" 26
"Democratic Republic of the Congo" 26
"Nepal" 26
"Sudan" 26
"Italy" 26
"Madagascar" 26
"Nicaragua" 26
"Burundi" 26
"Colombia" 26
"Djibouti" 26
"Uzbekistan" 26
"Equatorial Guinea" 26
"Uruguay" 26
"Venezuela (Bolivarian Republic of)" 26
"United Republic of Tanzania" 26
"Namibia" 26
"Morocco" 26
"Philippines" 26
"Gambia" 26
"Georgia" 26
"Sierra Leone" 26
"Belize" 26
"Haiti" 26
"Thailand" 26
"C?te d'Ivoire" 26
"El Salvador" 26
"Algeria" 26
"Belarus" 26
"Ecuador" 26
"Nigeria" 26
"Bahamas" 26
"Costa Rica" 26
"Republic of Moldova" 26
"Panama" 26
"Guinea" 26
"Brazil" 26
"Niger" 26
"Uganda" 26
"Mozambique" 26
"Senegal" 26
"Malaysia" 26
"South Africa" 26
"Chad" 26
"Angola" 26
"Mali" 26
"Australia" 26
"Central African Republic" 26
"Indonesia" 26
"Ukraine" 26
"Bolivia (Plurinational State of)" 26
"Dominican Republic" 26
"Togo" 26
"Cuba" 26
"Benin" 26
"Malawi" 26
"Peru" 26
"Somalia" 26
"Rwanda" 26
"Mongolia" 26
"Iran (Islamic Republic of)" 26
"Eritrea" 26
"Bangladesh" 26
"Afghanistan" 26
"Tajikistan" 26
"Kenya" 26
"Lesotho" 26
"Azerbaijan" 26
"Viet Nam" 26
"Pakistan" 26
"Yemen" 26
"Gabon" 26
"Jamaica" 26
"Liberia" 26
"Spain" 26
"Guatemala" 26
"Cape Verde" 26
"Ghana" 26
"Burkina Faso" 26
"Cameroon" 26
"Argentina" 26
"Swaziland" 26
"Sri Lanka" 26
Key Type Example Value Comment
"HIV Prevalence" dict { }
"AIDS-Related Deaths" dict { }
"New HIV Infections" dict { }
"People Living with HIV" dict { }

Downloads

Download all of the following files.

Usage

This library has 1 function you can use.
import aids
list_of_report = aids.get_reports()
Additionally, some of the functions can return a sample of the Big Data using an extra argument. If you use this sampled Big Data, it may be much faster. When you are sure your code is correct, you can remove the argument to use the full dataset.
import aids
# These may be slow!
list_of_report = aids.get_reports(test=True)

Documentation

 aids.get_reports(test=False)

Returns aids reports from the dataset.