Description Usage Format Source References Examples
Datasets with age-specific male and female historical population estimates.
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Data frames with one row per country and age group. For each country there are 21 age groups. It contains the following variables:
country
Country name.
country_code
Numerical Location Code (3-digit codes following ISO 3166-1 numeric standard) - see http://en.wikipedia.org/wiki/ISO_3166-1_numeric.
age
A character string representing an age interval. For each country there are 21 values: “0-4”, “5-9”, “10-14”, “15-19”, “20-24”, “25-29”, “30-34”, “35-39”, “40-44”, “45-49”, “50-54”, “55-59”, “60-64”, “65-69”, “70-74”, “75-79”, “80-84”, “85-89”, “90-94”, “95-99”, and “100+” in that order.
1950
, 1955
, ...Population estimate for the given time.
These datasets are based on estimates and projections of United Nations, Department of Economic and Social Affairs, Population Division (2009).
World Population Prospects: The 2008 Revision. Special Tabulations.
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'data.frame': 4137 obs. of 16 variables:
$ country : Factor w/ 197 levels "Afghanistan",..: 1 1 1 1 1 1 1 1 1 1 ...
$ country_code: int 4 4 4 4 4 4 4 4 4 4 ...
$ age : Factor w/ 21 levels "0-4","10-14",..: 1 11 2 4 5 6 7 8 9 10 ...
$ 1950 : num 736 565 494 434 375 ...
$ 1955 : num 767 638 545 475 411 ...
$ 1960 : num 855 672 616 525 452 ...
$ 1965 : num 962 756 651 596 501 ...
$ 1970 : num 1095 860 733 630 570 ...
$ 1975 : num 1247 988 837 713 605 ...
$ 1980 : num 1317 1048 888 750 632 ...
$ 1985 : num 1180 931 789 667 557 ...
$ 1990 : num 1223 967 809 685 573 ...
$ 1995 : num 1780 1405 1176 983 822 ...
$ 2000 : num 2019 1615 1349 1127 932 ...
$ 2005 : num 2343 1938 1639 1367 1130 ...
$ 2010 : num 2658 2266 1973 1665 1376 ...
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