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openintro (version 2.4.0)

world_pop: World Population Data.

Description

From World Bank, population 1960-2020

Usage

world_pop

Arguments

Format

A data frame with 216 rows and 62 variables.

country

Name of country.

year_1960

population in 1960.

year_1961

population in 1961.

year_1962

population in 1962.

year_1963

population in 1963.

year_1964

population in 1964.

year_1965

population in 1965.

year_1966

population in 1966.

year_1967

population in 1967.

year_1968

population in 1968.

year_1969

population in 1969.

year_1970

population in 1970.

year_1971

population in 1971.

year_1972

population in 1972.

year_1973

population in 1973.

year_1974

population in 1974.

year_1975

population in 1975.

year_1976

population in 1976.

year_1977

population in 1977.

year_1978

population in 1978.

year_1979

population in 1979.

year_1980

population in 1980.

year_1981

population in 1981.

year_1982

population in 1982.

year_1983

population in 1983.

year_1984

population in 1984.

year_1985

population in 1985.

year_1986

population in 1986.

year_1987

population in 1987.

year_1988

population in 1988.

year_1989

population in 1989.

year_1990

population in 1990.

year_1991

population in 1991.

year_1992

population in 1992.

year_1993

population in 1993.

year_1994

population in 1994.

year_1995

population in 1995.

year_1996

population in 1996.

year_1997

population in 1997.

year_1998

population in 1998.

year_1999

population in 1999.

year_2000

population in 2000.

year_2001

population in 2001.

year_2002

population in 2002.

year_2003

population in 2003.

year_2004

population in 2004.

year_2005

population in 2005.

year_2006

population in 2006.

year_2007

population in 2007.

year_2008

population in 2008.

year_2009

population in 2009.

year_2010

population in 2010.

year_2011

population in 2011.

year_2012

population in 2012.

year_2013

population in 2013.

year_2014

population in 2014.

year_2015

population in 2015.

year_2016

population in 2016.

year_2017

population in 2017.

year_2018

population in 2018.

year_2019

population in 2019.

year_2020

population in 2020.

Examples

Run this code
library(dplyr)
library(ggplot2)
library(tidyr)

# List percentage of population change from 1960 to 2020
world_pop %>%
  mutate(percent_change = round((year_2020 - year_1960) / year_2020 * 100, 2)) %>%
  mutate(rank_pop_change = round(rank(-percent_change)), 0) %>%
  select(rank_pop_change, country, percent_change) %>%
  arrange(rank_pop_change)

# Graph population in millions by decade for specified countries
world_pop %>%
  select(
    country, year_1960, year_1970, year_1980, year_1990,
    year_2000, year_2010, year_2020
    ) %>%
  filter(country %in% c("China", "India", "United States")) %>%
  pivot_longer(
    cols = c(year_1960, year_1970, year_1980, year_1990, year_2000, year_2010, year_2020),
    names_to = "year",
    values_to = "population"
  ) %>%
  mutate(year = as.numeric(gsub("year_", "", year))) %>%
  ggplot(aes(year, population, color = country)) +
  geom_point() +
  geom_smooth(method = "loess", formula = "y ~ x") +
  labs(
    title = "Population",
    subtitle = "by Decade",
    x = "Year",
    y = "Population (in millions)",
    color = "Country"
  )

Run the code above in your browser using DataLab