fertility.csv

Human overpopulation is a growing concern and has been associated with depletion of Earth’s natural resources (water is a big one that ) and degredation of the environment. This, in turn, has social and economic consequences such as global tension over resources such as water and food, higher cost of living and higher unemployment rates. The data in fertility.csv were collected from several sources (e.g., World Bank) and are thought to correlate with fertility rates, a measure directly linked to population. The variables are:

Preview

# Import data
fertility = readr::read_csv(file = "https://raw.githubusercontent.com/zief0002/bespectacled-antelope/main/data/fertility.csv")

# View data
fertility
# A tibble: 124 × 7
   country      region                   ferti…¹ educ_…² infan…³ contr…⁴ gni_c…⁵
   <chr>        <chr>                      <dbl>   <dbl>   <dbl>   <dbl> <chr>  
 1 Albania      Europe and Central Asia     1.49     9.1    15        46 Upper/…
 2 Algeria      Middle East and North A…    2.78     5.9    17.2      57 Upper/…
 3 Armenia      Europe and Central Asia     1.39    10.8    14.7      57 Upper/…
 4 Austria      Europe and Central Asia     1.42     8.9     3.3      66 Upper  
 5 Azerbaijan   Europe and Central Asia     1.92    10.5    30.8      55 Upper/…
 6 Bahamas, The Latin America and the C…    1.97    11.1    13.9      45 Upper  
 7 Bangladesh   South Asia                  2.5      4.6    33.1      62 Low/Mi…
 8 Belgium      Europe and Central Asia     1.65    10.5     3.4      67 Upper  
 9 Belize       Latin America and the C…    3.08     9.2    15.7      51 Upper/…
10 Benin        Sub-Saharan Africa          5.13     2      58.5      16 Low    
# … with 114 more rows, and abbreviated variable names ¹​fertility_rate,
#   ²​educ_female, ³​infant_mortality, ⁴​contraceptive, ⁵​gni_class

References

Roser, M. (2017). Fertility rate. Our world in data.

UNICEF. (2016). State of the world’s children 2016. United Nations Population Division’s World Contraceptive Use, household surveys including Demographic and Health Surveys and Multiple Indicator Cluster Surveys.

World Bank (2019). World Bank open data.