Gustavo Arruda Franco 2020-12-03
knitr::opts_chunk$set(echo = TRUE, warnings = FALSE, message = FALSE)
library(gapminder)
library(dplyr)##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(geonames)## Warning: package 'geonames' was built under R version 4.0.3
library(countrycode)## Warning: package 'countrycode' was built under R version 4.0.3
library(ggplot2)
library(ggthemes)## Warning: package 'ggthemes' was built under R version 4.0.3
theme_set(theme_fivethirtyeight())The following code retrieves the relevant dataframes from a R library and an API, then tidies and joins them.
gapminder <- data.frame(gapminder)
key <- getOption("geonamesUsername")
countryInfo <- data.frame(GNcountryInfo())
countryJoin <- countrycode(countryInfo[, 13], origin = 'iso2c', destination = 'country.name')## Warning in countrycode(countryInfo[, 13], origin = "iso2c", destination = "country.name"): Some values were not matched unambiguously: XK
countryInfo <- mutate(countryInfo, country = countryJoin)
gapminder_density <- left_join(gapminder, countryInfo, by = "country") %>%
mutate(popDensity = pop / as.numeric(areaInSqKm))ggplot(gapminder_density, aes(x = popDensity, y = lifeExp)) +
geom_jitter(alpha = 0.1) +
geom_smooth() +
labs(x = "Population density (inhabitants per Sq Km)", y = "Average life expectancy", title = "Life Expectancy by Population Density")## Warning: Removed 192 rows containing non-finite values (stat_smooth).
## Warning: Removed 192 rows containing missing values (geom_point).
ggplot(gapminder_density, aes(x = popDensity, y = lifeExp)) +
geom_jitter(alpha = 0.1) +
facet_wrap(~ continent.x) +
geom_smooth()## Warning: Removed 192 rows containing non-finite values (stat_smooth).
## Warning: Removed 192 rows containing missing values (geom_point).
gapminder_density_mod <- lm(lifeExp ~ popDensity, data = gapminder_density)
summary(gapminder_density_mod)##
## Call:
## lm(formula = lifeExp ~ popDensity, data = gapminder_density)
##
## Residuals:
## Min 1Q Median 3Q Max
## -36.823 -11.102 1.172 11.459 23.021
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 58.717842 0.345941 169.734 < 2e-16 ***
## popDensity 0.006155 0.000872 7.059 2.55e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 12.88 on 1510 degrees of freedom
## (192 observations deleted due to missingness)
## Multiple R-squared: 0.03194, Adjusted R-squared: 0.0313
## F-statistic: 49.82 on 1 and 1510 DF, p-value: 2.554e-12
From the “Life Expectancy by Population Density” chart and the linear regression model coefficients, we can see there is a small but strong correlation between population density and life expectancy. However, most of the observations are clustered vertically at the beginning of the low density scale. When we probe deeper by faceting the observations by continent, we see that there is a sharp increase, a valley, then another sharp increase in Europe, Americas and Africa. Asia looks different, with no valleys and a much longer tail of increasing population density. Oceania shows no visible correlation.
devtools::session_info()## - Session info ---------------------------------------------------------------
## setting value
## version R version 4.0.2 (2020-06-22)
## os Windows 8.1 x64
## system x86_64, mingw32
## ui RTerm
## language (EN)
## collate English_United States.1252
## ctype English_United States.1252
## tz America/Chicago
## date 2020-12-03
##
## - Packages -------------------------------------------------------------------
## package * version date lib source
## assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.2)
## callr 3.5.1 2020-10-13 [1] CRAN (R 4.0.3)
## cli 2.0.2 2020-02-28 [1] CRAN (R 4.0.2)
## colorspace 1.4-1 2019-03-18 [1] CRAN (R 4.0.2)
## countrycode * 1.2.0 2020-05-22 [1] CRAN (R 4.0.3)
## crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.2)
## desc 1.2.0 2018-05-01 [1] CRAN (R 4.0.2)
## devtools 2.3.2 2020-09-18 [1] CRAN (R 4.0.3)
## digest 0.6.25 2020-02-23 [1] CRAN (R 4.0.2)
## dplyr * 1.0.2 2020-08-18 [1] CRAN (R 4.0.2)
## ellipsis 0.3.1 2020-05-15 [1] CRAN (R 4.0.2)
## evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.2)
## fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.2)
## farver 2.0.3 2020-01-16 [1] CRAN (R 4.0.2)
## fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2)
## gapminder * 0.3.0 2017-10-31 [1] CRAN (R 4.0.2)
## generics 0.1.0 2020-10-31 [1] CRAN (R 4.0.3)
## geonames * 0.999 2019-02-19 [1] CRAN (R 4.0.3)
## ggplot2 * 3.3.2 2020-06-19 [1] CRAN (R 4.0.2)
## ggthemes * 4.2.0 2019-05-13 [1] CRAN (R 4.0.3)
## glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.2)
## gtable 0.3.0 2019-03-25 [1] CRAN (R 4.0.2)
## htmltools 0.5.0 2020-06-16 [1] CRAN (R 4.0.2)
## knitr 1.30 2020-09-22 [1] CRAN (R 4.0.2)
## labeling 0.3 2014-08-23 [1] CRAN (R 4.0.0)
## lattice 0.20-41 2020-04-02 [2] CRAN (R 4.0.2)
## lifecycle 0.2.0 2020-03-06 [1] CRAN (R 4.0.2)
## lubridate 1.7.9 2020-06-08 [1] CRAN (R 4.0.2)
## magrittr 1.5 2014-11-22 [1] CRAN (R 4.0.2)
## Matrix 1.2-18 2019-11-27 [2] CRAN (R 4.0.2)
## memoise 1.1.0 2017-04-21 [1] CRAN (R 4.0.2)
## mgcv 1.8-31 2019-11-09 [2] CRAN (R 4.0.2)
## munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.2)
## nlme 3.1-148 2020-05-24 [2] CRAN (R 4.0.2)
## pillar 1.4.6 2020-07-10 [1] CRAN (R 4.0.2)
## pkgbuild 1.1.0 2020-07-13 [1] CRAN (R 4.0.2)
## pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.2)
## pkgload 1.1.0 2020-05-29 [1] CRAN (R 4.0.2)
## prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.0.2)
## processx 3.4.4 2020-09-03 [1] CRAN (R 4.0.2)
## ps 1.3.4 2020-08-11 [1] CRAN (R 4.0.2)
## purrr 0.3.4 2020-04-17 [1] CRAN (R 4.0.2)
## R6 2.4.1 2019-11-12 [1] CRAN (R 4.0.2)
## Rcpp 1.0.5 2020-07-06 [1] CRAN (R 4.0.2)
## remotes 2.2.0 2020-07-21 [1] CRAN (R 4.0.2)
## rjson 0.2.20 2018-06-08 [1] CRAN (R 4.0.3)
## rlang 0.4.7 2020-07-09 [1] CRAN (R 4.0.2)
## rmarkdown 2.5 2020-10-21 [1] CRAN (R 4.0.3)
## rprojroot 2.0.2 2020-11-15 [1] CRAN (R 4.0.3)
## scales 1.1.1 2020-05-11 [1] CRAN (R 4.0.2)
## sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.2)
## stringi 1.5.3 2020-09-09 [1] CRAN (R 4.0.2)
## stringr 1.4.0 2019-02-10 [1] CRAN (R 4.0.2)
## testthat 2.3.2 2020-03-02 [1] CRAN (R 4.0.2)
## tibble 3.0.3 2020-07-10 [1] CRAN (R 4.0.2)
## tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.2)
## usethis 1.6.3 2020-09-17 [1] CRAN (R 4.0.2)
## vctrs 0.3.4 2020-08-29 [1] CRAN (R 4.0.2)
## withr 2.3.0 2020-09-22 [1] CRAN (R 4.0.2)
## xfun 0.17 2020-09-09 [1] CRAN (R 4.0.2)
## yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.3)
##
## [1] C:/Users/Gustavo/OneDrive - The University of Chicago/Documents/R/win-library/4.0
## [2] C:/Program Files/R/R-4.0.2/library