United Nations Populations
Jiang Li
4/20/2020
Dataset Overview
This dataset was downloaded from Facebook website, I took a look and I think that it would be fun for me to recall the ggplot2 visualization skills and walk myself through the entire EDA procedure.
suppressMessages(library(tidyverse))## Warning: package 'tidyverse' was built under R version 3.5.2## Warning: package 'stringr' was built under R version 3.5.2## Warning: package 'forcats' was built under R version 3.5.2suppressMessages(library(cowplot))## Warning: package 'cowplot' was built under R version 3.5.2df <- read_csv('~/Downloads/UnitedNationsPopulationdataset.csv')
glimpse(df)## Rows: 374
## Columns: 5
## $ `Country Name` <chr> "Aruba", "Afghanistan", "Angola", "Albania", "United…
## $ `Country Code` <chr> "ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "AT…
## $ Region <chr> "The Americas", "Asia", "Africa", "Europe", "Middle …
## $ Year <dbl> 1980, 1980, 1980, 1980, 1980, 1980, 1980, 1980, 1980…
## $ `Fertility Rate` <dbl> 4.820, 7.450, 7.379, 6.186, 6.928, 3.109, 4.550, 4.4…Clearly, we got five features in the dataset and three are strings and two are numeric, so the following steps of analysis is simple.
Data pre-processing
df <- df %>% rename(Country.Code=`Country Code`, Country.Name=`Country Name`, Fertility.Rate=`Fertility Rate`)
df <- df %>% mutate(Year=as.factor(Year))
df.long <- df %>% spread(Year, Fertility.Rate)
df.long <- df.long %>% rename(Y1980=`1980`,Y2018=`2018`)
glimpse(df)## Rows: 374
## Columns: 5
## $ Country.Name <chr> "Aruba", "Afghanistan", "Angola", "Albania", "United A…
## $ Country.Code <chr> "ABW", "AFG", "AGO", "ALB", "ARE", "ARG", "ARM", "ATG"…
## $ Region <chr> "The Americas", "Asia", "Africa", "Europe", "Middle Ea…
## $ Year <fct> 1980, 1980, 1980, 1980, 1980, 1980, 1980, 1980, 1980, …
## $ Fertility.Rate <dbl> 4.820, 7.450, 7.379, 6.186, 6.928, 3.109, 4.550, 4.425…glimpse(df.long)## Rows: 187
## Columns: 5
## $ Country.Name <chr> "Afghanistan", "Albania", "Algeria", "Angola", "Antigua …
## $ Country.Code <chr> "AFG", "ALB", "DZA", "AGO", "ATG", "ARG", "ARM", "ABW", …
## $ Region <chr> "Asia", "Europe", "Africa", "Africa", "The Americas", "T…
## $ Y1980 <dbl> 7.450, 6.186, 7.524, 7.379, 4.425, 3.109, 4.550, 4.820, …
## $ Y2018 <dbl> 5.050, 1.771, 2.893, 6.165, 2.088, 2.335, 1.553, 1.669, …EDA
Top 10 countries ranked by Fertility Rate
df %>% group_by(Year) %>% arrange(desc(Fertility.Rate)) %>% top_n(10) %>% ungroup() %>% ggplot(aes(x=reorder(Country.Name, Fertility.Rate),y=Fertility.Rate, fill=Country.Name))+geom_col()+facet_grid(~Year)+
labs(x='',fill=NA)+theme_classic()+theme(
legend.position = 'none',
axis.text.x = element_text(angle = 90,hjust = 1)
)
Average Fertility Rate in Regions
p1<-df %>% ggplot(aes(x=Region, y=Fertility.Rate, fill=Year))+geom_boxplot()+labs(x='')+
theme_classic()+theme(
axis.text.x = element_text(angle = 90,hjust = 1)
)
p2<-df %>% group_by(Region,Year) %>% summarise(Fertility.Rate=mean(Fertility.Rate)) %>%
ggplot(aes(x=Region,y=Year,fill=Fertility.Rate))+geom_tile()+
scale_fill_continuous(low="blue",high="red")+theme_classic()+theme(
axis.text.x = element_text(angle = 90,hjust = 1)
)## `summarise()` regrouping output by 'Region' (override with `.groups` argument)plot_grid(p1,p2)
Fertility Rate Change in Countries
p1<-df.long %>% mutate(status=case_when(Y2018>=Y1980 ~ 'Increase',Y2018<Y1980 ~ 'Decrease'),change=Y2018-Y1980) %>% group_by(change) %>% top_n(10) %>% ggplot(aes(x=reorder(Country.Name,-change),y=change,fill=status))+geom_col()+
labs(x='')+theme_classic()+theme(
axis.text.x = element_blank()
)## Selecting by changep2<-df.long %>% ggplot(aes(x=Y2018,y=Y1980,color=Region))+geom_point()+theme_classic()
plot_grid(p1,p2,nrow = 2)
Countries with Increased & Decreased Rate
library(ggalluvial)
df.long %>% mutate(status=case_when(Y2018>=Y1980 ~ 'Increase',Y2018<Y1980 ~ 'Decrease')) %>% group_by(Region,status) %>% count() %>% ggplot(aes(y=n,axis1=Region,axis2=status))+geom_flow(aes(fill=status),width = .4)+geom_stratum(width = .4)+geom_text(stat = "stratum", infer.label = TRUE)+theme_classic()
Session Info
devtools::session_info()## ─ Session info ───────────────────────────────────────────────────────────────
## setting value
## version R version 3.5.0 (2018-04-23)
## os macOS High Sierra 10.13.6
## system x86_64, darwin15.6.0
## ui X11
## language (EN)
## collate en_US.UTF-8
## ctype en_US.UTF-8
## tz Asia/Shanghai
## date 2020-07-06
##
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