library(highcharter)
library(viridis)
library(tidyverse)
library(countrycode)
library(crosstalk)
library(plotly)
4 historical
4.1 Setup
4.2 Data preparation
<- read.csv("dataset/number-of-deaths-from-tetanus.csv")
data1 <- data1 %>%
data11 select(Year, Deaths) %>%
group_by(Year) %>%
summarise(Deaths = round((sum(Deaths))), 2)
##
<- data1 %>%
country_tibble1 select(Entity, Deaths) %>%
filter(Entity != 'African Region (WHO)',
!= 'East Asia & Pacific (WB)',
Entity != 'Eastern Mediterranean Region (WHO)',
Entity != 'Europe & Central Asia (WB)',
Entity != 'European Region (WHO)',
Entity != 'G20',
Entity != 'Latin America & Caribbean (WB)',
Entity != 'Middle East & North Africa (WB)',
Entity != 'North America (WB)',
Entity != 'OECD Countries',
Entity != 'Region of the Americas (WHO)',
Entity != 'South Asia (WB)',
Entity != 'South-East Asia Region (WHO)',
Entity != 'Sub-Saharan Africa (WB)',
Entity != 'Western Pacific Region (WHO)',
Entity != 'World Bank High Income',
Entity != 'World Bank Low Income',
Entity != 'World Bank Lower Middle Income',
Entity != 'World Bank Upper Middle Income',
Entity != 'World')%>%
Entity group_by(Entity) %>%
summarize(Deaths = round((sum(Deaths))), 2)
4.3 Worldwide deaths from tetanus infection
highchart() %>%
hc_add_series(data11, hcaes(x = Year, y = Deaths), type = "line") %>%
hc_tooltip(crosshairs = TRUE, borderWidth = 1.5, headerFormat = "", pointFormat = paste("Year: <b>{point.x}</b> <br> Deaths: <b>{point.y}</b>")) %>%
hc_title(text = "Worldwide cases of death from tetanus") %>%
hc_subtitle(text = "1990-2019") %>%
hc_colorAxis(minColor = "yellow", maxColor = "#592822") %>%
hc_xAxis(title = list(text = "Year")) %>%
hc_yAxis(title = list(text = "Deaths"),
allowDecimals = FALSE,
plotLines = list(list(
color = "black", width = 1, dashStyle = "Dash",
value = mean(data11$Deaths),
label = list(text = "Mean = 667745.9",
style = list(color = "black"))))) %>%
hc_legend(enabled = FALSE)