---
title: "Like A G-7 (Group of 7 Developed Countries)"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
source_code: embed
---
```{r setup, message = FALSE, echo = FALSE}
library(flexdashboard)
library(tidyverse)
library(p8105.datasets)
library(plotly)
library(readxl)
```
```{r, include = FALSE}
ghed_df <-
read_excel("./data/GHED_data.XLSX")
ghed_df <- ghed_df %>%
janitor::clean_names()
developed_nations <- ghed_df %>%
filter(country == "Canada" | country == "Japan" | country == "France" | country == "Germany" | country == "Italy" | country == "United Kingdom" | country == "United States of America")
undeveloped_nations <- ghed_df %>%
filter(country != "Canada" & country != "Japan" & country != "France" & country != "Germany" & country != "Italy" & country != "United Kingdom" & country != "United States of America", year == 2019)
```
Column {data-width=500}
-----------------------------------------------------------------------
### Private vs. Government Expenditure in Developed Countries in 2019
```{r,message=FALSE}
ghed_df %>%
filter(country == "Canada" | country == "Japan" | country == "France" | country == "Germany" | country == "Italy" | country == "United Kingdom" | country == "United States of America") %>%
filter(year == 2019) %>%
select(country, year, gghed_che, pvtd_che) %>%
mutate(sum_per = gghed_che + pvtd_che) %>%
pivot_longer(cols = contains("che"),
names_to = "exp_type",
values_to = "exp_per") %>%
mutate(exp_type = replace(exp_type, exp_type == "gghed_che", "Government Expenditure"),
exp_type = replace(exp_type, exp_type == "pvtd_che", "Private Expenditure")) %>%
plot_ly(x = ~country, y = ~exp_per, name = ~exp_type, color = ~exp_type, type = 'bar', colors = "viridis") %>%
layout(yaxis = list(title = 'Percent of Total Expenditure'), xaxis = list(title = "Country", categoryorder = "total descending"), barmode = 'stack', colors = "viridis")
```
Column {data-width=500}
-----------------------------------------------------------------------
### Out-of-Pocket Spending as % of Current Health Expenditure
```{r, message=FALSE}
developed_nations %>%
filter(year == 2019) %>%
select(country, oops_che) %>%
arrange(desc(oops_che)) %>%
plot_ly(x = ~country, y = ~oops_che, name = ~country, color = ~country, type = 'bar', colors = "viridis") %>%
add_trace(data = undeveloped_nations, x = ~country, y = ~oops_che, name = ~country, color = ~country, type = 'bar', colors = "viridis", visible = "legendonly") %>%
layout(yaxis = list(title = 'OOPS Spending'), xaxis = list(title = "Country"), barmode = 'stack', colors = "viridis") %>%
layout(xaxis = list(categoryorder = "total descending"))
```
### Social Health Insurance as % of Current Health Expenditure
```{r, message=FALSE}
developed_nations %>%
filter(year == 2019) %>%
select(country, shi_che) %>%
arrange(desc(shi_che)) %>%
plot_ly(x = ~country, y = ~shi_che, name = ~country, color = ~country, type = 'bar', colors = "viridis") %>%
add_trace(data = undeveloped_nations, x = ~country, y = ~shi_che, name = ~country, color = ~country, type = 'bar', colors = "viridis", visible = "legendonly") %>%
layout(yaxis = list(title = 'SHI Spending'), xaxis = list(title = "Country"), barmode = 'stack', colors = "viridis") %>%
layout(xaxis = list(categoryorder = "total descending"))
```
Social Health Insurance as % of Current Health Expenditure