week 7 HW chart 2 again

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
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##     intersect, setdiff, setequal, union

library(ggplot2)
library(readr)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
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##     last_plot

## The following object is masked from 'package:stats':
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##     filter

## The following object is masked from 'package:graphics':
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##     layout

library(RColorBrewer)
setwd("C:/Users/Don A/Documents/Don's files/MC")
nations <- read_csv("nations.csv")

## Parsed with column specification:
## cols(
##   iso2c = col_character(),
##   iso3c = col_character(),
##   country = col_character(),
##   year = col_double(),
##   gdp_percap = col_double(),
##   population = col_double(),
##   birth_rate = col_double(),
##   neonat_mortal_rate = col_double(),
##   region = col_character(),
##   income = col_character()
## )

nations_area <- nations %>%
  mutate(gdp_percap = gdp_percap * population / 1000000000000) %>%
  group_by(region, year) %>%
  summarise(sum = sum(gdp_percap, na.rm = TRUE))

p2 <- ggplot(nations_area, aes(x = year, y = sum, fill = region)) +
  scale_fill_brewer(palette = "Set2") +
  ylab("GDP ($ trillion)") +
  theme_minimal(base_size = 12) +
  geom_area(color = "white") +
  ggtitle("GDP by World Bank Region")
ggplotly(p2)