library("dslabs") # installs packages("dslabs") which we will use for the homework## Warning: package 'dslabs' was built under R version 4.0.4data(package="dslabs")
list.files(system.file("script", package = "dslabs"))## [1] "make-admissions.R"
## [2] "make-brca.R"
## [3] "make-brexit_polls.R"
## [4] "make-death_prob.R"
## [5] "make-divorce_margarine.R"
## [6] "make-gapminder-rdas.R"
## [7] "make-greenhouse_gases.R"
## [8] "make-historic_co2.R"
## [9] "make-mnist_27.R"
## [10] "make-movielens.R"
## [11] "make-murders-rda.R"
## [12] "make-na_example-rda.R"
## [13] "make-nyc_regents_scores.R"
## [14] "make-olive.R"
## [15] "make-outlier_example.R"
## [16] "make-polls_2008.R"
## [17] "make-polls_us_election_2016.R"
## [18] "make-reported_heights-rda.R"
## [19] "make-research_funding_rates.R"
## [20] "make-stars.R"
## [21] "make-temp_carbon.R"
## [22] "make-tissue-gene-expression.R"
## [23] "make-trump_tweets.R"
## [24] "make-weekly_us_contagious_diseases.R"
## [25] "save-gapminder-example-csv.R"#installas packages for Highcharter
library(readr)
library(ggplot2)
library(scales)##
## Attaching package: 'scales'## The following object is masked from 'package:readr':
##
## col_factorlibrary(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, unionlibrary(highcharter)## Warning: package 'highcharter' was built under R version 4.0.4## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo##
## Attaching package: 'highcharter'## The following object is masked from 'package:dslabs':
##
## starslibrary(RColorBrewer)library(dplyr) #installs dplyr package
nations <- read_csv("nations.csv") %>% # uploads data
mutate(gdp_tn = gdp_percap*population/1000000000000) #adds a new column gdp in trillion##
## -- 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()
## )big4 <- nations %>%
filter(iso3c == "CHN" | iso3c == "DEU" | iso3c == "JPN" | iso3c == "USA") %>% #o the nations dataset, the countries: China, Germany, Japan and United States are pulled
arrange(year) # arranges per yearcols <- brewer.pal(4, "Set2") #sets the color palette for graph
big4_chart <- highchart() %>%
hc_add_series(data = big4,
type = "line",
hcaes(x = year,
y = gdp_tn,
group = country)) %>% # this creates a line chart based on year and gdp
hc_colors(cols) %>% #this is puts the palette that we selected previously
hc_xAxis(title = list(text="Year")) %>% # adds title to x axis
hc_yAxis(title = list(text="GDP ($ trillion)")) %>% #adds title to y axis
hc_plotOptions(series = list(marker = list(symbol = "circle"))) %>% # this select the marker type i.e, circle
hc_legend(align = "right",
verticalAlign = "top") %>% # moves the legend to the top of the graph rather than preset bottom
hc_tooltip(shared = TRUE,
borderColor = "black",
pointFormat = "{point.country}: {point.gdp_tn:.2f}<br>") #edits tooltip for each year to include the four countries and round the gdp numbers to two decimal places
big4_charthighchart() %>%
hc_yAxis_multiples(
list(title = list(text = "gdp (trillions)")),
list(title = list(text = "birth_rate"),
opposite = TRUE) # This adds two y axis to the same x axis
) %>%
hc_add_series(data = big4,
type = "line",
hcaes(x = year,
y = gdp_tn,
group = country), name = c("China GDP", "Germany GDP", "Japan GDP", "United State GDP"),
yAxis=0) %>% # this creates the line chart for x= year and y = gdp per country
hc_add_series(data = big4,
type = "line",
hcaes(x = year,
y = birth_rate,
group = country), name = c("China Birth", "Germany Birth", "Japan Birth", "United States Birth"),
yAxis=1) %>% # this creates the line chart for x= year and y = birth rate per country
hc_colors(cols) %>% #adds the color per country
hc_xAxis(title = list(text="Year")) %>% # adds title to x axis
#hc_yAxis(title = list(text="GDP ($ trillion)")) %>% # adds title to y axis
hc_plotOptions(series = list(marker = list(symbol = "circle"))) %>% # this select the marker type i.e, circle
hc_legend(align = "right",
verticalAlign = "top") #moves the legend to the top of the graph rather than preset bottomhighchart() %>%
hc_yAxis_multiples(
list(title = list(text = "gdp (trillions)")),
list(title = list(text = "birth_rate"),
opposite = TRUE) # This adds two y axis to the same x axis.
) %>%
hc_add_series(data = big4,
type = "line", color = "purple",
hcaes(x = year,
y = gdp_tn,
group = country), name = c("China GDP", "Germany GDP", "Japan GDP", "United State GDP"),
yAxis=0) %>% # this creates the line chart for x= year and y = gdp per country
hc_add_series(data = big4,
type = "line", color = "pink",
hcaes(x = year,
y = birth_rate,
group = country), name = c("China Birth", "Germany Birth", "Japan Birth", "United States Birth"),
yAxis=1) %>% # this creates the line chart for x= year and y = birth rate per country
hc_xAxis(title = list(text="Year")) %>% # adds title to x axis
#hc_yAxis(title = list(text="GDP ($ trillion)")) %>% # adds title to y axis
hc_plotOptions(series = list(marker = list(symbol = "circle"))) %>% # this select the marker type i.e, circle
hc_legend(align = "right",
verticalAlign = "top") #moves the legend to the top of the graph rather than preset bottom```