R Notebook

Load the readr, ggplot2, and dplyr packages

library(tidyverse) library(readr) library(ggplot2) library(dplyr) # Read datasets/confirmed_cases_worldwide.csv into confirmed_cases_worldwide confirmed_cases_worldwide <- read_csv(“datasets/confirmed_cases_worldwide.csv”)

See the result

confirmed_cases_worldwide

library(testthat) library(IRkernel.testthat)

soln_confirmed_cases_worldwide <- read_csv(“datasets/confirmed_cases_worldwide.csv”)

run_tests({ test_that(“readr is loaded”, { expect_true( “readr” %in% .packages(), info = “Did you load the readr package?” ) }) test_that(“ggplot2 is loaded”, { expect_true( “ggplot2” %in% .packages(), info = “Did you load the ggplot2 package?” ) }) test_that(“dplyr is loaded”, { expect_true( “dplyr” %in% .packages(), info = “Did you load the dplyr package?” ) })

test_that("confirmed_cases_worldwide is a data.frame", {
    expect_s3_class(
        confirmed_cases_worldwide,
        "data.frame",
    )
})
test_that("confirmed_cases_worldwide has the correct column", {
    expect_identical(
        colnames(confirmed_cases_worldwide),
        colnames(soln_confirmed_cases_worldwide), 
        info = "The column names of the `confirmed_cases_worldwide` data frame do not correspond with the ones in the CSV file: `\"datasets/confirmed_cases_worldwide.csv\"`."
    ) 
})
test_that("has the correct data", {
    expect_equal(
        confirmed_cases_worldwide,
        soln_confirmed_cases_worldwide, 
        info = "The data of the `confirmed_cases_worldwide` data frame do not correspond with data in the CSV file: \"datasets/confirmed_cases_worldwide.csv\"."
    )
})

})

Draw a line plot of cumulative cases vs. date

Label the y-axis

ggplot(confirmed_cases_worldwide, aes(x = date, y = cum_cases)) + geom_line() + ylab(“Cumulative confirmed cases”)

run_tests({ plot <- last_plot() test_that(“the plot is created”, { expect_false( is.null(plot), info = “Could not find a plot created with ggplot().” ) }) test_that(“the plot uses the correct data”, { expect_equal( plot\(data, confirmed_cases_worldwide, info = "The dataset used in the last plot is not `confirmed_cases_worldwide`." ) }) test_that("the plot uses the correct x aesthetic", { expect_equal( quo_name(plot\)mapping\(x), "date", info = "The x aesthetic used in the last plot is not `date`." ) }) test_that("the plot uses the correct y aesthetic", { expect_equal( quo_name(plot\)mapping\(y), "cum_cases", info = "The y aesthetic used in the last plot is not `cum_cases`." ) }) test_that("the plot uses the correct geom", { expect_true( "GeomLine" %in% class(plot\)layers[[1]]\(geom), info = "The geom used in the last plot is not `geom_line()`." ) }) test_that("the plot uses the correct y label", { expect_equal( plot\)labels$y, “Cumulative confirmed cases”, info = “The y label used in the last plot is not \"Cumulative confirmed cases\".” ) }) })

Read in datasets/confirmed_cases_china_vs_world.csv

confirmed_cases_china_vs_world <- read_csv(“datasets/confirmed_cases_china_vs_world.csv”)

See the result

glimpse(confirmed_cases_china_vs_world)

Draw a line plot of cumulative cases vs. date, grouped and colored by is_china

Define aesthetics within the line geom

plt_cum_confirmed_cases_china_vs_world <- ggplot(confirmed_cases_china_vs_world) + geom_line(aes(x = date, y = cum_cases, group = is_china, color = is_china)) + ylab(“Cumulative confirmed cases”)

See the plot

plt_cum_confirmed_cases_china_vs_world

soln_confirmed_cases_china_vs_world <- read_csv(“datasets/confirmed_cases_china_vs_world.csv”)

run_tests({ test_that(“confirmed_cases_china_vs_world is a data.frame”, { expect_s3_class( confirmed_cases_china_vs_world, “data.frame” ) }) test_that(“confirmed_cases_china_vs_world has the correct column names”, { expect_identical( colnames(confirmed_cases_china_vs_world), colnames(soln_confirmed_cases_china_vs_world), info = “The column names of the confirmed_cases_china_vs_world data frame do not correspond with the ones in the CSV file: \"datasets/confirmed_cases_china_vs_world.csv\".” ) }) test_that(“confirmed_cases_china_vs_world has the correct data”, { expect_equal( confirmed_cases_china_vs_world, soln_confirmed_cases_china_vs_world, info = “The data of the confirmed_cases_china_vs_world data frame do not correspond with data in the CSV file: "datasets/confirmed_cases_china_vs_world.csv".” ) }) # NOTE: glimpse is not tested. Can this be done? test_that(“plt_cum_confirmed_cases_china_vs_world is not NULL”, { expect_false( is.null(plt_cum_confirmed_cases_china_vs_world), info = “plt_cum_confirmed_cases_china_vs_world is NULL.” ) }) test_that(“plt_cum_confirmed_cases_china_vs_world is a plot”, { expect_true( “ggplot” %in% class(plt_cum_confirmed_cases_china_vs_world), info = “plt_cum_confirmed_cases_china_vs_world is not a ggplot() object.” ) }) test_that(“plt_cum_confirmed_cases_china_vs_world uses the correct data”, { expect_equal( plt_cum_confirmed_cases_china_vs_world\(data, confirmed_cases_china_vs_world, info = "The dataset used in `plt_cum_confirmed_cases_china_vs_world` is not `confirmed_cases_china_vs_world`." ) }) layer <- plt_cum_confirmed_cases_china_vs_world\)layers[[1]] test_that(“plt_cum_confirmed_cases_china_vs_world uses uses the correct geom”, { expect_false( is.null(layer), info = “The geom used in plt_cum_confirmed_cases_china_vs_world is not geom_line().” ) }) test_that(“plt_cum_confirmed_cases_china_vs_world uses uses the correct geom”, { expect_true( “GeomLine” %in% class(layer\(geom), info = "The geom used in `plt_cum_confirmed_cases_china_vs_world` is not `geom_line()`." ) }) test_that("plt_cum_confirmed_cases_china_vs_world uses uses the correct x aesthetic", { expect_equal( quo_name(layer\)mapping\(x), "date", info = "The x aesthetic used in `plt_cum_confirmed_cases_china_vs_world` is not `date`." ) }) test_that("plt_cum_confirmed_cases_china_vs_world uses uses the correct y aesthetic", { expect_equal( quo_name(layer\)mapping\(y), "cum_cases", info = "The y aesthetic used in `plt_cum_confirmed_cases_china_vs_world` is not `cum_cases`." ) }) test_that("plt_cum_confirmed_cases_china_vs_world uses uses the correct colour aesthetic", { expect_equal( quo_name(layer\)mapping\(colour), "is_china", info = "The colour aesthetic used in `plt_cum_confirmed_cases_china_vs_world` is not `is_china`." ) }) test_that("plt_cum_confirmed_cases_china_vs_world uses uses the correct group aesthetic", { expect_equal( quo_name(layer\)mapping$group), “is_china”, info = “The group aesthetic used in plt_cum_confirmed_cases_china_vs_world is not is_china.” ) }) })

who_events <- tribble(

date, ~ event, “2020-01-30”, “Global healthdeclared”, “2020-03-11”, “Pandemic”, “2020-02-13”, “China reporting” ) %>% mutate(date = as.Date(date))

Using who_events, add vertical dashed lines with an xintercept at date

and text at date, labeled by event, and at 100000 on the y-axis

plt_cum_confirmed_cases_china_vs_world + geom_vline(data = who_events, aes(xintercept = date), linetype = ‘dashed’) + geom_text(data = who_events, aes(x = date,label = event), y = 1e5)

run_tests({ plot <- last_plot() test_that(“the plot got created”, { expect_false( is.null(plot), info = “Could not find a plot created with ggplot().” ) }) layer1 <- plot\(layers[[2]] layer2 <- plot\)layers[[3]] test_that(“the plot has both geoms”, { expect_false( is.null(layer1) || is.null(layer2), info = “Could not fin geom_vline() and geom_text() in your last plot.” ) }) test_that(“the plot has both geoms”, { expect_true( “GeomVline” %in% class(layer1\(geom) && "GeomText" %in% class(layer2\)geom) || “GeomText” %in% class(layer1\(geom) && "GeomVline" %in% class(layer2\)geom), info = “Could not fin geom_vline() and geom_text() in your last plot.” ) }) if (“GeomVline” %in% class(layer1\(geom)) { vline <- layer1 text <- layer2 } else { vline <- layer2 text <- layer1 } test_that("the plot uses the correct data", { expect_equal( vline\)data, who_events, info = “The dataset used in the geom_vline() is not who_events.” ) }) test_that(“the geom uses the correct xintercept aesthetic”, { expect_equal( quo_name(vline\(mapping\)xintercept), “date”, info = “The xintercept aesthetic used in the geom_vline() is not date.” ) }) test_that(“the geom uses the correct lintype parameter”, { expect_equal( vline\(aes_params\)linetype, “dashed”, info = “The linetype parameter used in the geom_vline() is not \"dashed\".” ) }) test_that(“the geom uses the correct data”, { expect_equal( text\(data, who_events, info = "The dataset used in the `geom_text()` is not `who_events`." ) }) test_that("the geom uses the correct x aesthetic", { expect_equal( quo_name(text\)mapping\(x), "date", info = "The x aesthetic used in the `geom_text()` is not `date`." ) }) test_that("the geom uses the correct label aesthetic", { expect_equal( quo_name(text\)mapping\(label), "event", info = "The label aesthetic used in the `geom_text()` is not `event`." ) }) test_that("the geom uses the correct y parameter", { expect_equal( text\)aes_params$y, 100000, info = “The y parameter used in the geom_text() is not 1e5.” ) }) })

Filter for China, from Feb 15

china_after_feb15 <- confirmed_cases_china_vs_world %>% filter(is_china==“China”,date >= “2020-02-15”)

Using china_after_feb15, draw a line plot cum_cases vs. date

Add a smooth trend line using linear regression, no error bars

ggplot(china_after_feb15, aes(x= date, y=cum_cases)) + geom_line()+ geom_smooth(method=“lm”, se = FALSE) + ylab(“Cumulative confirmed cases”)

run_tests({ test_that(“the data is filtered correctly”, { soln_china_after_feb15 <- confirmed_cases_china_vs_world %>% filter(is_china == “China”, date >= “2020-02-15”) expect_equivalent( soln_china_after_feb15, china_after_feb15, info = “china_after_feb15 has not been filtered correctly.” ) }) plot <- last_plot() test_that(“the plot is created”, { expect_false( is.null(plot), info = “Could not find a plot created with ggplot().” ) }) test_that(“the plot uses the correct data”, { expect_equal( plot\(data, china_after_feb15, info = "The dataset used in the last plot is not `soln_china_after_feb15`." ) }) test_that("the plot uses the correct x aesthetic", { expect_equal( quo_name(plot\)mapping\(x), "date", info = "The x aesthetic used in the last plot is not `date`." ) }) test_that("the plot uses the correct y aesthetic", { expect_equal( quo_name(plot\)mapping\(y), "cum_cases", info = "The y aesthetic used in the last plot is not `cum_cases`." ) }) layer1 <- plot\)layers[[1]] layer2 <- plot\(layers[[2]] test_that("the plot has the correct geoms", { expect_false( is.null(layer1) || is.null(layer2), info = "Could not fin `geom_line()` and `geom_smooth()` in your last plot." ) }) test_that("the plot has the correct geoms", { expect_true( "GeomLine" %in% class(layer1\)geom) && “GeomSmooth” %in% class(layer2\(geom) || "GeomSmooth" %in% class(layer1\)geom) && “GeomLine” %in% class(layer2\(geom), info = "Could not fin `geom_line()` and `geom_smooth()` in your last plot." ) }) if ("GeomLine" %in% class(layer1\)geom)) { line <- layer1 smooth <- layer2 } else { line <- layer2 smooth <- layer1 } test_that(“the geom has the correct method parameter”, { expect_equal( smooth\(stat_params\)method, “lm”, info = “The method parameter used in the geom_smooth() is not \"lm\".”

    )
})
test_that("the geom has the correct se parameter", {
    expect_equal(
        smooth$stat_params$se,
        FALSE,
        info = "The se parameter used in the `geom_smooth()` is not `\"FALSE\"`."
    )
})

})

Filter confirmed_cases_china_vs_world for not China

not_china <- confirmed_cases_china_vs_world %>% filter(is_china == “Not China”)

Using not_china, draw a line plot cum_cases vs. date

Add a smooth trend line using linear regression, no error bars

plt_not_china_trend_lin <- ggplot(not_china, aes(x= date, y=cum_cases)) + geom_line()+ geom_smooth(method=“lm”, se = FALSE) + ylab(“Cumulative confirmed cases”)

See the result

plt_not_china_trend_lin

run_tests({ test_that(“the data is filtered correctly”, { soln_not_china <- confirmed_cases_china_vs_world %>% filter(is_china == “Not China”) expect_equal( soln_not_china, not_china, info = “not_china has not been filtered correctly.” ) }) plot <- last_plot() test_that(“the plot is created”, { expect_false( is.null(plot), info = “Could not find a plot created with ggplot().” ) }) test_that(“the plot uses the correct data”, { expect_equal( plot\(data, not_china, info = "The dataset used in the last plot is not `not_china`." ) }) test_that("the plot uses the correct x aesthetic", { expect_equal( quo_name(plot\)mapping\(x), "date", info = "The x aesthetic used in the last plot is not `date`." ) }) test_that("the plot uses the correct y aesthetic", { expect_equal( quo_name(plot\)mapping\(y), "cum_cases", info = "The y aesthetic used in the last plot is not `cum_cases`." ) }) layer1 <- plot\)layers[[1]] layer2 <- plot\(layers[[2]] test_that("the plot uses the correct geoms", { expect_false( is.null(layer1) || is.null(layer2), info = "Could not fin `geom_line()` and `geom_smooth()` in your last plot." ) }) test_that("the plot uses the correct geoms", { expect_true( "GeomLine" %in% class(layer1\)geom) && “GeomSmooth” %in% class(layer2\(geom) || "GeomSmooth" %in% class(layer1\)geom) && “GeomLine” %in% class(layer2\(geom), info = "Could not fin `geom_line()` and `geom_smooth()` in your last plot." ) }) if ("GeomLine" %in% class(layer1\)geom)) { line <- layer1 smooth <- layer2 } else { line <- layer2 smooth <- layer1 } test_that(“the geom uses the correct method parameter”, { expect_equal( smooth\(stat_params\)method, “lm”, info = “The method parameter used in the geom_smooth() is not \"lm\".” ) }) test_that(“the geom uses the correct se parameter”, { expect_equal( smooth\(stat_params\)se, FALSE, info = “The se parameter used in the geom_smooth() is not \"FALSE\".” ) }) })

Modify the plot to use a logarithmic scale on the y-axis

plt_not_china_trend_lin + scale_y_log10()

run_tests({ plot <- last_plot() test_that(“the plot is created”, { expect_false( is.null(plot), info = “Could not find a plot created with ggplot().” ) }) scale <- plot\(scales\)get_scales(aes(“y”)) test_that(“the plot has a scale”, { expect_false( is.null(scale), info = “Could not find a scale in your last plot.” ) }) test_that(“the plot uses the correct scale”, { expect_equal( scale\(trans\)name, “log-10”, info = “Could not find a logarithmic y scale: scale_y_log10().” ) }) })

Run this to get the data for each country

confirmed_cases_by_country <- read_csv(“datasets/confirmed_cases_by_country.csv”) glimpse(confirmed_cases_by_country)

Group by country, summarize to calculate total cases, find the top 7

top_countries_by_total_cases <- confirmed_cases_by_country %>% group_by(country) %>% summarize(total_cases= max(cum_cases))%>% top_n(7)

See the result

top_countries_by_total_cases

run_tests({ test_that(“the data is manipulated correctly”, { soln_top_countries_by_total_cases <- confirmed_cases_by_country %>% group_by(country) %>% summarize(total_cases = max(cum_cases)) %>% top_n(7, total_cases) expect_equivalent( soln_top_countries_by_total_cases, top_countries_by_total_cases, info = “top_countries_by_total_cases has not been filtered correctly.” ) }) })

Run this to get the data for the top 7 countries

confirmed_cases_top7_outside_china <- read_csv(“datasets/confirmed_cases_top7_outside_china.csv”)

glimpse(confirmed_cases_top7_outside_china)

Using confirmed_cases_top7_outside_china, draw a line plot of

cum_cases vs. date, grouped and colored by country

ggplot(confirmed_cases_top7_outside_china, aes(x=date, y= cum_cases, group= country, color = country))+geom_line()+ylab(“Cumulative confirmed cases”)

soln_confirmed_cases_top7_outside_china <- read_csv(“datasets/confirmed_cases_top7_outside_china.csv”)

run_tests({ test_that(‘confirmed_cases_top7_outside_china is a data.frame’, { expect_s3_class( confirmed_cases_top7_outside_china, ‘data.frame’ ) }) test_that(‘confirmed_cases_top7_outside_china had the correct column names’, { expect_identical( colnames(confirmed_cases_top7_outside_china), colnames(soln_confirmed_cases_top7_outside_china), info = “The column names of the confirmed_cases_top7_outside_china data frame do not correspond with the ones in the CSV file: \"datasets/confirmed_cases_top7_outside_china.csv\".” ) }) test_that(‘confirmed_cases_top7_outside_china had the correct data’, { expect_equal( confirmed_cases_top7_outside_china, soln_confirmed_cases_top7_outside_china, info = “The data of the confirmed_cases_top7_outside_china data frame do not correspond with data in the CSV file: "datasets/confirmed_cases_top7_outside_china.csv".” ) }) # NOTE: glimpse is not tested. Can this be done? plot <- last_plot() test_that(‘the plot is created’, { expect_false( is.null(plot), info = “Could not find a plot created with ggplot().” ) }) test_that(‘the plot uses the correct data’, { expect_equal( plot\(data, confirmed_cases_top7_outside_china, info = "The dataset used in the last plot is not `not_china`." ) }) line <- plot\)layers[[1]] test_that(‘the plot uses the correct geom’, { expect_false( is.null(line), info = “Could not fin geom_line() in your last plot.” ) }) test_that(‘the plot uses the correct geom’, { expect_true( ‘GeomLine’ %in% class(line\(geom), info = "Could not fin `geom_line()` in your last plot." ) }) mapping <- plot\)mapping geom_mapping <- line\(mapping test_that('the plot uses the correct x aesthetic', { expect_true( !is.null(mapping\)x) && quo_name(mapping\(x) == "date" || !is.null(geom_mapping\)x) && quo_name(geom_mapping$x) == “date”, info = “The x aesthetic used in the last plot is not date.”

    )
})
test_that('the plot uses the correct y aesthetic', {
    expect_true(
        !is.null(mapping$y) && quo_name(mapping$y) == "cum_cases" ||
        !is.null(geom_mapping$y) && quo_name(geom_mapping$y) == "cum_cases",
        info = "The y aesthetic used in the last plot is not `cum_cases`."
    )
})
test_that('the plot uses the correct color aesthetic', {
    expect_true(
        !is.null(mapping$colour) && quo_name(mapping$colour) == "country" ||
        !is.null(geom_mapping$colour) && quo_name(geom_mapping$colour) == "country",
        info = "The colour aesthetic used in the last plot is not `country`."
    )
})
test_that('the plot uses the correct group aesthetic', {
    expect_true(
        !is.null(mapping$group) && quo_name(mapping$group) == "country" ||
        !is.null(geom_mapping$group) && quo_name(geom_mapping$group) == "country",
        info = "The group aesthetic used in the last plot is not `country`."
    )
})
test_that('the plot uses the correct y label', {
    expect_equal(
        plot$labels$y,
        "Cumulative confirmed cases",
        info = "The y label used in the last plot is not `\"Cumulative confirmed cases\"`."
    )
})

})