Effective communication of exploratory results

based on IMS Ch 6: Applications: Explore

Outline

• keep it simple

• use color to draw attention

• tell a story

• order matters

• pick the right chart

• select meaningful colors

Steps in data analysis

Load the packages

library(tidyverse)
library(openintro)
library(scales) 
library(ggcharts) # install  for bar_chart and lollipop_chart
theme_set(theme_ggcharts()) #set theme of all plots 

Read the dataset

health_cos  <-  read_csv("https://bus320-quarto.netlify.app/data/health_cos.csv")

Glimpse the data

glimpse(health_cos)

Rows: 464
Columns: 11
$ ticker      <chr> "ZTS", "ZTS", "ZTS", "ZTS", "ZTS", "ZTS", "ZTS", "ZTS", "Z…
$ name        <chr> "Zoetis Inc", "Zoetis Inc", "Zoetis Inc", "Zoetis Inc", "Z…
$ revenue     <dbl> 4233000000, 4336000000, 4561000000, 4785000000, 4765000000…
$ gp          <dbl> 2581000000, 2773000000, 2892000000, 3068000000, 3027000000…
$ rnd         <dbl> 427000000, 409000000, 399000000, 396000000, 364000000, 376…
$ netincome   <dbl> 245000000, 436000000, 504000000, 583000000, 339000000, 821…
$ assets      <dbl> 5711000000, 6262000000, 6558000000, 6588000000, 7913000000…
$ liabilities <dbl> 1975000000, 2221000000, 5596000000, 5251000000, 6822000000…
$ marketcap   <dbl> NA, NA, 16345223371, 21572007994, 23860348635, 26434855920…
$ year        <dbl> 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2011, 2012…
$ industry    <chr> "Drug Manufacturers - Specialty & Generic", "Drug Manufact…

Keep it simple

• what do you want your audience to see?

• Use colors to group items or differentiate between items

Example

A pie chart (with added irrelevant features) as compared to a simple bar plot

bar_chart from ggcharts

website: bar_chart

health_cos  |> 
  filter(year == 2018) |>
  bar_chart(x = name, y = revenue, top_n = 10)+
  scale_y_continuous(labels = dollar_format(suffix = "B", scale = 1e-9))+
  labs(x = NULL, y = NULL, title = "Top 10 Health Companies by 2018 Revenue")

Your turn

• create a bar chart of the top 5 health companies by 2017 marketcap

• use the health_cos dataset

• format the y-axis to show billions of dollars

• eliminate the x-axis label, the y-axis label

• title the chart “Top 5 Drug Companies by 2017 Marketcap”

lollipop_chart from ggcharts

health_cos  |> 
  filter(year == 2018) |>
  lollipop_chart(x = name, y = revenue, top_n = 10)+
  scale_y_continuous(labels = dollar_format(suffix = "B", scale = 1e-9))+
  labs(x = NULL, y = NULL, title = "Top 10 Health Companies by 2018 Revenue")

Your turn

• create a lollipop_chart of the top 5 health companies by 2017 research and development expenditure (rnd)

• use the health_cos dataset

• format the y-axis to show billions of dollars

• eliminate the x-axis label, the y-axis label

• title the chart “Top 5 Drug Companies by 2017 Research and Development Expenditure””

Use color to draw attention

highlight_spec from ggcharts

health_cos  |> 
  filter(year == 2018) |>
  bar_chart(x = name, y = revenue, highlight = "Anthem Inc", top_n = 10)+
  labs(title = "Top 10 Health Companies by 2018 Revenue")+
  scale_y_continuous(labels = dollar_format(suffix = "B", scale = 1e-9), expand = c(0,0) )+
  labs(x = NULL, y = NULL)

Your turn

• create a lollipop_chart of the top 5 health companies by 2017 research and development expenditure (rnd)

• use the health_cos dataset

• format the y-axis to show billions of dollars

• eliminate the x-axis label, the y-axis label

• title the chart “Top 5 Drug Companies by 2017 Research and Development Expenditure””

• highlight the company with the highest research and development expenditure

Facets (subplots)

• Use bar_chart from the ggcharts package create a separate a bar chart of the `revenue`` for “Abbott Laboratories”, “Agilent Technologies Inc” and “Amgen Inc” for the years 2015-2018.
• Format the y-axis to show billions of dollars
• Eliminate the x-axis label, the y-axis label
• Title the chart: “Revenue for Abbott, Agilent and Amgen”
• Create a subplot for each year

Facet plot by year

health_cos |> 
  filter(year %in% c(2015, 2016, 2017, 2018)) |> 
  filter(name %in% c("Abbott Laboratories", "Agilent Technologies Inc", "Amgen Inc")) |> 
  bar_chart(x = name, y = revenue, facet = year) +
  scale_y_continuous(labels = dollar_format(suffix = "B", scale = 1e-9)) +
  labs(x = NULL, y = NULL, title = "Revenue for Abbott, Agilent and Amgen")

Your turn - facets

• Use bar_chart from the ggcharts package create a separate a bar chart of the netincome for “Cooper Companies Inc”, “Centene Corp” and “Cigna Corp” for the years 2013-2015.
• Format the y-axis to show billions of dollars
• Eliminate the x-axis label, the y-axis label
• Title the chart: “Net Income for Cooper, Centene and Cigna”
• Create a subplot for each year

Quiz

• 5 multiple choice questions (one answer for each question) using ggcharts and tidyverse packages and the health_cos dataset