Interactive reporting + visualization with Shiny I

Lecture 25

Dr. Greg Chism

University of Arizona
INFO 526 - Fall 2023

Warm up

Announcements

  • Peer evals are next week (survey to be announced soon)
  • HW 06 is due Dec 6th, 11:59pm

Setup

# load packages
library(countdown)
library(tidyverse)
library(gganimate)

# set theme for ggplot2
ggplot2::theme_set(ggplot2::theme_minimal(base_size = 14))

# set width of code output
options(width = 65)

# set figure parameters for knitr
knitr::opts_chunk$set(
  fig.width = 7, # 7" width
  fig.asp = 0.618, # the golden ratio
  fig.retina = 3, # dpi multiplier for displaying HTML output on retina
  fig.align = "center", # center align figures
  dpi = 300 # higher dpi, sharper image
)

From last time

The racing bar chart

Making of the racing bar chart

freedom <- read_csv(here::here("slides/25", "data/freedom.csv"), na = "-")

countries_to_plot <- freedom %>%
  rowwise() %>%
  mutate(sd = sd(c_across(contains("cl_")), na.rm = TRUE)) %>%
  ungroup() %>%
  arrange(desc(sd)) %>%
  relocate(country, sd) %>%
  slice_head(n = 15) %>%
  pull(country)

freedom_to_plot <- freedom %>%
  filter(country %in% countries_to_plot) %>%
  drop_na()

freedom_ranked <- freedom_to_plot %>%
  select(country, contains("cl_")) %>%
  pivot_longer(
    cols = -country,
    names_to = "year",
    values_to = "civil_liberty",
    names_prefix = "cl_",
    names_transform = list(year = as.numeric)
  ) %>%
  group_by(year) %>%
  mutate(rank_in_year = rank(civil_liberty, ties.method = "first")) %>%
  ungroup() %>%
  mutate(is_turkey = if_else(country == "Turkey", TRUE, FALSE))

freedom_faceted_plot <- freedom_ranked %>%
  ggplot(aes(x = civil_liberty, y = factor(rank_in_year))) +
  geom_col(aes(fill = is_turkey), show.legend = FALSE) +
  scale_fill_manual(values = c("gray", "red")) +
  facet_wrap(~year) +
  scale_x_continuous(
    limits = c(-5, 7),
    breaks = 1:7
  ) +
  geom_text(
    hjust = "right",
    aes(label = country),
    x = -1
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    axis.text.y = element_blank()
  ) +
  labs(x = NULL, y = NULL)

freedom_bar_race <- freedom_faceted_plot +
  facet_null() +
  geom_text(
    x = 5, y = 1,
    hjust = "left",
    aes(label = as.character(year)),
    size = 10
  ) +
  aes(group = country) +
  transition_time(as.integer(year)) +
  labs(
    title = "Civil liberties rating, {frame_time}",
    subtitle = "1: Highest degree of freedom - 7: Lowest degree of freedom"
  )

animate(
  freedom_bar_race,
  fps      = 2,
  nframes  = 30,
  width    = 900,
  height   = 560,
  renderer = gifski_renderer()
  )
anim_save("gifs/freedom_bar_race.gif")

Shiny: High level view

Shiny

Every Shiny app has a webpage that the user visits,
and behind this webpage there is a computer that serves this webpage by running R.

Shiny

When running your app locally, the computer serving your app is your computer.

Shiny

When your app is deployed, the computer serving your app is a web server.

Shiny

Demo

  • Clone the shiny-ex repo.
  • Launch the app by opening the app.R file and clicking on Run App.
  • Close the app by clicking the stop icon
  • Select view mode in the drop down menu next to Run App

Anatomy of a Shiny app

What’s in an app?

library(shiny)
ui <- fluidPage()


server <- function(
    input, 
    output, 
    session) {
  ...
}


shinyApp(
  ui = ui, 
  server = server
  )

  • User interface controls the layout and appearance of app

  • Server function contains instructions needed to build app

Data: Ask a manager

Source: Ask a Manager Survey via TidyTuesday

This data does not reflect the general population; it reflects Ask a Manager readers who self-selected to respond, which is a very different group (as you can see just from the demographic breakdown below, which is very white and very female).

Some findings here.

Data: manager

manager <- read_csv(here::here("slides/25", "data/survey.csv"))
manager
# A tibble: 26,232 × 18
   timestamp          how_old_are_you industry          job_title
   <chr>              <chr>           <chr>             <chr>    
 1 4/27/2021 11:02:10 25-34           Education (Highe… Research…
 2 4/27/2021 11:02:22 25-34           Computing or Tech Change &…
 3 4/27/2021 11:02:38 25-34           Accounting, Bank… Marketin…
 4 4/27/2021 11:02:41 25-34           Nonprofits        Program …
 5 4/27/2021 11:02:42 25-34           Accounting, Bank… Accounti…
 6 4/27/2021 11:02:46 25-34           Education (Highe… Scholarl…
 7 4/27/2021 11:02:51 25-34           Publishing        Publishi…
 8 4/27/2021 11:03:00 25-34           Education (Prima… Librarian
 9 4/27/2021 11:03:01 45-54           Computing or Tech Systems …
10 4/27/2021 11:03:02 35-44           Accounting, Bank… Senior A…
# ℹ 26,222 more rows
# ℹ 14 more variables: additional_context_on_job_title <chr>,
#   annual_salary <dbl>, other_monetary_comp <dbl>,
#   currency <chr>, currency_other <chr>,
#   additional_context_on_income <chr>, country <chr>,
#   state <chr>, city <chr>,
#   overall_years_of_professional_experience <chr>, …

Ultimate goal

https://minecr.shinyapps.io/manager-survey

Interactive reporting with Shiny

Livecoding

Code along in manager-survey/app.R. We will do part 1 today, parts 2-3 Monday.


Highlights:

  • Data pre-processing
  • Basic reactivity

🔗 datavizaz.org