Use Titles to Highlight Findings
This lesson is called Use Titles to Highlight Findings, part of the Going Deeper with R course. This lesson is called Use Titles to Highlight Findings, part of the Going Deeper with R course.
Transcript
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View code shown in video
# Load Packages -----------------------------------------------------------
library(tidyverse)
library(fs)
library(scales)
library(ggrepel)
library(ggtext)
# Create Directory --------------------------------------------------------
dir_create("data")
# Download Data -----------------------------------------------------------
# download.file("https://github.com/rfortherestofus/going-deeper-v2/raw/main/data/third_grade_math_proficiency.rds",
# mode = "wb",
# destfile = "data/third_grade_math_proficiency.rds")
# Import Data -------------------------------------------------------------
third_grade_math_proficiency <-
read_rds("data/third_grade_math_proficiency.rds") |>
select(academic_year, school, school_id, district, proficiency_level, number_of_students) |>
mutate(is_proficient = case_when(
proficiency_level >= 3 ~ TRUE,
.default = FALSE
)) |>
group_by(academic_year, school, district, school_id, is_proficient) |>
summarize(number_of_students = sum(number_of_students, na.rm = TRUE)) |>
ungroup() |>
group_by(academic_year, school, district, school_id) |>
mutate(percent_proficient = number_of_students / sum(number_of_students, na.rm = TRUE)) |>
ungroup() |>
filter(is_proficient == TRUE) |>
select(academic_year, school, district, percent_proficient) |>
rename(year = academic_year) |>
mutate(percent_proficient = case_when(
is.nan(percent_proficient) ~ NA,
.default = percent_proficient
))
# Plot --------------------------------------------------------------------
top_growth_school <-
third_grade_math_proficiency |>
filter(district == "Portland SD 1J") |>
group_by(school) |>
mutate(growth_from_previous_year = percent_proficient - lag(percent_proficient)) |>
ungroup() |>
drop_na(growth_from_previous_year) |>
slice_max(order_by = growth_from_previous_year,
n = 1) |>
pull(school)
third_grade_math_proficiency |>
filter(district == "Portland SD 1J") |>
mutate(highlight_school = case_when(
school == top_growth_school ~ "Y",
.default = "N"
)) |>
mutate(percent_proficient_formatted = case_when(
school == top_growth_school ~ percent(percent_proficient, accuracy = 1)
)) |>
mutate(percent_proficient_formatted = case_when(
highlight_school == "Y" & year == "2021-2022" ~ str_glue("{percent_proficient_formatted} of students
were proficient
in {year}"),
highlight_school == "Y" & year == "2018-2019" ~ percent_proficient_formatted
)) |>
mutate(school = fct_relevel(school, top_growth_school, after = Inf)) |>
ggplot(aes(x = year,
y = percent_proficient,
group = school,
color = highlight_school,
label = percent_proficient_formatted)) +
geom_line() +
geom_text_repel(hjust = 0,
lineheight = 0.9,
direction = "x") +
scale_color_manual(values = c(
"N" = "grey90",
"Y" = "orange"
)) +
scale_y_continuous(labels = percent_format()) +
labs(title = str_glue("<b style='color: orange;'>{top_growth_school}</b>
showed large growth in math proficiency over the
last two years")) +
theme_minimal() +
theme(axis.title = element_blank(),
legend.position = "none",
plot.title = element_markdown(),
plot.title.position = "plot",
panel.grid = element_blank())
Your Turn
Add a descriptive title to your plot
Use color strategically in your title using the
ggtext
packageAlign your title all the way to the edge of the plot
Learn More
To learn more about ggtext
, check out both the package documentation and this presentation by Cara Thompson.
To learn more about why you should align your plot title all the way to the edge, see this talk by Axios data journalist Will Chase.
Have any questions? Put them below and we will help you out!
Course Content
44 Lessons
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Anne Hill • November 13, 2024
The video for this particular section appears to be missing.
David Keyes Founder • November 13, 2024
Strange. I can see it on my end. Could you try a different browser and let me know if that works?