Making Your Reports Shine: PDF Edition
This lesson is called Making Your Reports Shine: PDF Edition, part of the Going Deeper with R course. This lesson is called Making Your Reports Shine: PDF Edition, part of the Going Deeper with R course.
Transcript
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View code shown in video
---
title: "Portland Public Schools Math Proficiency Report"
format:
typst:
papersize: us-letter
mainfont: Inter
fontsize: 12pt
margin:
top: 1in
execute:
echo: false
warning: false
message: false
editor_options:
chunk_output_type: console
---
```{r}
library(tidyverse)
library(fs)
library(scales)
library(ggrepel)
library(ggtext)
library(ragg)
library(here)
library(flextable)
```
```{r}
third_grade_math_proficiency <-
read_rds(here("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
)) |>
mutate(percent_proficient_formatted = percent(percent_proficient,
accuracy = 1))
```
```{r}
theme_dk <- function() {
theme_minimal(base_family = "IBM Plex Mono") +
theme(axis.title = element_blank(),
axis.text = element_text(color = "grey60",
size = 10),
plot.title = element_markdown(),
plot.title.position = "plot",
panel.grid = element_blank(),
legend.position = "none")
}
```
## Chart
The chart below shows math proficiency for all PPS schools.
```{r}
#| fig-height: 5
#| fig-alt: A line chart showing math proficiency rates among all PPS schools in 2018-2019 and 2021-2022
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(
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,
.default = NA
)) |>
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,
family = "IBM Plex Mono",
direction = "x") +
scale_color_manual(values = c(
"N" = "grey90",
"Y" = "orange"
)) +
scale_y_continuous(labels = percent_format()) +
scale_x_discrete(expand = expansion(mult = c(0.05, 0.5))) +
annotate(geom = "text",
x = 2.02,
y = 0.6,
hjust = 0,
lineheight = 0.9,
color = "grey70",
family = "IBM Plex Mono",
label = str_glue("Each grey line
represents one school")) +
labs(title = str_glue("<b style='color: orange;'>{top_growth_school}</b> showed large growth<br>in math proficiency over the last two years")) +
theme_dk()
```
{{< pagebreak >}}
# Table
```{r}
#| tbl-cap: Math proficiency among third graders in five Portland schools
flextable_data <-
read_rds(here("data/third_grade_math_proficiency_dichotomous.rds")) |>
filter(district == "Portland SD 1J") |>
filter(school %in% c("Abernethy Elementary School",
"Ainsworth Elementary School",
"Alameda Elementary School",
"Arleta Elementary School",
"Atkinson Elementary School")) |>
select(year, school, percent_proficient_formatted) |>
arrange(school) |>
pivot_wider(id_cols = school,
names_from = year,
values_from = percent_proficient_formatted)
flextable_data |>
flextable() |>
set_header_labels(school = "School") |>
align(j = 2, align = "center") |>
autofit() |>
set_caption("Math proficiency among third graders in five Portland schools")
```
Your Turn
Create a PDF document using the typst
format. Refer to the typst
documentation on the Quarto website to see all of the things you can do.
To do this you'll need to first download and install a pre-release version of Quarto (version 1.4 or higher will work).
Learn More
There isn't a ton out there about making Typst templates, but do check out the talk I gave at posit::conf 2024 about Typst. You can also see the GitHub repo with my materials.
Have any questions? Put them below and we will help you out!
Course Content
44 Lessons
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Jan Bezuidenhout • March 19, 2025
Can you give a simple example of how to use templates with your typst format?
As an example, how do i add an header and footer to my document. I see some really good looking templates on the web (https://github.com/hzkonor/bubble-template/blob/main/template.typ), but cant get it to work in my qaurto document.
David Keyes Founder • March 20, 2025
There isn't a ton out there, check out the talk I gave last summer about Typst. You can also see the GitHub repo with my materials.