Tables

This lesson is called Tables, part of the R in 3 Months (Spring 2026) course. This lesson is called Tables, part of the R in 3 Months (Spring 2026) course.

Transcript

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---
title: "Portland Public Schools Math Proficiency Report"
format: html
execute: 
  echo: false
  warning: false
  message: false
---

```{r}
library(tidyverse)
library(here)
library(flextable)
library(gt)
library(scales)
```

```{r}
third_grade_math_proficiency_wide <-
  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) |>
  arrange(school) |>
  pivot_wider(
    id_cols = school,
    names_from = year,
    values_from = percent_proficient
  )
```

![Portland Public Schools](portland-public-schools-logo.svg){width=300px fig-align="center" fig-alt="Portland Public Schools logo"}

# Introduction

This is a report on math proficiency results in [Portland Public Schools (PPS)](https://www.pps.net/). The PPS mission statement is as follows:

> We provide rigorous, high-quality academic learning experiences that are inclusive and joyful. We disrupt racial inequities to create vibrant environments for every student to demonstrate excellence.^[https://www.pps.net/about/portland-public-schools-information/overview]

# Don’t Use the Default Output

```{r}
third_grade_math_proficiency_wide
```

# Flextable

```{r}
#| tbl-cap: Math proficiency among third graders in five Portland schools

third_grade_math_proficiency_wide |>
  mutate(`2018-2019` = percent(`2018-2019`)) |>
  mutate(`2021-2022` = percent(`2021-2022`)) |>
  flextable() |>
  set_header_labels(school = "School") |>
  # align(j = 2, align = "center") |>
  # width(j = 2, 4, unit = "cm") |>
  # width(j = 3, 2, unit = "cm")
  autofit()
```

# gt

```{r}
#| tbl-cap: Math proficiency among third graders in five Portland schools

third_grade_math_proficiency_wide |>
  gt() |>
  cols_label(school = "School") |>
  cols_width(
    school ~ px(100)
  ) |>
  # cols_align(
  #   columns = `2018-2019`,
  #   align = "center"
  # ) |>
  fmt_percent(
    columns = 2:3,
    decimals = 1
  )
```

# gt interactive

```{r}
third_grade_math_proficiency_wide_full <-
  read_rds(here("data/third_grade_math_proficiency_dichotomous.rds")) |>
  filter(district == "Portland SD 1J") |>
  select(year, school, percent_proficient) |>
  arrange(school) |>
  pivot_wider(
    id_cols = school,
    names_from = year,
    values_from = percent_proficient
  )
```

```{r}
third_grade_math_proficiency_wide_full |>
  gt() |>
  cols_label(school = "School") |>
  fmt_percent(
    columns = 2:3,
    decimals = 0
  ) |>
  opt_interactive(
    use_search = TRUE,
    use_highlight = TRUE
  )
```

Your Turn

Copy the starter code below into RStudio and use it to make a table using flextable or gt.
Work on adjusting your column names, column width, number formatting, and anything else you might want to try out.

---
title: "Oregon Department of Education Diversity Report"
format: html
---

```{r}
library(tidyverse)
```

![](ode-logo.jpg)

This is a report for the [Oregon Department of Education](https://www.oregon.gov/ode/pages/default.aspx) on diversity in Oregon school districts.

&gt; The Oregon Department of Education fosters equity and excellence for every learner through collaboration with educators, partners, and communities.^[https://www.oregon.gov/ode/about-us/Pages/default.aspx]



```{r}
# The code below will bring in the enrollment by race/ethnicity data
# It will then filter to only include one school district (Baker SD 5J)
# It then use select() to drop a few columns that we don't need

baker_enrollment_by_race_ethnicity &lt;-
  read_rds("https://github.com/rfortherestofus/going-deeper-v2/raw/main/data/enrollment_by_race_ethnicity.rds") |&gt; 
  select(-district_institution_id)  |&gt; 
  select(year, district, everything()) |&gt; 
  mutate(year = case_when(
    year == "School 2021-22" ~ "2021-2022",
    year == "School 2022-23" ~ "2022-2023",
  )) |&gt; 
  filter(district == "Baker SD 5J") |&gt; 
  select(-c(district, number_of_students)) 
```

```{r}
# Use pivot_wider() to make the race/ethnicity groups into the columns (keep year in rows)
# Then create a table with the flextable or gt package
# Work on adjusting your column names, column width, number formatting, 
# and anything else you might want to try out.

# YOUR CODE HERE
```

Learn More

If you want to learn more about pivot_wider(), see Chapter 5 of R for Data Science.

If you really want to go deep on making good tables, check out the course Making Beautiful Tables with R or read Chapter 5 of my book R Without Statistics.

To learn more about the flextable package, visit its documentation page. There is also a book that David Gohel, the package author, has created to show how flextable works. And finally, there is a flextable gallery, where you can see examples of nice tables made with the package (and the code used to make them).

Tables

Transcript

Your Turn

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