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Going Deeper with R

Pipe Data into ggplot

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View code shown in video 
# Load Packages -----------------------------------------------------------

library(tidyverse)
library(fs)

# 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() |> 
  mutate(percent_proficient = case_when(
    is.nan(percent_proficient) ~ NA,
    .default = percent_proficient
  )) |> 
  filter(is_proficient == TRUE) |> 
  select(academic_year, school, district, percent_proficient) |> 
  rename(year = academic_year) 


# Plot --------------------------------------------------------------------

third_grade_math_proficiency |> 
  filter(year == "2021-2022") |> 
  filter(district == "Portland SD 1J") |> 
  ggplot(aes(x = percent_proficient, 
             y = school)) +
  geom_col()

Your Turn

  1. Create a new R script file.

  2. Download the enrollment data by race/ethnicity and create a data frame called enrollment_by_race_ethnicity using the starter code below.

  3. Pipe your data into a bar chart that shows the breakdown of race/ethnicity among students in Beaverton SD 48J in 2022-2023.

# Load Packages -----------------------------------------------------------

library(tidyverse)
library(fs)

# Create Directory --------------------------------------------------------

dir_create("data")

# Download Data -----------------------------------------------------------

download.file("https://github.com/rfortherestofus/going-deeper-v2/raw/main/data/enrollment_by_race_ethnicity.rds",
              mode = "wb",
              destfile = "data/enrollment_by_race_ethnicity.rds")

# Import Data -------------------------------------------------------------

enrollment_by_race_ethnicity <-
  read_rds("data/enrollment_by_race_ethnicity.rds") |> 
  select(-district_institution_id)  |> 
  select(year, district, everything()) |> 
  mutate(year = case_when(
    year == "School 2021-22" ~ "2021-2022",
    year == "School 2022-23" ~ "2022-2023",
  ))

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Course Content

44 Lessons