Bring it All Together (Advanced Data Visualization)
This lesson is called Bring it All Together (Advanced Data Visualization), part of the Going Deeper with R course. This lesson is called Bring it All Together (Advanced Data Visualization), part of the Going Deeper with R course.
Transcript
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View code shown in video
---
title: "R Survey"
author: "David Keyes"
format: html
execute:
echo: false
warning: false
message: false
output: true
editor_options:
chunk_output_type: console
---
```{r}
# Load packages
library(tidyverse)
library(janitor)
library(scales)
library(ggtext)
```
```{r}
demographics <- read_rds("data/demographics.rds")
other_coding_languages <- read_rds("data/other_coding_languages.rds")
```
Here is a data viz of the most common coding languages people say they know.
```{r}
#| fig-height: 5
update_geom_defaults(geom = "text",
aes(family = "Inter"))
other_coding_languages |>
count(qcoding_languages) |>
slice_max(order_by = n,
n = 10) |>
mutate(qcoding_languages = fct_reorder(qcoding_languages, n)) |>
mutate(n_formatted = comma(n)) |>
mutate(is_r = case_when(
qcoding_languages == "R" ~ "Y",
.default = "N"
)) |>
ggplot(aes(x = n,
y = qcoding_languages,
fill = is_r,
color = is_r)) +
geom_col(width = 0.5,
color = "transparent") +
geom_text(aes(label = n_formatted),
hjust = 1.25,
color = "white") +
geom_text(aes(x = 0,
label = qcoding_languages),
hjust = 0,
vjust = -1.5) +
labs(title = "<b style='color: #6cabdd;'>R</b> is by far the most the popular language among respondents") +
theme_void(base_family = "Inter") +
theme(legend.position = "none",
plot.title = element_markdown(margin = margin(b = 10,
unit = "pt"))) +
scale_x_continuous(expand = expansion(add = 0)) +
scale_fill_manual(values = c(
"Y" = "#6cabdd",
"N" = "grey80"
)) +
scale_color_manual(values = c(
"Y" = "#6cabdd",
"N" = "grey70"
))
```
Here is the data viz of the most common coding languages people say they know **broken out by country**.
```{r}
other_coding_languages |>
left_join(demographics,
join_by(id)) |>
count(qcoding_languages, qdegree) |>
slice_max(order_by = n,
n = 10) |>
mutate(qcoding_languages = fct_reorder(qcoding_languages, n)) |>
ggplot(aes(x = n,
y = qcoding_languages)) +
geom_col() +
theme_minimal() +
facet_wrap(vars(qdegree))
```
Learn More
Another nice example of creating a nice line plot comes from Albert Rapp's video titled Stop making messy line charts and create meaningful plots instead.
A more general resource comes from the European Union's Data Visualization Guide. It's got section on best practices (including the concepts shown in this course) and some specifics on how to implement these practices with ggplot code.
Have any questions? Put them below and we will help you out!
Course Content
44 Lessons
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