ggplot Wizardry Hands-On

Reproduction of Cédric Scherer A Step-by-Step tutorial as supplement to my talk “ggplot Wizardry: My Favorite Tricks and Secrets for Beautiful Plot in R”.

show

## packages
library(tidyverse)   ## data science package collection (incl. the ggplot2 package)
library(systemfonts) ## use custom fonts (need to be installed on your OS)  
library(scico)       ## scico color palettes(http://www.fabiocrameri.ch/colourmaps.php) in R 
library(ggtext)      ## add improved text rendering to ggplot2
library(ggforce)     ## add missing functionality to ggplot2
library(ggdist)      ## add uncertainity visualizations to ggplot2
library(magick)      ## load images into R
library(patchwork)   ## combine outputs from ggplot2
library(ggplot2)

Data

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penguins <- 
  readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-28/penguins.csv') %>% 
  ## correct species name
  mutate(species = if_else(species == "Adelie", "Adélie", species)) %>% 
  ## remove missing observations
  filter(!is.na(bill_length_mm), !is.na(bill_depth_mm))

## inspect data
penguins

# A tibble: 342 × 8
   species island    bill_length…¹ bill_…² flipp…³ body_…⁴ sex    year
   <chr>   <chr>             <dbl>   <dbl>   <dbl>   <dbl> <chr> <dbl>
 1 Adélie  Torgersen          39.1    18.7     181    3750 male   2007
 2 Adélie  Torgersen          39.5    17.4     186    3800 fema…  2007
 3 Adélie  Torgersen          40.3    18       195    3250 fema…  2007
 4 Adélie  Torgersen          36.7    19.3     193    3450 fema…  2007
 5 Adélie  Torgersen          39.3    20.6     190    3650 male   2007
 6 Adélie  Torgersen          38.9    17.8     181    3625 fema…  2007
 7 Adélie  Torgersen          39.2    19.6     195    4675 male   2007
 8 Adélie  Torgersen          34.1    18.1     193    3475 <NA>   2007
 9 Adélie  Torgersen          42      20.2     190    4250 <NA>   2007
10 Adélie  Torgersen          37.8    17.1     186    3300 <NA>   2007
# … with 332 more rows, and abbreviated variable names
#   ¹​bill_length_mm, ²​bill_depth_mm, ³​flipper_length_mm, ⁴​body_mass_g
# ℹ Use `print(n = ...)` to see more rows

show

## view full table
View(penguins)

## if you like: nicely formatted table in report
penguins %>% 
  kableExtra::kbl() %>%
  kableExtra::kable_paper(full_width = TRUE) %>%
  kableExtra::kable_styling(bootstrap_options = c("striped", "condensed", "responsive")) %>%
  kableExtra::scroll_box(width = "700px", height = "500px")

species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adélie	Torgersen	39.1	18.7	181	3750	male	2007
Adélie	Torgersen	39.5	17.4	186	3800	female	2007
Adélie	Torgersen	40.3	18.0	195	3250	female	2007
Adélie	Torgersen	36.7	19.3	193	3450	female	2007
Adélie	Torgersen	39.3	20.6	190	3650	male	2007
Adélie	Torgersen	38.9	17.8	181	3625	female	2007
Adélie	Torgersen	39.2	19.6	195	4675	male	2007
Adélie	Torgersen	34.1	18.1	193	3475	NA	2007
Adélie	Torgersen	42.0	20.2	190	4250	NA	2007
Adélie	Torgersen	37.8	17.1	186	3300	NA	2007
Adélie	Torgersen	37.8	17.3	180	3700	NA	2007
Adélie	Torgersen	41.1	17.6	182	3200	female	2007
Adélie	Torgersen	38.6	21.2	191	3800	male	2007
Adélie	Torgersen	34.6	21.1	198	4400	male	2007
Adélie	Torgersen	36.6	17.8	185	3700	female	2007
Adélie	Torgersen	38.7	19.0	195	3450	female	2007
Adélie	Torgersen	42.5	20.7	197	4500	male	2007
Adélie	Torgersen	34.4	18.4	184	3325	female	2007
Adélie	Torgersen	46.0	21.5	194	4200	male	2007
Adélie	Biscoe	37.8	18.3	174	3400	female	2007
Adélie	Biscoe	37.7	18.7	180	3600	male	2007
Adélie	Biscoe	35.9	19.2	189	3800	female	2007
Adélie	Biscoe	38.2	18.1	185	3950	male	2007
Adélie	Biscoe	38.8	17.2	180	3800	male	2007
Adélie	Biscoe	35.3	18.9	187	3800	female	2007
Adélie	Biscoe	40.6	18.6	183	3550	male	2007
Adélie	Biscoe	40.5	17.9	187	3200	female	2007
Adélie	Biscoe	37.9	18.6	172	3150	female	2007
Adélie	Biscoe	40.5	18.9	180	3950	male	2007
Adélie	Dream	39.5	16.7	178	3250	female	2007
Adélie	Dream	37.2	18.1	178	3900	male	2007
Adélie	Dream	39.5	17.8	188	3300	female	2007
Adélie	Dream	40.9	18.9	184	3900	male	2007
Adélie	Dream	36.4	17.0	195	3325	female	2007
Adélie	Dream	39.2	21.1	196	4150	male	2007
Adélie	Dream	38.8	20.0	190	3950	male	2007
Adélie	Dream	42.2	18.5	180	3550	female	2007
Adélie	Dream	37.6	19.3	181	3300	female	2007
Adélie	Dream	39.8	19.1	184	4650	male	2007
Adélie	Dream	36.5	18.0	182	3150	female	2007
Adélie	Dream	40.8	18.4	195	3900	male	2007
Adélie	Dream	36.0	18.5	186	3100	female	2007
Adélie	Dream	44.1	19.7	196	4400	male	2007
Adélie	Dream	37.0	16.9	185	3000	female	2007
Adélie	Dream	39.6	18.8	190	4600	male	2007
Adélie	Dream	41.1	19.0	182	3425	male	2007
Adélie	Dream	37.5	18.9	179	2975	NA	2007
Adélie	Dream	36.0	17.9	190	3450	female	2007
Adélie	Dream	42.3	21.2	191	4150	male	2007
Adélie	Biscoe	39.6	17.7	186	3500	female	2008
Adélie	Biscoe	40.1	18.9	188	4300	male	2008
Adélie	Biscoe	35.0	17.9	190	3450	female	2008
Adélie	Biscoe	42.0	19.5	200	4050	male	2008
Adélie	Biscoe	34.5	18.1	187	2900	female	2008
Adélie	Biscoe	41.4	18.6	191	3700	male	2008
Adélie	Biscoe	39.0	17.5	186	3550	female	2008
Adélie	Biscoe	40.6	18.8	193	3800	male	2008
Adélie	Biscoe	36.5	16.6	181	2850	female	2008
Adélie	Biscoe	37.6	19.1	194	3750	male	2008
Adélie	Biscoe	35.7	16.9	185	3150	female	2008
Adélie	Biscoe	41.3	21.1	195	4400	male	2008
Adélie	Biscoe	37.6	17.0	185	3600	female	2008
Adélie	Biscoe	41.1	18.2	192	4050	male	2008
Adélie	Biscoe	36.4	17.1	184	2850	female	2008
Adélie	Biscoe	41.6	18.0	192	3950	male	2008
Adélie	Biscoe	35.5	16.2	195	3350	female	2008
Adélie	Biscoe	41.1	19.1	188	4100	male	2008
Adélie	Torgersen	35.9	16.6	190	3050	female	2008
Adélie	Torgersen	41.8	19.4	198	4450	male	2008
Adélie	Torgersen	33.5	19.0	190	3600	female	2008
Adélie	Torgersen	39.7	18.4	190	3900	male	2008
Adélie	Torgersen	39.6	17.2	196	3550	female	2008
Adélie	Torgersen	45.8	18.9	197	4150	male	2008
Adélie	Torgersen	35.5	17.5	190	3700	female	2008
Adélie	Torgersen	42.8	18.5	195	4250	male	2008
Adélie	Torgersen	40.9	16.8	191	3700	female	2008
Adélie	Torgersen	37.2	19.4	184	3900	male	2008
Adélie	Torgersen	36.2	16.1	187	3550	female	2008
Adélie	Torgersen	42.1	19.1	195	4000	male	2008
Adélie	Torgersen	34.6	17.2	189	3200	female	2008
Adélie	Torgersen	42.9	17.6	196	4700	male	2008
Adélie	Torgersen	36.7	18.8	187	3800	female	2008
Adélie	Torgersen	35.1	19.4	193	4200	male	2008
Adélie	Dream	37.3	17.8	191	3350	female	2008
Adélie	Dream	41.3	20.3	194	3550	male	2008
Adélie	Dream	36.3	19.5	190	3800	male	2008
Adélie	Dream	36.9	18.6	189	3500	female	2008
Adélie	Dream	38.3	19.2	189	3950	male	2008
Adélie	Dream	38.9	18.8	190	3600	female	2008
Adélie	Dream	35.7	18.0	202	3550	female	2008
Adélie	Dream	41.1	18.1	205	4300	male	2008
Adélie	Dream	34.0	17.1	185	3400	female	2008
Adélie	Dream	39.6	18.1	186	4450	male	2008
Adélie	Dream	36.2	17.3	187	3300	female	2008
Adélie	Dream	40.8	18.9	208	4300	male	2008
Adélie	Dream	38.1	18.6	190	3700	female	2008
Adélie	Dream	40.3	18.5	196	4350	male	2008
Adélie	Dream	33.1	16.1	178	2900	female	2008
Adélie	Dream	43.2	18.5	192	4100	male	2008
Adélie	Biscoe	35.0	17.9	192	3725	female	2009
Adélie	Biscoe	41.0	20.0	203	4725	male	2009
Adélie	Biscoe	37.7	16.0	183	3075	female	2009
Adélie	Biscoe	37.8	20.0	190	4250	male	2009
Adélie	Biscoe	37.9	18.6	193	2925	female	2009
Adélie	Biscoe	39.7	18.9	184	3550	male	2009
Adélie	Biscoe	38.6	17.2	199	3750	female	2009
Adélie	Biscoe	38.2	20.0	190	3900	male	2009
Adélie	Biscoe	38.1	17.0	181	3175	female	2009
Adélie	Biscoe	43.2	19.0	197	4775	male	2009
Adélie	Biscoe	38.1	16.5	198	3825	female	2009
Adélie	Biscoe	45.6	20.3	191	4600	male	2009
Adélie	Biscoe	39.7	17.7	193	3200	female	2009
Adélie	Biscoe	42.2	19.5	197	4275	male	2009
Adélie	Biscoe	39.6	20.7	191	3900	female	2009
Adélie	Biscoe	42.7	18.3	196	4075	male	2009
Adélie	Torgersen	38.6	17.0	188	2900	female	2009
Adélie	Torgersen	37.3	20.5	199	3775	male	2009
Adélie	Torgersen	35.7	17.0	189	3350	female	2009
Adélie	Torgersen	41.1	18.6	189	3325	male	2009
Adélie	Torgersen	36.2	17.2	187	3150	female	2009
Adélie	Torgersen	37.7	19.8	198	3500	male	2009
Adélie	Torgersen	40.2	17.0	176	3450	female	2009
Adélie	Torgersen	41.4	18.5	202	3875	male	2009
Adélie	Torgersen	35.2	15.9	186	3050	female	2009
Adélie	Torgersen	40.6	19.0	199	4000	male	2009
Adélie	Torgersen	38.8	17.6	191	3275	female	2009
Adélie	Torgersen	41.5	18.3	195	4300	male	2009
Adélie	Torgersen	39.0	17.1	191	3050	female	2009
Adélie	Torgersen	44.1	18.0	210	4000	male	2009
Adélie	Torgersen	38.5	17.9	190	3325	female	2009
Adélie	Torgersen	43.1	19.2	197	3500	male	2009
Adélie	Dream	36.8	18.5	193	3500	female	2009
Adélie	Dream	37.5	18.5	199	4475	male	2009
Adélie	Dream	38.1	17.6	187	3425	female	2009
Adélie	Dream	41.1	17.5	190	3900	male	2009
Adélie	Dream	35.6	17.5	191	3175	female	2009
Adélie	Dream	40.2	20.1	200	3975	male	2009
Adélie	Dream	37.0	16.5	185	3400	female	2009
Adélie	Dream	39.7	17.9	193	4250	male	2009
Adélie	Dream	40.2	17.1	193	3400	female	2009
Adélie	Dream	40.6	17.2	187	3475	male	2009
Adélie	Dream	32.1	15.5	188	3050	female	2009
Adélie	Dream	40.7	17.0	190	3725	male	2009
Adélie	Dream	37.3	16.8	192	3000	female	2009
Adélie	Dream	39.0	18.7	185	3650	male	2009
Adélie	Dream	39.2	18.6	190	4250	male	2009
Adélie	Dream	36.6	18.4	184	3475	female	2009
Adélie	Dream	36.0	17.8	195	3450	female	2009
Adélie	Dream	37.8	18.1	193	3750	male	2009
Adélie	Dream	36.0	17.1	187	3700	female	2009
Adélie	Dream	41.5	18.5	201	4000	male	2009
Gentoo	Biscoe	46.1	13.2	211	4500	female	2007
Gentoo	Biscoe	50.0	16.3	230	5700	male	2007
Gentoo	Biscoe	48.7	14.1	210	4450	female	2007
Gentoo	Biscoe	50.0	15.2	218	5700	male	2007
Gentoo	Biscoe	47.6	14.5	215	5400	male	2007
Gentoo	Biscoe	46.5	13.5	210	4550	female	2007
Gentoo	Biscoe	45.4	14.6	211	4800	female	2007
Gentoo	Biscoe	46.7	15.3	219	5200	male	2007
Gentoo	Biscoe	43.3	13.4	209	4400	female	2007
Gentoo	Biscoe	46.8	15.4	215	5150	male	2007
Gentoo	Biscoe	40.9	13.7	214	4650	female	2007
Gentoo	Biscoe	49.0	16.1	216	5550	male	2007
Gentoo	Biscoe	45.5	13.7	214	4650	female	2007
Gentoo	Biscoe	48.4	14.6	213	5850	male	2007
Gentoo	Biscoe	45.8	14.6	210	4200	female	2007
Gentoo	Biscoe	49.3	15.7	217	5850	male	2007
Gentoo	Biscoe	42.0	13.5	210	4150	female	2007
Gentoo	Biscoe	49.2	15.2	221	6300	male	2007
Gentoo	Biscoe	46.2	14.5	209	4800	female	2007
Gentoo	Biscoe	48.7	15.1	222	5350	male	2007
Gentoo	Biscoe	50.2	14.3	218	5700	male	2007
Gentoo	Biscoe	45.1	14.5	215	5000	female	2007
Gentoo	Biscoe	46.5	14.5	213	4400	female	2007
Gentoo	Biscoe	46.3	15.8	215	5050	male	2007
Gentoo	Biscoe	42.9	13.1	215	5000	female	2007
Gentoo	Biscoe	46.1	15.1	215	5100	male	2007
Gentoo	Biscoe	44.5	14.3	216	4100	NA	2007
Gentoo	Biscoe	47.8	15.0	215	5650	male	2007
Gentoo	Biscoe	48.2	14.3	210	4600	female	2007
Gentoo	Biscoe	50.0	15.3	220	5550	male	2007
Gentoo	Biscoe	47.3	15.3	222	5250	male	2007
Gentoo	Biscoe	42.8	14.2	209	4700	female	2007
Gentoo	Biscoe	45.1	14.5	207	5050	female	2007
Gentoo	Biscoe	59.6	17.0	230	6050	male	2007
Gentoo	Biscoe	49.1	14.8	220	5150	female	2008
Gentoo	Biscoe	48.4	16.3	220	5400	male	2008
Gentoo	Biscoe	42.6	13.7	213	4950	female	2008
Gentoo	Biscoe	44.4	17.3	219	5250	male	2008
Gentoo	Biscoe	44.0	13.6	208	4350	female	2008
Gentoo	Biscoe	48.7	15.7	208	5350	male	2008
Gentoo	Biscoe	42.7	13.7	208	3950	female	2008
Gentoo	Biscoe	49.6	16.0	225	5700	male	2008
Gentoo	Biscoe	45.3	13.7	210	4300	female	2008
Gentoo	Biscoe	49.6	15.0	216	4750	male	2008
Gentoo	Biscoe	50.5	15.9	222	5550	male	2008
Gentoo	Biscoe	43.6	13.9	217	4900	female	2008
Gentoo	Biscoe	45.5	13.9	210	4200	female	2008
Gentoo	Biscoe	50.5	15.9	225	5400	male	2008
Gentoo	Biscoe	44.9	13.3	213	5100	female	2008
Gentoo	Biscoe	45.2	15.8	215	5300	male	2008
Gentoo	Biscoe	46.6	14.2	210	4850	female	2008
Gentoo	Biscoe	48.5	14.1	220	5300	male	2008
Gentoo	Biscoe	45.1	14.4	210	4400	female	2008
Gentoo	Biscoe	50.1	15.0	225	5000	male	2008
Gentoo	Biscoe	46.5	14.4	217	4900	female	2008
Gentoo	Biscoe	45.0	15.4	220	5050	male	2008
Gentoo	Biscoe	43.8	13.9	208	4300	female	2008
Gentoo	Biscoe	45.5	15.0	220	5000	male	2008
Gentoo	Biscoe	43.2	14.5	208	4450	female	2008
Gentoo	Biscoe	50.4	15.3	224	5550	male	2008
Gentoo	Biscoe	45.3	13.8	208	4200	female	2008
Gentoo	Biscoe	46.2	14.9	221	5300	male	2008
Gentoo	Biscoe	45.7	13.9	214	4400	female	2008
Gentoo	Biscoe	54.3	15.7	231	5650	male	2008
Gentoo	Biscoe	45.8	14.2	219	4700	female	2008
Gentoo	Biscoe	49.8	16.8	230	5700	male	2008
Gentoo	Biscoe	46.2	14.4	214	4650	NA	2008
Gentoo	Biscoe	49.5	16.2	229	5800	male	2008
Gentoo	Biscoe	43.5	14.2	220	4700	female	2008
Gentoo	Biscoe	50.7	15.0	223	5550	male	2008
Gentoo	Biscoe	47.7	15.0	216	4750	female	2008
Gentoo	Biscoe	46.4	15.6	221	5000	male	2008
Gentoo	Biscoe	48.2	15.6	221	5100	male	2008
Gentoo	Biscoe	46.5	14.8	217	5200	female	2008
Gentoo	Biscoe	46.4	15.0	216	4700	female	2008
Gentoo	Biscoe	48.6	16.0	230	5800	male	2008
Gentoo	Biscoe	47.5	14.2	209	4600	female	2008
Gentoo	Biscoe	51.1	16.3	220	6000	male	2008
Gentoo	Biscoe	45.2	13.8	215	4750	female	2008
Gentoo	Biscoe	45.2	16.4	223	5950	male	2008
Gentoo	Biscoe	49.1	14.5	212	4625	female	2009
Gentoo	Biscoe	52.5	15.6	221	5450	male	2009
Gentoo	Biscoe	47.4	14.6	212	4725	female	2009
Gentoo	Biscoe	50.0	15.9	224	5350	male	2009
Gentoo	Biscoe	44.9	13.8	212	4750	female	2009
Gentoo	Biscoe	50.8	17.3	228	5600	male	2009
Gentoo	Biscoe	43.4	14.4	218	4600	female	2009
Gentoo	Biscoe	51.3	14.2	218	5300	male	2009
Gentoo	Biscoe	47.5	14.0	212	4875	female	2009
Gentoo	Biscoe	52.1	17.0	230	5550	male	2009
Gentoo	Biscoe	47.5	15.0	218	4950	female	2009
Gentoo	Biscoe	52.2	17.1	228	5400	male	2009
Gentoo	Biscoe	45.5	14.5	212	4750	female	2009
Gentoo	Biscoe	49.5	16.1	224	5650	male	2009
Gentoo	Biscoe	44.5	14.7	214	4850	female	2009
Gentoo	Biscoe	50.8	15.7	226	5200	male	2009
Gentoo	Biscoe	49.4	15.8	216	4925	male	2009
Gentoo	Biscoe	46.9	14.6	222	4875	female	2009
Gentoo	Biscoe	48.4	14.4	203	4625	female	2009
Gentoo	Biscoe	51.1	16.5	225	5250	male	2009
Gentoo	Biscoe	48.5	15.0	219	4850	female	2009
Gentoo	Biscoe	55.9	17.0	228	5600	male	2009
Gentoo	Biscoe	47.2	15.5	215	4975	female	2009
Gentoo	Biscoe	49.1	15.0	228	5500	male	2009
Gentoo	Biscoe	47.3	13.8	216	4725	NA	2009
Gentoo	Biscoe	46.8	16.1	215	5500	male	2009
Gentoo	Biscoe	41.7	14.7	210	4700	female	2009
Gentoo	Biscoe	53.4	15.8	219	5500	male	2009
Gentoo	Biscoe	43.3	14.0	208	4575	female	2009
Gentoo	Biscoe	48.1	15.1	209	5500	male	2009
Gentoo	Biscoe	50.5	15.2	216	5000	female	2009
Gentoo	Biscoe	49.8	15.9	229	5950	male	2009
Gentoo	Biscoe	43.5	15.2	213	4650	female	2009
Gentoo	Biscoe	51.5	16.3	230	5500	male	2009
Gentoo	Biscoe	46.2	14.1	217	4375	female	2009
Gentoo	Biscoe	55.1	16.0	230	5850	male	2009
Gentoo	Biscoe	44.5	15.7	217	4875	NA	2009
Gentoo	Biscoe	48.8	16.2	222	6000	male	2009
Gentoo	Biscoe	47.2	13.7	214	4925	female	2009
Gentoo	Biscoe	46.8	14.3	215	4850	female	2009
Gentoo	Biscoe	50.4	15.7	222	5750	male	2009
Gentoo	Biscoe	45.2	14.8	212	5200	female	2009
Gentoo	Biscoe	49.9	16.1	213	5400	male	2009
Chinstrap	Dream	46.5	17.9	192	3500	female	2007
Chinstrap	Dream	50.0	19.5	196	3900	male	2007
Chinstrap	Dream	51.3	19.2	193	3650	male	2007
Chinstrap	Dream	45.4	18.7	188	3525	female	2007
Chinstrap	Dream	52.7	19.8	197	3725	male	2007
Chinstrap	Dream	45.2	17.8	198	3950	female	2007
Chinstrap	Dream	46.1	18.2	178	3250	female	2007
Chinstrap	Dream	51.3	18.2	197	3750	male	2007
Chinstrap	Dream	46.0	18.9	195	4150	female	2007
Chinstrap	Dream	51.3	19.9	198	3700	male	2007
Chinstrap	Dream	46.6	17.8	193	3800	female	2007
Chinstrap	Dream	51.7	20.3	194	3775	male	2007
Chinstrap	Dream	47.0	17.3	185	3700	female	2007
Chinstrap	Dream	52.0	18.1	201	4050	male	2007
Chinstrap	Dream	45.9	17.1	190	3575	female	2007
Chinstrap	Dream	50.5	19.6	201	4050	male	2007
Chinstrap	Dream	50.3	20.0	197	3300	male	2007
Chinstrap	Dream	58.0	17.8	181	3700	female	2007
Chinstrap	Dream	46.4	18.6	190	3450	female	2007
Chinstrap	Dream	49.2	18.2	195	4400	male	2007
Chinstrap	Dream	42.4	17.3	181	3600	female	2007
Chinstrap	Dream	48.5	17.5	191	3400	male	2007
Chinstrap	Dream	43.2	16.6	187	2900	female	2007
Chinstrap	Dream	50.6	19.4	193	3800	male	2007
Chinstrap	Dream	46.7	17.9	195	3300	female	2007
Chinstrap	Dream	52.0	19.0	197	4150	male	2007
Chinstrap	Dream	50.5	18.4	200	3400	female	2008
Chinstrap	Dream	49.5	19.0	200	3800	male	2008
Chinstrap	Dream	46.4	17.8	191	3700	female	2008
Chinstrap	Dream	52.8	20.0	205	4550	male	2008
Chinstrap	Dream	40.9	16.6	187	3200	female	2008
Chinstrap	Dream	54.2	20.8	201	4300	male	2008
Chinstrap	Dream	42.5	16.7	187	3350	female	2008
Chinstrap	Dream	51.0	18.8	203	4100	male	2008
Chinstrap	Dream	49.7	18.6	195	3600	male	2008
Chinstrap	Dream	47.5	16.8	199	3900	female	2008
Chinstrap	Dream	47.6	18.3	195	3850	female	2008
Chinstrap	Dream	52.0	20.7	210	4800	male	2008
Chinstrap	Dream	46.9	16.6	192	2700	female	2008
Chinstrap	Dream	53.5	19.9	205	4500	male	2008
Chinstrap	Dream	49.0	19.5	210	3950	male	2008
Chinstrap	Dream	46.2	17.5	187	3650	female	2008
Chinstrap	Dream	50.9	19.1	196	3550	male	2008
Chinstrap	Dream	45.5	17.0	196	3500	female	2008
Chinstrap	Dream	50.9	17.9	196	3675	female	2009
Chinstrap	Dream	50.8	18.5	201	4450	male	2009
Chinstrap	Dream	50.1	17.9	190	3400	female	2009
Chinstrap	Dream	49.0	19.6	212	4300	male	2009
Chinstrap	Dream	51.5	18.7	187	3250	male	2009
Chinstrap	Dream	49.8	17.3	198	3675	female	2009
Chinstrap	Dream	48.1	16.4	199	3325	female	2009
Chinstrap	Dream	51.4	19.0	201	3950	male	2009
Chinstrap	Dream	45.7	17.3	193	3600	female	2009
Chinstrap	Dream	50.7	19.7	203	4050	male	2009
Chinstrap	Dream	42.5	17.3	187	3350	female	2009
Chinstrap	Dream	52.2	18.8	197	3450	male	2009
Chinstrap	Dream	45.2	16.6	191	3250	female	2009
Chinstrap	Dream	49.3	19.9	203	4050	male	2009
Chinstrap	Dream	50.2	18.8	202	3800	male	2009
Chinstrap	Dream	45.6	19.4	194	3525	female	2009
Chinstrap	Dream	51.9	19.5	206	3950	male	2009
Chinstrap	Dream	46.8	16.5	189	3650	female	2009
Chinstrap	Dream	45.7	17.0	195	3650	female	2009
Chinstrap	Dream	55.8	19.8	207	4000	male	2009
Chinstrap	Dream	43.5	18.1	202	3400	female	2009
Chinstrap	Dream	49.6	18.2	193	3775	male	2009
Chinstrap	Dream	50.8	19.0	210	4100	male	2009
Chinstrap	Dream	50.2	18.7	198	3775	female	2009

show

write.csv(penguins, "penguins.csv")

Basic Plot

show

## simple plot: data + mappings + geometry
ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(alpha = .6, size = 3.5)+
  theme_minimal()

show

##ggsave("00_scatterplot_raw.pdf", width = 9, height = 8, device = cairo_pdf)

Customized Plot

show

## change global theme settings (for all following plots)
theme_set(theme_minimal(base_size = 12, base_family = "Open Sans"))

## modify plot elements globally (for all following plots)
theme_update(
  axis.ticks = element_line(color = "grey92"),
  axis.ticks.length = unit(.5, "lines"),
  panel.grid.minor = element_blank(),
  legend.title = element_text(size = 12),
  legend.text = element_text(color = "grey30"),
  plot.title = element_text(size = 18, face = "bold"),
  plot.subtitle = element_text(size = 12, color = "grey30"),
  plot.caption = element_text(size = 9, margin = margin(t = 15))
)

show

ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = body_mass_g), alpha = .6, size = 3.5) + 
  ## custom axes scaling
  scale_x_continuous(breaks = 3:6 * 10, limits = c(30, 60)) +
  scale_y_continuous(breaks = seq(12.5, 22.5, by = 2.5), limits = c(12.5, 22.5)) +
  ## custom colors
  scico::scale_color_scico(palette = "bukavu", direction = -1) +
  ## custom labels
  labs(
    title = 'Bill Dimensions of Brush-Tailed Penguins (Pygoscelis)',
    subtitle = 'A scatter plot of bill depth versus bill length.',
    caption = 'Data: Gorman, Williams & Fraser (2014) PLoS ONE',
    x = 'Bill Length (mm)', 
    y = 'Bill Depth (mm)',
    color = 'Body mass (g)'
  )

show

ggsave("01_theme_color_labs.pdf", width = 9, height = 8, device = cairo_pdf)

{ggtext}

The ggtext package provides simple Markdown and HTML rendering for ggplot2. Under the hood, the package uses the gridtext package for the actual rendering, and consequently it is limited to the feature set provided by gridtext.
Support is provided for Markdown both in theme elements (plot titles, subtitles, captions, axis labels, legends, etc.) and in geoms (similar to geom_text()). In both cases, there are two alternatives, one for creating simple text labels and one for creating text boxes with word wrapping.

→ www.wilkelab.org/ggtext

element_markdown()

element_markdwon() → formatted text elements, e.g. titles, caption, axis text, striptext

show

## assign plot to `g` - we can ad new things to this plot later
## (wrapped in parenthesis so it is assigned and plotted in one step)
(gt <- ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = body_mass_g), alpha = .6, size = 3.5) + 
  scale_x_continuous(breaks = 3:6 * 10, limits = c(30, 60)) +
  scale_y_continuous(breaks = seq(12.5, 22.5, by = 2.5), limits = c(12.5, 22.5)) +
  scico::scale_color_scico(palette = "bukavu", direction = -1) +
  ## markdown formatting using asterisks
  labs(
    title = 'Bill Dimensions of Brush-Tailed Penguins (*Pygoscelis*)',
    subtitle = 'A scatter plot of bill depth versus bill length.',
    caption = 'Data: Gorman, Williams & Fraser (2014) *PLoS ONE*',
    x = '**Bill Length** (mm)', 
    y = '**Bill Depth** (mm)',
    color = 'Body mass (g)'
  ) +
  ## render respective text elements
  theme(
    plot.title = ggtext::element_markdown(),
    plot.caption = ggtext::element_markdown(),
    axis.title.x = ggtext::element_markdown(),
    axis.title.y = ggtext::element_markdown()
  )
)

show

ggsave("02a_ggtext_element_markdown.pdf", width = 9, height = 8, device = cairo_pdf)

element_markdown() in combination with HTML

show

## use HTML syntax to change text color
gt_mar <- gt +
  labs(title = 'Bill Dimensions of Brush-Tailed Penguins <i style="color:#28A87D;">Pygoscelis</i>') +
  theme(plot.margin = margin(t = 25))

ggsave("02b_ggtext_element_markdown_color.pdf", width = 9, height = 8, device = cairo_pdf)

## use HTML syntax to change font and text size
gt_mar +
  labs(title = 'Bill Dimensions of Brush-Tailed Penguins <b style="font-size:32pt;font-family:blacksword;">Pygoscelis</b>')

show

ggsave("02c_ggtext_element_markdown_font.pdf", width = 9, height = 8, device = cairo_pdf)

## use HTML syntax to add images to text elements
##gt_mar + 
  #labs(title = 'Bill Dimensions of Brush-Tailed Penguins <img src="https://www.researchgate.net/profile/Jean_Lightner/publication/274710342/figure/fig8/AS:614338578640906@1523481139381/Pygoscelis-papua-Source-Wikipedia-http-wwwenwikipediaorg.png"‚ width="100"/>') +
  ## title with missing quotation mark to make an erroneous pdf - 
  ## otherwise it throws an error because of RCurl on Windows OS
  ##labs(title = 'Bill Dimensions of Brush-Tailed Penguins <img src="https://www.researchgate.net/profile/Jean_Lightner/publication/274710342/figure/fig8/AS:614338578640906@1523481139381/Pygoscelis-papua-Source-Wikipedia-http-wwwenwikipediaorg.png‚ width="100"/>') +
    
##ggsave("02d_ggtext_element_markdown_image.pdf", width = 9, height = 8, device = cairo_pdf)

element_textbox(), geom_richtext() and geom_textbox()

geom_richtext() → formatted text labels with 360° rotation

show

gt_rich <- ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species), alpha = .6, size = 3.5) + 
  ## add text annotations for each species
  ggtext::geom_richtext(
    data = tibble(
      x = c(34, 56, 54), y = c(20, 18.5, 14.5),
      species = c("Adélie", "Chinstrap", "Gentoo"),
      lab = c("<b style='font-family:anton;font-size:24pt;'>Adélie</b><br><i style='color:darkgrey;'>P. adéliae</i>", 
              "<b style='font-family:anton;font-size:24pt;'>Chinstrap</b><br><i style='color:darkgrey;'>P. antarctica</i>", 
              "<b style='font-family:anton;font-size:24pt;'>Gentoo</b><br><i style='color:darkgrey;'>P. papua</i>"),
      angle = c(12, 20, 335)
    ),
    aes(x, y, label = lab, color = species, angle = angle), 
    size = 4, fill = NA, label.color = NA,
    lineheight = .3
  ) +
  scale_x_continuous(breaks = 3:6 * 10, limits = c(30, 60)) +
  scale_y_continuous(breaks = seq(12.5, 22.5, by = 2.5), limits = c(12.5, 22.5)) +
  rcartocolor::scale_color_carto_d(palette = "Bold", guide = "none") +
  labs(
    title = 'Bill Dimensions of Brush-Tailed Penguins (*Pygoscelis*)',
    subtitle = 'A scatter plot of bill depth versus bill length.',
    caption = 'Data: Gorman, Williams & Fraser (2014) *PLoS ONE*',
    x = '**Bill Length** (mm)', 
    y = '**Bill Depth** (mm)',
    color = 'Body mass (g)'
  )

(gt_rich +
  theme(
    plot.title = ggtext::element_markdown(),
    plot.caption = ggtext::element_markdown(),
    axis.title.x = ggtext::element_markdown(),
    axis.title.y = ggtext::element_markdown(),
    plot.margin = margin(25, 6, 15, 6)
  )
)

show

ggsave("02e_ggtext_geom_richtext.pdf", width = 9, height = 8, device = cairo_pdf)

element_textbox() and element_textbox_simple() → formatted text boxes with word wrapping

show

gt_box <- gt_rich +
  theme(
    ## turn title into filled textbox
    plot.title = ggtext::element_textbox_simple( "Prueba",
      color = "white", fill = "#28A87D",  size = 32, 
      padding = margin(8, 4, 8, 4), margin = margin(b = 5), lineheight= .9
    ),
    ## add round outline to caption
    plot.caption = ggtext::element_textbox_simple("Prueba2",
      width = NULL, linetype = 1, padding = margin(4, 8, 4, 8), 
      margin = margin(t = 15), r = grid::unit(8, "pt")
    ),
    axis.title.x = ggtext::element_markdown(),
    axis.title.y = ggtext::element_markdown(),
    plot.margin = margin(25, 6, 15, 6)
  )


##ggsave("02f_ggtext_element_textbox.pdf", width = 9, height = 8, device = cairo_pdf)

geom_textbox() → formatted text boxes with word wrapping

show

gt_box +
  ## add textbox with long paragraphs
  ggtext::geom_textbox(
    data = tibble(x = 34, y = 13.7, label = "<span style='font-size:12pt;font-family:anton;'>Lorem Ipsum Dolor Sit Amet</span><br><br>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum."),
    aes(x, y, label = label),
    size = 2.2, family = "Open Sans",
    fill = "cornsilk", box.color = "cornsilk3",
    width = unit(11, "lines")
  ) +
  coord_cartesian(clip = "off")

show

ggsave("02g_ggtext_geom_textbox.pdf", width = 9, height = 8, device = cairo_pdf)

show

## use ggtext rendering for the following plots
theme_update(
  plot.title = ggtext::element_markdown(),
  plot.caption = ggtext::element_markdown(),
  axis.title.x = ggtext::element_markdown(),
  axis.title.y = ggtext::element_markdown()
)

{ggforce}

ggforce is a package aimed at providing missing functionality to ggplot2 through the extension system introduced with ggplot2 v2.0.0. Broadly speaking ggplot2 has been aimed primarily at explorative data visualization in order to investigate the data at hand, and less at providing utilities for composing custom plots a la D3.js. ggforce is mainly an attempt to address these “shortcoming” (design choices might be a better description). The goal is to provide a repository of geoms, stats, etc. that are as well documented and implemented as the official ones found in ggplot2.

→ www.ggforce.data-imaginist.com

show

## plot that we will annotate with gggforce afterwards
gf <- ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) + 
  scico::scale_color_scico(palette = "bukavu", direction = -1) +
  coord_cartesian(xlim = c(25, 65), ylim = c(10, 25)) +
  rcartocolor::scale_fill_carto_d(palette = "Bold") +
  labs(
    title = "Bill Dimensions of Brush-Tailed Penguins (*Pygoscelis*)",
    subtitle = 'A scatter plot of bill depth versus bill length.',
    caption = "Data: Gorman, Williams & Fraser (2014) *PLoS ONE*",
    x = "**Bill Length** (mm)", 
    y = "**Bill Depth** (mm)",
    color = "Body mass (g)",
    fill = "Species"
  )
 
## ellipsoids for all groups
(gf +
  ggforce::geom_mark_ellipse(
    aes(fill = species, label = species), 
    alpha = .15, show.legend = FALSE
  ) +
  geom_point(aes(color = body_mass_g), alpha = .6, size = 3.5)
)

show

ggsave("03a_ggforce_geom_mark_ellipsoid.pdf", width = 9, height = 8, device = cairo_pdf)
 
## ellipsoids for specific subset
(gf +
  ggforce::geom_mark_ellipse(
    aes(fill = species, label = species, filter = species == 'Gentoo'), 
    alpha = 0, show.legend = FALSE
  ) +
  geom_point(aes(color = body_mass_g), alpha = .6, size = 3.5) +
  coord_cartesian(xlim = c(25, 65), ylim = c(10, 25))
)

show

ggsave("03b_ggforce_geom_mark_filtered.pdf", width = 9, height = 8, device = cairo_pdf)

## circles
(gf +
  ggforce::geom_mark_circle(
    aes(fill = species, label = species, filter = species == 'Gentoo'), 
    alpha = 0, show.legend = FALSE
  ) +
  geom_point(aes(color = body_mass_g), alpha = .6, size = 3.5)
)

show

ggsave("03c_ggforce_geom_mark_circle_b.pdf", width = 9, height = 8, device = cairo_pdf)

## rectangles
(gf +
  ggforce::geom_mark_rect(
    aes(fill = species, label = species, filter = species == 'Gentoo'), 
    alpha = 0, show.legend = FALSE
  ) +
  geom_point(aes(color = body_mass_g), alpha = .6, size = 3.5) 
)

show

ggsave("03d_ggforce_geom_mark_rect_b.pdf", width = 9, height = 8, device = cairo_pdf)

## hull
(gf +
  ggforce::geom_mark_hull(
    aes(fill = species, label = species, filter = species == 'Gentoo'), 
    alpha = 0, show.legend = FALSE
  ) +
  geom_point(aes(color = body_mass_g), alpha = .6, size = 3.5)
)

show

ggsave("03e_ggforce_geom_mark_hull_b.pdf", width = 9, height = 8, device = cairo_pdf)

ggplot tricks

show

(gg0 <- 
  ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) +
    ggforce::geom_mark_ellipse(
      aes(fill = species, label = species), 
      alpha = 0, show.legend = FALSE
    ) +
    geom_point(aes(color = body_mass_g), alpha = .6, size = 3.5) + 
    scale_x_continuous(breaks = seq(25, 65, by = 5), limits = c(25, 65)) +
    scale_y_continuous(breaks = seq(12, 24, by = 2), limits = c(12, 24)) +
    scico::scale_color_scico(palette = "bukavu", direction = -1) +
    labs(
      title = "Bill Dimensions of Brush-Tailed Penguins (*Pygoscelis*)",
      subtitle = 'A scatter plot of bill depth versus bill length.',
      caption = "Data: Gorman, Williams & Fraser (2014) *PLoS ONE*",
      x = "Bill Length (mm)", 
      y = "Bill Depth (mm)",
      color = "Body mass (g)"
    )
)

show

ggsave("04_scatterplot_mod_start.pdf", width = 9, height = 8, device = cairo_pdf)

Left-Aligned Title

show

(gg1 <- gg0 + theme(plot.title.position = "plot"))

show

ggsave("05a_position_title.pdf", width = 9, height = 8, device = cairo_pdf)

Right-Aligned Caption

show

(gg1b <- gg1 +  theme(plot.caption.position = "plot"))

show

ggsave("05b_position_caption.pdf", width = 9, height = 8, device = cairo_pdf)

Legend Design

show

(gg2 <- gg1b + theme(legend.position = "top"))

show

ggsave("06a_legend_position.pdf", width = 9, height = 8, device = cairo_pdf)

(gg2b <- gg2 + 
  guides(color = guide_colorbar(title.position = "top", 
                                title.hjust = .5, 
                                barwidth = unit(20, "lines"), 
                                barheight = unit(.5, "lines"))))

show

ggsave("06b_legend_guide.pdf", width = 9, height = 8, device = cairo_pdf)

Limit Expansion

show

(gg3 <- gg2b + coord_cartesian(expand = FALSE))

show

ggsave("07_coord_expand.pdf", width = 9, height = 8, device = cairo_pdf)

Geeky Details: Clipping

show

(gg3b <- gg3 + coord_cartesian(expand = FALSE, clip = "off"))

show

ggsave("08_coord_offclip.pdf", width = 9, height = 8, device = cairo_pdf)

White Space

show

(gg4 <- gg3b + theme(plot.margin = margin(t = 25, r = 25, b = 10, l = 25))) ## top, right, bottom, left

show

ggsave("09_theme_margin.pdf", width = 9, height = 8, device = cairo_pdf)

Add Images

show

## read PNG file from web
png <- magick::image_read("https://raw.githubusercontent.com/allisonhorst/palmerpenguins/master/man/figures/culmen_depth.png")
## turn image into `rasterGrob`
img <- grid::rasterGrob(png, interpolate = TRUE)

(gg5 <- gg4 +
  annotation_custom(img, ymin = 21.5, ymax = 30.5, xmin = 55, xmax = 65.5) +
    labs(caption = "Data: Gorman, Williams & Fraser (2014) *PLoS ONE* &bull; Illustration: Allison Horst"))

show

ggsave("10_annotate_img.pdf", width = 9, height = 8, device = cairo_pdf)

{patchwork}

The goal of patchwork is to make it ridiculously simple to combine separate ggplots into the same graphic. As such it tries to solve the same problem as gridExtra::grid.arrange() and cowplot::plot_grid but using an API that incites exploration and iteration, and scales to arbitrily complex layouts.

→ www.patchwork.data-imaginist.com

show

## calculate bill ratio and summary stats
df_peng_stats <- 
  penguins %>% 
  mutate(bill_ratio = bill_length_mm / bill_depth_mm) %>% 
  filter(!is.na(bill_ratio)) %>% 
  group_by(species) %>% 
  mutate(
    n = n(),
    median = median(bill_ratio),
    max = max(bill_ratio)
  ) %>% 
  ungroup() %>% 
  mutate(species_num = as.numeric(fct_rev(species))) 

## create a second chart with raincloud plots
p2 <- 
  ggplot(df_peng_stats, aes(bill_ratio, species_num, color = species)) +
  stat_summary(
    geom = "linerange",
    fun.min = function(x) -Inf,
    fun.max = function(x) median(x, na.rm = TRUE),
    linetype = "dotted",
    orientation = "y",
    size = .7
  ) +
  geom_point(
    aes(y = species_num - .15), 
    shape = "|",
    size = 5,
    alpha = .33
  ) +
  ggdist::stat_halfeye(
    aes(
      y = species_num,
      color = species,
      fill = after_scale(colorspace::lighten(color, .5))
    ),
    shape = 18,
    point_size = 3,
    interval_size = 1.8,
    adjust = .5,
    .width = c(0, 1)
  ) +
  geom_text(
    aes(x = median, label = format(round(median, 2), nsmall = 2)),
    stat = "unique",
    color = "white",
    family = "Open Sans",
    fontface = "bold",
    size = 3.4,
    nudge_y = .15
  ) +
  geom_text(
    aes(x = max, label = glue::glue("n = {n}")),
    stat = "unique",
    family = "Open Sans",
    fontface = "bold",
    size = 3.5,
    hjust = 0,
    nudge_x = .01,
    nudge_y = .02
  ) +
  coord_cartesian(clip = "off", expand = FALSE) +
  scale_x_continuous(
    limits = c(1.6, 3.8),
    breaks = seq(1.6, 3.8, by = .2)
  ) +
  scale_y_continuous(
    limits = c(.55, NA),
    breaks = 1:3,
    labels = c("Gentoo", "Chinstrap", "Adélie")
  ) +
  scale_color_manual(values = c("#3d6721", "#a86826", "#006c89"), guide = "none") +
  scale_fill_manual(values = c("#3d6721", "#a86826", "#006c89"), guide = "none") +
  labs(
    x = "Bill ratio",
    y = NULL,
    subtitle = "B. Raincloud plot showing the distribution of bill ratios, estimated as bill length divided by bill depth.",
    caption = "Data: Gorman, Williams & Fraser (2014) *PLoS ONE* &bull; Illustration: Allison Horst"
  ) +
  theme(
    panel.grid.major.x = element_line(size = .35),
    panel.grid.major.y = element_blank(),
    axis.text.y = element_text(size = 13),
    axis.ticks.length = unit(0, "lines"),
    plot.title.position = 'plot',
    plot.subtitle = element_text(margin = margin(t = 5, b = 10)),
    plot.margin = margin(10, 25, 10, 25)
  )

ggsave("11_raincloud_plot.pdf", width = 9, height = 5.2, device = cairo_pdf)

show

## combine both plots
(gg5 + labs(caption = NULL, subtitle = "A. Scatter plot of bill depth versus bill length.")) / p2 +
  plot_layout(heights = c(1, .65))

show

ggsave("12_patchwork_panel.pdf", width = 9, height = 13.2, device = cairo_pdf)

---

Resources

• Slides of my talk
• Intro to R (one of many good online tutorials)
• “R for Data Science” book (open-access)
• ggplot2 Book (open-access)
• R Graph Gallery
• My extensive ggplot2 tutorial
• My “Evolution of a ggplot” blog post
• #TidyTuesday project (#TidyTuesday on Twitter)
• My #TidyTuesday Contributions incl. all codes
• R4DS learning community (huge Slack community for people learning R incl. a mentoring program)
• Illustrations by Allison Horst (more general about data and stats + R-related)
• R Packages:
  • ggplot2
  • ggtext
  • ggforce
  • ggdist
  • ggraph
  • ggstream
  • ggbump
  • gggibous
  • waffle
  • geofacet
  • cartogram
  • patchwork
  • sf

---

Session Info

show

Sys.time()

[1] "2022-11-29 22:41:31 -04"

show

sessionInfo()

R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)

Matrix products: default

locale:
[1] LC_COLLATE=Spanish_Chile.utf8  LC_CTYPE=Spanish_Chile.utf8   
[3] LC_MONETARY=Spanish_Chile.utf8 LC_NUMERIC=C                  
[5] LC_TIME=Spanish_Chile.utf8    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods  
[7] base     

other attached packages:
 [1] patchwork_1.1.1   magick_2.7.3      ggdist_3.2.0     
 [4] ggforce_0.4.1     ggtext_0.1.2      scico_1.3.1      
 [7] systemfonts_1.0.4 forcats_0.5.1     stringr_1.4.0    
[10] dplyr_1.0.10      purrr_0.3.4       readr_2.1.2      
[13] tidyr_1.2.0       tibble_3.1.8      ggplot2_3.4.0    
[16] tidyverse_1.3.2  

loaded via a namespace (and not attached):
 [1] fs_1.5.2             lubridate_1.8.0      bit64_4.0.5         
 [4] webshot_0.5.3        httr_1.4.4           tools_4.2.2         
 [7] backports_1.4.1      bslib_0.4.0          utf8_1.2.2          
[10] R6_2.5.1             DBI_1.1.3            colorspace_2.0-3    
[13] withr_2.5.0          tidyselect_1.1.2     downlit_0.4.2       
[16] bit_4.0.4            curl_4.3.2           compiler_4.2.2      
[19] cli_3.3.0            rvest_1.0.2          xml2_1.3.3          
[22] labeling_0.4.2       sass_0.4.2           scales_1.2.0        
[25] digest_0.6.29        rmarkdown_2.14       svglite_2.1.0       
[28] pkgconfig_2.0.3      htmltools_0.5.3      highr_0.9           
[31] dbplyr_2.2.1         fastmap_1.1.0        rlang_1.0.6         
[34] readxl_1.4.1         rstudioapi_0.13      jquerylib_0.1.4     
[37] farver_2.1.1         generics_0.1.3       jsonlite_1.8.0      
[40] vroom_1.5.7          distill_1.5          googlesheets4_1.0.0 
[43] distributional_0.3.1 magrittr_2.0.3       kableExtra_1.3.4    
[46] Rcpp_1.0.9           munsell_0.5.0        fansi_1.0.3         
[49] lifecycle_1.0.3      stringi_1.7.8        yaml_2.3.5          
[52] MASS_7.3-58          grid_4.2.2           parallel_4.2.2      
[55] crayon_1.5.1         haven_2.5.0          gridtext_0.1.5      
[58] hms_1.1.1            knitr_1.39           pillar_1.8.0        
[61] markdown_1.1         reprex_2.0.1         glue_1.6.2          
[64] rcartocolor_2.0.0    evaluate_0.15        V8_4.2.2            
[67] modelr_0.1.8         vctrs_0.5.0          tzdb_0.3.0          
[70] tweenr_2.0.2         cellranger_1.1.0     gtable_0.3.0        
[73] polyclip_1.10-4      assertthat_0.2.1     cachem_1.0.6        
[76] xfun_0.31            broom_1.0.0          googledrive_2.0.0   
[79] viridisLite_0.4.0    gargle_1.2.0         memoise_2.0.1       
[82] concaveman_1.1.0     ellipsis_0.3.2