Load libraries
library (tidyverse)
library (janitor)
Iris dataset
## Rows: 150
## Columns: 5
## $ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.…
## $ Sepal.Width <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.…
## $ Petal.Length <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.…
## $ Petal.Width <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.…
## $ Species <fct> setosa, setosa, setosa, setosa, setosa, setosa, setosa, s…
iris_clean <- iris %>%
clean_names () %>%
pivot_longer (
cols = - species,
names_to = "measurement" ,
values_to = "value"
) %>%
mutate (
species = str_to_sentence (species),
measurement = str_replace (measurement, "_" , " " ) %>%
str_to_sentence ()
) %>%
glimpse ()
## Rows: 600
## Columns: 3
## $ species <chr> "Setosa", "Setosa", "Setosa", "Setosa", "Setosa", "Setosa"…
## $ measurement <chr> "Sepal length", "Sepal width", "Petal length", "Petal widt…
## $ value <dbl> 5.1, 3.5, 1.4, 0.2, 4.9, 3.0, 1.4, 0.2, 4.7, 3.2, 1.3, 0.2…
Visualization
Set plot defaults
Density of measurements by species
iris_clean %>%
ggplot (aes (x= value, color= species, fill= species)) +
geom_density (alpha= 1 / 5 ) +
facet_grid (
measurement~ species,
scales = "free_y"
) +
labs (
x = "Value" ,
y = "Density" ,
title = "Density of measurements by species" ,
color = "Species" ,
fill = "Species"
)
Session info
Show/hide
```
## ─ Session info ───────────────────────────────────────────────────────────────
## setting value
## version R version 4.0.4 (2021-02-15)
## os macOS Big Sur 10.16
## system x86_64, darwin17.0
## ui X11
## language (EN)
## collate en_US.UTF-8
## ctype en_US.UTF-8
## tz America/Mexico_City
## date 2021-03-15
##
## ─ Packages ───────────────────────────────────────────────────────────────────
## package * version date lib source
## assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.2)
## backports 1.2.1 2020-12-09 [1] CRAN (R 4.0.2)
## blogdown 1.2.1 2021-03-07 [1] Github (rstudio/blogdown@f324246)
## bookdown 0.21 2020-10-13 [1] CRAN (R 4.0.2)
## broom 0.7.5 2021-02-19 [1] CRAN (R 4.0.2)
## bslib 0.2.4 2021-01-25 [1] CRAN (R 4.0.2)
## cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.0.2)
## cli 2.3.1 2021-02-23 [1] CRAN (R 4.0.2)
## colorspace 2.0-0 2020-11-11 [1] CRAN (R 4.0.2)
## crayon 1.4.1 2021-02-08 [1] CRAN (R 4.0.2)
## DBI 1.1.1 2021-01-15 [1] CRAN (R 4.0.2)
## dbplyr 2.1.0 2021-02-03 [1] CRAN (R 4.0.2)
## digest 0.6.27 2020-10-24 [1] CRAN (R 4.0.2)
## dplyr * 1.0.4 2021-02-02 [1] CRAN (R 4.0.2)
## ellipsis 0.3.1 2020-05-15 [1] CRAN (R 4.0.2)
## evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.1)
## fansi 0.4.2 2021-01-15 [1] CRAN (R 4.0.2)
## farver 2.1.0 2021-02-28 [1] CRAN (R 4.0.4)
## forcats * 0.5.1 2021-01-27 [1] CRAN (R 4.0.2)
## fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2)
## generics 0.1.0 2020-10-31 [1] CRAN (R 4.0.2)
## ggplot2 * 3.3.3 2020-12-30 [1] CRAN (R 4.0.2)
## glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.2)
## gtable 0.3.0 2019-03-25 [1] CRAN (R 4.0.2)
## haven 2.3.1 2020-06-01 [1] CRAN (R 4.0.1)
## highr 0.8 2019-03-20 [1] CRAN (R 4.0.2)
## hms 1.0.0 2021-01-13 [1] CRAN (R 4.0.2)
## htmltools 0.5.1.1 2021-01-22 [1] CRAN (R 4.0.2)
## httr 1.4.2 2020-07-20 [1] CRAN (R 4.0.2)
## janitor * 2.1.0 2021-01-05 [1] CRAN (R 4.0.2)
## jquerylib 0.1.3 2020-12-17 [1] CRAN (R 4.0.2)
## jsonlite 1.7.2 2020-12-09 [1] CRAN (R 4.0.2)
## knitr 1.31 2021-01-27 [1] CRAN (R 4.0.2)
## labeling 0.4.2 2020-10-20 [1] CRAN (R 4.0.2)
## lifecycle 1.0.0 2021-02-15 [1] CRAN (R 4.0.2)
## lubridate 1.7.10 2021-02-26 [1] CRAN (R 4.0.2)
## magrittr 2.0.1 2020-11-17 [1] CRAN (R 4.0.2)
## modelr 0.1.8 2020-05-19 [1] CRAN (R 4.0.1)
## munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.2)
## pillar 1.5.0 2021-02-22 [1] CRAN (R 4.0.2)
## pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.2)
## purrr * 0.3.4 2020-04-17 [1] CRAN (R 4.0.2)
## R6 2.5.0 2020-10-28 [1] CRAN (R 4.0.2)
## Rcpp 1.0.6 2021-01-15 [1] CRAN (R 4.0.2)
## readr * 1.4.0 2020-10-05 [1] CRAN (R 4.0.2)
## readxl 1.3.1 2019-03-13 [1] CRAN (R 4.0.1)
## reprex 1.0.0 2021-01-27 [1] CRAN (R 4.0.2)
## rlang 0.4.10 2020-12-30 [1] CRAN (R 4.0.2)
## rmarkdown 2.7 2021-02-19 [1] CRAN (R 4.0.2)
## rstudioapi 0.13 2020-11-12 [1] CRAN (R 4.0.2)
## rvest 0.3.6 2020-07-25 [1] CRAN (R 4.0.2)
## sass 0.3.1 2021-01-24 [1] CRAN (R 4.0.2)
## scales 1.1.1 2020-05-11 [1] CRAN (R 4.0.2)
## sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.2)
## snakecase 0.11.0 2019-05-25 [1] CRAN (R 4.0.2)
## stringi 1.5.3 2020-09-09 [1] CRAN (R 4.0.2)
## stringr * 1.4.0 2019-02-10 [1] CRAN (R 4.0.2)
## tibble * 3.1.0 2021-02-25 [1] CRAN (R 4.0.2)
## tidyr * 1.1.2 2020-08-27 [1] CRAN (R 4.0.2)
## tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.2)
## tidyverse * 1.3.0 2019-11-21 [1] CRAN (R 4.0.2)
## utf8 1.1.4 2018-05-24 [1] CRAN (R 4.0.2)
## vctrs 0.3.6 2020-12-17 [1] CRAN (R 4.0.2)
## withr 2.4.1 2021-01-26 [1] CRAN (R 4.0.2)
## xfun 0.21 2021-02-10 [1] CRAN (R 4.0.2)
## xml2 1.3.2 2020-04-23 [1] CRAN (R 4.0.2)
## yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.2)
##
## [1] /Library/Frameworks/R.framework/Versions/4.0/Resources/library
```
Details
Posted on:
March 15, 2021
Length:
4 minute read, 828 words
Categories:
R
Tags:
R
See Also:
Using reactable in #TidyTuesday CHAT dataset - World Energy Production Package: decoupleR
