Iris dataset

By Jesús Vélez Santiago in R

March 15, 2021

Load libraries

library(tidyverse)
library(janitor)

Iris dataset

iris %>%
    glimpse()
## 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…

Clean and transform to tidy format

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

theme_set(theme_bw())

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:
Package: decoupleR