sine1000 | R Documentation |
Simulated sine and pipe data for calculating optimisation features. Each dataset has 1000 observations and the last two columns contain the intended structure with the rest being noise.
sine1000
sine1000_8d
pipe1000
pipe1000_8d
pipe1000_10d
pipe1000_12d
boa
boa5
boa6
An object of class matrix
(inherits from array
) with 1000 rows and 6 columns.
An object of class matrix
(inherits from array
) with 1000 rows and 8 columns.
An object of class matrix
(inherits from array
) with 1000 rows and 6 columns.
An object of class matrix
(inherits from array
) with 1000 rows and 8 columns.
An object of class matrix
(inherits from array
) with 1000 rows and 10 columns.
An object of class matrix
(inherits from array
) with 1000 rows and 12 columns.
An object of class tbl_df
(inherits from tbl
, data.frame
) with 1000 rows and 10 columns.
An object of class tbl_df
(inherits from tbl
, data.frame
) with 1000 rows and 5 columns.
An object of class tbl_df
(inherits from tbl
, data.frame
) with 1000 rows and 6 columns.
library(ggplot2)
library(tidyr)
library(dplyr)
boa %>%
pivot_longer(cols = x1:x10, names_to = "var", values_to = "value") %>%
mutate(var = forcats::fct_relevel(as.factor(var), paste0("x", 1:10))) %>%
ggplot(aes(x = value)) +
geom_density() +
facet_wrap(vars(var))
sine1000 |> ggplot(aes(x = V5, y = V6)) + geom_point() + theme(aspect.ratio = 1)
pipe1000_8d |> ggplot(aes(x = V5, y = V6)) + geom_point() + theme(aspect.ratio = 1)
pipe1000_8d |> ggplot(aes(x = V7, y = V8)) + geom_point() + theme(aspect.ratio = 1)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.