Good Afternoon dear all,
Please considering this data, I will like to know the best way to check for outliers in a scatter plot without using the ggplotly function from plotly. Thanks
Load Required Packages
library(tidyverse)
library(ggpmisc)
library(plotly)
library(ggrepel)
Load the Data
LeafArea <- tibble::tribble(
~Planting, ~Variety, ~Inoculation, ~Fertilizer, ~Plant, ~leaf, ~mid.lobe.length, ~mid.lobe.width,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 1L, 1L, 15.4, 4.6,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 1L, 2L, 12.3, 3.7,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 2L, 1L, 15.6, 4.7,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 2L, 2L, 18, 6.5,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 3L, 3L, 44, 6.7,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 3L, 4L, 17.1, 6.7,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 4L, 3L, 14.9, 6.9,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 4L, 4L, 21.5, 7.2,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 5L, 5L, 20.2, 7.1,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 5L, 6L, 21.5, 6.7,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 6L, 5L, 22.5, 7.7,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 6L, 6L, 18.7, 6.5,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 7L, 7L, 17.2, 6.7,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 7L, 8L, 20.8, 6.4,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 8L, 7L, 60, 18,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 8L, 8L, 18, 7.1,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 9L, 9L, 16, 6.2,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 9L, 10L, 15.5, 4.7,
"May", "TME 419", "No", "0 kg P2O5 ha-1", 10L, 9L, 11.8, 3.4
)
Plot
p1 <- ggplot(data = LeafArea, aes(x = mid.lobe.length,y = mid.lobe.width)) +
stat_poly_line(fullrange = T) +
stat_poly_eq(use_label(c("eq","R2","P"))) +
#stat_poly_eq(label.y = 0.8)+
geom_point()+
labs(y='Actual Mid-lobe Width (cm)',x='Mid Lobe Length (cm)')+
#coord_cartesian(xlim = c(0,1),)+
theme_test()
p1
Checking for Outliers
ggplotly(p1)