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library(dplyr) library(ggplot2) library(cluster) library(factoextra) library(rpart) library(rpart.plot) library(caret)
set.seed(123) data(“CO2”)
head(CO2) summary(CO2) str(CO2) CO2_prep <- CO2 %>% mutate( Treatment = as.numeric(Treatment), Type = as.numeric(Type), Plant = as.numeric(Plant) )
sum(is.na(CO2_prep))
CO2_prep <- CO2 %>% mutate( Treatment = as.numeric(Treatment), Type = as.numeric(Type), Plant = as.numeric(Plant) )
sum(is.na(CO2_prep))
ggplot(CO2, aes(x = conc, y = uptake, color = Type)) + geom_point(size = 3) + geom_smooth(method = “lm”, se = FALSE) + labs(title = “CO2 Uptake vs Concentration by Type”, x = “CO2 Concentration”, y = “CO2 Uptake”) + theme_minimal()