library(dplyr) library(ggplot2) library(tidyverse)

library(data.table) library(readxl) library(compare)

CCB <- fread("Point.csv", sep = ";", dec = ",", stringsAsFactors = FALSE)

View(CCB)

env <- read_excel("Data_Env.xlsx", col_names = TRUE)

ccb1 <- merge(CCB, env, by = "Plot_ID", all = TRUE) # Replace "ID" with the actual common column name view(ccb1)

#data kehadiran biodiversity pada setiap plot

bio<- fread("bio.csv",sep=";",dec=",",stringsAsFactors = FALSE) view(bio)

bio1<-bio%>% select(1:4)

view(bio1)

#Clean the data and correction(Manipulating)

ccb2<-merge(ccb1, bio1, by = "Plot_ID", all = TRUE) view(ccb2)

#explorasi data cor1<-cor(ccb2[,5:21]) print(cor1) plot(cor1)

install.packages("corrplot") library(corrplot) corrplot(cor(cor1))

summary(ccb2)

plot(ccb2$Water_Temperature,ccb2$n_zooplankton) plot(ccb2$DO,ccb2$n_zooplankton)

#hw <- heightweight %>%

ggplot(ccb2, aes(x =n_zooplankton, y = Water_Temperature , shape = Note)) + geom_point(size = 2.5)

ggplot(ccb2, aes(x = Water_Temperature, y = n_fitoplankton , shape = Note)) + geom_point(size = 2.5)

#boxplot

ggplot(ccb2, aes(x = Water_Temperature, y = n_zooplankton, color = Note)) + geom_boxplot()

ggplot(ccb2, aes(x = Water_Temperature, y = n_fitoplankton, color = Note)) + geom_boxplot()

a<-ggplot(ccb1, aes(x = DO , y = Water_Temperature)) + geom_point() + labs(title = "Plot of Water Temperature vs. DO")

a1 <- a + geom_smooth(method = "lm", formula = y ~ x, se = FALSE) + annotate("text", x = min(ccb2$DO), y = max(ccb1$Water_Temperature), label = paste("Correlation Coefficient (r) =", round(cor(ccb1$DO, ccb1$Water_Temperature), 3)), hjust = 0, vjust = 1)

a1