NEW

# === STEP 1: Install and Load Required Libraries ===
# Uncomment these if not already installed
# install.packages("openxlsx")
# install.packages("plotly")
# install.packages("ggplot2")

library(openxlsx)

## Warning: package 'openxlsx' was built under R version 4.3.3

library(ggplot2)
library(plotly)

## Warning: package 'plotly' was built under R version 4.3.3

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

library(magrittr)

# Load Excel data
ftir <- read.xlsx("C:/Users/Administrator/Desktop/ANALYSIS with R/Final 1.xlsx", 
                  sheet = 1, 
                  colNames = TRUE, 
                  rowNames = TRUE)

# Convert Group column to factor
ftir$Group <- as.factor(ftir$Group)

# Create ftir_data excluding the Group column
ftir_data <- ftir[, !names(ftir) %in% "Group"]

# Run PCA
pca_ftir <- prcomp(ftir_data, scale. = TRUE)

# Combine PCA results with group info
scores_pca <- cbind.data.frame(pca_ftir$x[, 1:3], Group = ftir$Group)

# Create 3D plot
plot_ly(
  data = scores_pca,
  x = ~PC1, y = ~PC2, z = ~PC3,
  color = ~Group,
  text = rownames(scores_pca),
  marker = list(size = 6)
) %>%
  layout(
    scene = list(
      xaxis = list(title = "PC1 (58.9%)"),
      yaxis = list(title = "PC2 (15.1%)"),
      zaxis = list(title = "PC3 (13.1%)")
    )
  )

## No trace type specified:
##   Based on info supplied, a 'scatter3d' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter3d

## No scatter3d mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode