In pratheesh3780/grapesAgri1: Collection of Shiny Apps for Agricultural Research Data Analysis
knitr::opts_chunk$set(echo = TRUE)
library(shiny)
library(ggplot2)
library(Hmisc)
library(agricolae)
library(shinyWidgets)
library(shinycssloaders)
library(dplyr)
library(gtools)
library(knitr)
library(kableExtra)
library(magrittr)
RESULT
RBD ANALYSIS
csvfile <- reactive({
csvfile <- input$file1
if (is.null(csvfile)) {
return(NULL)
}
dt <- read.csv(csvfile$datapath, header = input$header, sep = ",")
dt
})
if (input$submit > 0) {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
out <- agricolae::LSD.test(csvfile()[, input$yield], csvfile()[, input$treatment], result[3, 1], result[3, 3])
trtmeans <- out$means
trtmeans <- trtmeans[ gtools::mixedsort(row.names(trtmeans)), ]
colnames(trtmeans)[1] <- "Treatment_means"
drops <- c("r", "Q25", "Q50", "Q75","se")
trtmeans <- trtmeans[, !(names(trtmeans) %in% drops)]
kable(trtmeans, caption = "Treatment mean and other statistics", digits = 3, align = "c", row.names = TRUE) %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
tags$br()
################ anova table
if (input$submit > 0) {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
SoV <- c("Treatment", "Replication", "Error")
final <- cbind(SoV, result)
kable(final, caption = "ANOVA TABLE", digits = 3, align = "c", row.names = FALSE) %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
tags$br()
############################################## SEM
if (input$submit > 0) {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
out <- LSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3])
colnam <- c("MSE", "SE(d)", "SE(m)", "CV")
stat <- out$statistics
MSE <- stat[1, 1]
SED <- sqrt((2 * MSE) / r)
SEM <- sqrt(MSE / r)
CV <- stat[1, 4]
Result <- cbind(MSE, SED, SEM, CV)
colnames(Result) <- colnam
kable(Result, caption = "SEM & Other statistics", digits = 3, align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
tags$br()
if (input$submit > 0) {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
if (result[1, 5] <= 0.05) {
cat("Since the P-value in ANOVA table is < 0.05,\nthere is a significant difference between atleast a pair of treatments,\nso multiple comparison is required to identify best treatment(s)")
}
if (result[1, 5] > 0.05) {
cat("Treatment means are not significantly different")
}
}
############################### CD and measures
tags$br()
if (input$submit > 0) {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
if (result[1, 5] > 0.05) {
return()
}
else if (input$req == "lsd") {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
out <- agricolae::LSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3])
colnam <- c("MSE", "SE(d)", "SE(m)", "CD", "t value", "CV")
stat <- out$statistics
MSE <- stat[1, 1]
SED <- sqrt((2 * MSE) / r)
SEM <- sqrt(MSE / r)
CD <- stat[1, 6]
t <- stat[1, 5]
CV <- stat[1, 4]
Result <- cbind(MSE, SED, SEM, CD, t, CV)
colnames(Result) <- colnam
kable(Result, caption = "LSD test", digits = 3, align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
else if (input$req == "dmrt") {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
out <- agricolae::duncan.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3], alpha = 0.05, group = TRUE, main = NULL, console = FALSE)
Result <- out$duncan
kable(Result, caption = "DMRT", digits = 3, align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
else if (input$req == "tukey") {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
out <- agricolae::HSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3], alpha = 0.05, group = TRUE, main = NULL, unbalanced = FALSE, console = FALSE)
Result <- out$statistics
kable(Result, caption = "Tukey's HSD", digits = 3, align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
}
tags$br()
########################################### grouping
if (input$submit > 0) {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
if (result[1, 5] > 0.05) {
return()
}
else if (input$req == "lsd") {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
out <- agricolae::LSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3])
outgroup <- out$groups
colnames(outgroup) <- c("trt_mean", "grouping")
kable(outgroup, caption = "Treatment Grouping", align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
else if (input$req == "dmrt") {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
out <- agricolae::duncan.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3], alpha = 0.05, group = TRUE, main = NULL, console = FALSE)
outgroup <- out$groups
colnames(outgroup) <- c("trt_mean", "grouping")
kable(outgroup, caption = "Treatment Grouping", align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
else if (input$req == "tukey") {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
out <- agricolae::HSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3], alpha = 0.05, group = TRUE, main = NULL, unbalanced = FALSE, console = FALSE)
outgroup <- out$groups
colnames(outgroup) <- c("trt_mean", "grouping")
kable(outgroup, caption = "Treatment Grouping", align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F)
}
}
############
if (input$submit > 0) {
d <- as.data.frame(csvfile())
r <- as.numeric(input$rep)
t <- as.numeric(input$trt)
response <- d[, input$yield]
treatment <- d[, input$treatment]
replication <- d[, input$Replication]
treatment <- factor(treatment)
replication <- factor(replication)
anvaTable <- lm(response ~ treatment + replication)
result <- as.data.frame(anova(anvaTable))
if (result[1, 5] > 0.05) {
return("")
}
if (input$req == "tukey" || input$req == "dmrt" || input$req == "lsd") {
cat("Treatments with same letters are not significantly different")
}
}
tags$br()
tags$br()
Report generated from: Package: grapesAgri1, Version 1.0.0
pratheesh3780/grapesAgri1 documentation built on Dec. 7, 2023, 5:49 a.m.
R Package Documentation
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knitr::opts_chunk$set(echo = TRUE) library(shiny) library(ggplot2) library(Hmisc) library(agricolae) library(shinyWidgets) library(shinycssloaders) library(dplyr) library(gtools) library(knitr) library(kableExtra) library(magrittr)
RESULT
RBD ANALYSIS
csvfile <- reactive({ csvfile <- input$file1 if (is.null(csvfile)) { return(NULL) } dt <- read.csv(csvfile$datapath, header = input$header, sep = ",") dt }) if (input$submit > 0) { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) out <- agricolae::LSD.test(csvfile()[, input$yield], csvfile()[, input$treatment], result[3, 1], result[3, 3]) trtmeans <- out$means trtmeans <- trtmeans[ gtools::mixedsort(row.names(trtmeans)), ] colnames(trtmeans)[1] <- "Treatment_means" drops <- c("r", "Q25", "Q50", "Q75","se") trtmeans <- trtmeans[, !(names(trtmeans) %in% drops)] kable(trtmeans, caption = "Treatment mean and other statistics", digits = 3, align = "c", row.names = TRUE) %>% kable_styling() %>% kable_paper("hover", full_width = F) } tags$br() ################ anova table if (input$submit > 0) { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) SoV <- c("Treatment", "Replication", "Error") final <- cbind(SoV, result) kable(final, caption = "ANOVA TABLE", digits = 3, align = "c", row.names = FALSE) %>% kable_styling() %>% kable_paper("hover", full_width = F) } tags$br() ############################################## SEM if (input$submit > 0) { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) out <- LSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3]) colnam <- c("MSE", "SE(d)", "SE(m)", "CV") stat <- out$statistics MSE <- stat[1, 1] SED <- sqrt((2 * MSE) / r) SEM <- sqrt(MSE / r) CV <- stat[1, 4] Result <- cbind(MSE, SED, SEM, CV) colnames(Result) <- colnam kable(Result, caption = "SEM & Other statistics", digits = 3, align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F) } tags$br() if (input$submit > 0) { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) if (result[1, 5] <= 0.05) { cat("Since the P-value in ANOVA table is < 0.05,\nthere is a significant difference between atleast a pair of treatments,\nso multiple comparison is required to identify best treatment(s)") } if (result[1, 5] > 0.05) { cat("Treatment means are not significantly different") } } ############################### CD and measures tags$br() if (input$submit > 0) { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) if (result[1, 5] > 0.05) { return() } else if (input$req == "lsd") { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) out <- agricolae::LSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3]) colnam <- c("MSE", "SE(d)", "SE(m)", "CD", "t value", "CV") stat <- out$statistics MSE <- stat[1, 1] SED <- sqrt((2 * MSE) / r) SEM <- sqrt(MSE / r) CD <- stat[1, 6] t <- stat[1, 5] CV <- stat[1, 4] Result <- cbind(MSE, SED, SEM, CD, t, CV) colnames(Result) <- colnam kable(Result, caption = "LSD test", digits = 3, align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F) } else if (input$req == "dmrt") { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) out <- agricolae::duncan.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3], alpha = 0.05, group = TRUE, main = NULL, console = FALSE) Result <- out$duncan kable(Result, caption = "DMRT", digits = 3, align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F) } else if (input$req == "tukey") { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) out <- agricolae::HSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3], alpha = 0.05, group = TRUE, main = NULL, unbalanced = FALSE, console = FALSE) Result <- out$statistics kable(Result, caption = "Tukey's HSD", digits = 3, align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F) } } tags$br() ########################################### grouping if (input$submit > 0) { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) if (result[1, 5] > 0.05) { return() } else if (input$req == "lsd") { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) out <- agricolae::LSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3]) outgroup <- out$groups colnames(outgroup) <- c("trt_mean", "grouping") kable(outgroup, caption = "Treatment Grouping", align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F) } else if (input$req == "dmrt") { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) out <- agricolae::duncan.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3], alpha = 0.05, group = TRUE, main = NULL, console = FALSE) outgroup <- out$groups colnames(outgroup) <- c("trt_mean", "grouping") kable(outgroup, caption = "Treatment Grouping", align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F) } else if (input$req == "tukey") { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) out <- agricolae::HSD.test(d[, input$yield], d[, input$treatment], result[3, 1], result[3, 3], alpha = 0.05, group = TRUE, main = NULL, unbalanced = FALSE, console = FALSE) outgroup <- out$groups colnames(outgroup) <- c("trt_mean", "grouping") kable(outgroup, caption = "Treatment Grouping", align = "c") %>% kable_styling() %>% kable_paper("hover", full_width = F) } } ############ if (input$submit > 0) { d <- as.data.frame(csvfile()) r <- as.numeric(input$rep) t <- as.numeric(input$trt) response <- d[, input$yield] treatment <- d[, input$treatment] replication <- d[, input$Replication] treatment <- factor(treatment) replication <- factor(replication) anvaTable <- lm(response ~ treatment + replication) result <- as.data.frame(anova(anvaTable)) if (result[1, 5] > 0.05) { return("") } if (input$req == "tukey" || input$req == "dmrt" || input$req == "lsd") { cat("Treatments with same letters are not significantly different") } } tags$br() tags$br()
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