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app.r
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library(shiny)
library(datasets)
library(ggplot2)
library(dplyr)
library(ISLR)
library(caret)
library(tidyverse)
###################################################################################################
ui <- shinyUI(fluidPage(
## Title
titlePanel("國立台北商業大學 校務永續發展中心"),
## Image
img(src="campus_logo.png", height=80, width=300),
br(),
###################################################################################################
## Tabs
tabsetPanel(
## Tabs panel
tabPanel("Data Information", # Upload File
## Title panel
titlePanel("Uploading Files"),
sidebarLayout(
sidebarPanel(
fileInput('file1', 'Choose CSV File',
accept=c('text/csv',
'text/comma-separated-values,text/plain',
'.csv')),
tags$br(),
## Checking box
checkboxInput('header', 'Header', TRUE),
## Radio Buttons
radioButtons('sep', 'Separator',
c(Comma=',',
Semicolon=';',
Tab='\t'),
','),
## Radio Buttons
radioButtons('quote', 'Quote',
c(None='',
'Double Quote'='"',
'Single Quote'="'"),
'"')
),
## Main Panel
mainPanel(
## Table Out
h4(strong("Observation")),
DT::dataTableOutput("table"),
#tableOutput('contents')
h4(strong("Summary")),
verbatimTextOutput("summary")
)
)
),
###################################################################################################
tabPanel("Data Mining",
h3("Filter"),
sidebarLayout(
sidebarPanel(
fluidRow(column(4, selectInput("fltrCol", "Filter By:", c(""))),
column(4, selectInput("fltrBolean", "Boolean", c("==", "!=", ">", "<"))),
column(4, selectInput("fltrVal", "Value", c(""))
# column(4, uiOutput("COL_VALUE"))
#column(4, textInput(inputId = "inpFilter", label = "Value"))
))
),
mainPanel(
DT::dataTableOutput("Filter")
)),
hr(),
h3("Select"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "selCol",
label = "Select Cloumn",
c(""),
),
# varSelectInput(inputId = "selCol",
# label = "Select Cloumn",
# c(""),
# multiple = TRUE
# ),
),
mainPanel(
DT::dataTableOutput("Select")
)),
hr(),
h3("Arrange"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "Argn",
label = "Arrange By",
choices = "", multiple = TRUE),
),
mainPanel(
DT::dataTableOutput("Arrange")
)),
hr(),
#3
h3("Mutate"),
sidebarLayout(
sidebarPanel(
fluidRow(column(5, textInput(inputId = "mutName", label = "Name")),
#column(4, textInput("mutpick", label=" ", value="=")),
column(2, p("=", style="text-align: center;")), #align="center",
column(5, textInput(inputId = "mutForml", label = "Formula"))
),
actionButton("mutApply", "Apply Mutate",
class="btn-block"),
),
mainPanel(
DT::dataTableOutput("Mutate")
)),
hr(),
#3
h3("Summarise"),
sidebarLayout(
sidebarPanel(
fluidRow(column(5, selectInput(inputId = "sumVal", label = "Value", c(""))),
column(2, p("=", style="text-align: center;")),
column(5, selectInput("sumFunc", "Filter By:", c("Maen"="smrMean",
"Median"="smrMedian",
"Variance"="smrVar",
"Numbers"="smrNum",
"SD"="smrSD",
"IQR"="smrIqr",
"Min"="smrMin",
"Max"="smrMax",
"All"="smrAll")))
)),
mainPanel(
#DT::dataTableOutput("Summarise")
verbatimTextOutput("Summarise")
)),
hr(),
#5
h3("Group-by"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "Grpby", #textInput
label = "Name :",
c("")),
),
mainPanel(
DT::dataTableOutput("Groupby")
)),
hr(),
#3
h3("Rename"),
sidebarLayout(
sidebarPanel(
fluidRow(column(5, selectInput(inputId = "olName", label = "Old Value", c(""))),
column(2, p("=", style="text-align: center;")),
column(5, textInput(inputId = "nwName", label = "New Value"))
),
actionButton("rnmApply", "Apply Change",
class="btn-block"),
),
mainPanel(
DT::dataTableOutput("Rename")
)),
),
###################################################################################################
## Tabs
tabPanel("Data Preprocessing",
titlePanel("Preprocess"),
sidebarLayout(
sidebarPanel(
p(strong("Note:"),textOutput("miss")),
#textOutput("miss"),
######################ALL#########################
tags$strong("Impute Missing Value (whole)"),
tags$br(),
actionButton("avg", "Average/Most Frequent",
#style='padding:5px; font-size:100%',
class="btn-block"),
actionButton("rplc", "Replace with Zero",
class="btn-block"),
actionButton("rmv", "Remove row with missing values",
class="btn-block"),
tags$br(),
tags$strong("Normalize (whole)"),
tags$br(),
actionButton("normlz", "Normalize to interval [0, 1]",
class="btn-block"),
actionButton("std", "Standardize",
class="btn-block"),
####################Partial#####################
tags$br(),
tags$strong("Impute Missing Value (partial)"),
tags$br(),
selectInput(inputId = "imptMissVal",
label = "select column:",
choices = ""),
actionButton("avg_p", "Average/Most Frequent",
#style='padding:5px; font-size:100%',
class="btn-block"),
actionButton("rplc_p", "Replace with Zero",
class="btn-block"),
tags$br(),
tags$strong("Normalize (partial)"),
tags$br(),
selectInput(inputId = "norm_p",
label = "select column:",
choices = ""),
actionButton("normlz_p", "Normalize to interval [0, 1]",
class="btn-block"),
actionButton("std_p", "Standardize",
class="btn-block"),
################## LAST BUTTON ###################
tags$br(),
tags$strong("Data Reset (all)"),
tags$br(),
actionButton("resetData", "Reset Dataset",
class="btn-block"),
),
mainPanel(
#textOutput("miss"),
h4(strong("Observation")),
verbatimTextOutput("datainfo")
)
)
),
###################################################################################################
## Tabs
tabPanel("Statistical Test",
#titlePanel("ANOVA"),
h3("ANOVA"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "anovaX",
label = "Dependent Variable (X) :",
c("")),
selectInput(inputId = "anovaY",
label = "Independent Variable (Y) :",
c("")),
),
mainPanel(
verbatimTextOutput("ANOVArslt")
)
), #<----- here
h3("T-test"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "ttestX",
label = "(X) :",
c("")),
selectInput(inputId = "ttestY",
label = "(Y) :",
c("")),
),
mainPanel(
verbatimTextOutput("ttestRslt")
)
), #<----- here
h3("U-test"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "utestX",
label = "(X) :",
c("")),
selectInput(inputId = "utestY",
label = "(Y) :",
c("")),
),
mainPanel(
verbatimTextOutput("utestRslt")
)
), #<----- here
h3("Paired test"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "PtestX",
label = "(X) :",
c("")),
selectInput(inputId = "PtestY",
label = "(Y) :",
c("")),
),
mainPanel(
verbatimTextOutput("ptRslt")
)
), #<----- here
h3("Chi Squared tests"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "cstestX",
label = "(X) :",
c("")),
selectInput(inputId = "cstestY",
label = "(Y) :",
c("")),
),
mainPanel(
verbatimTextOutput("cstestRslt")
)
), #<----- here
h3("Goodness of Fit test"),
sidebarLayout(
sidebarPanel(
selectInput(inputId = "gftestX",
label = "(X) :",
c("")),
selectInput(inputId = "gftestY",
label = "(Y) :",
c("")),
),
mainPanel(
verbatimTextOutput("gftRslt")
)
), #<----- here
),
# 1.T-test
# 2.U-test
# 3.Paired tests
# 4.Chi Squared tests
# 5.Goodness of Fit test
###################################################################################################
tabPanel("Data Visualization", ## First Type
pageWithSidebar(
headerPanel('Plots'),
sidebarPanel(
#p("Test"),
selectInput(
inputId = "n_var",
label = "How many variable",
choices = c(
"One Variable" = "one_var",
"Two Variable" = "two_var",
"Three Variable" = "three_var"
)
),
##########################################
## one Variable Pick
conditionalPanel(
condition = "input.n_var == 'one_var'",
selectInput(
inputId = "one_var_pick",
label = "Plot Kinds",
choices = c(
"Countinuous" = "conti",
"Discrate" = "disct"
)
)
),
## two Variable Pick
conditionalPanel(
condition = "input.n_var == 'two_var'",
selectInput(
inputId = "two_var_pick",
label = "Plot Kinds",
choices = c(
"Both Continuous" = "both_conti",
"One Discrete, one continuous" = "one_dist_one_conti",
"Both Discrete" = "both_dist",
"Continuous Bivariate distribution" = "conti_bivar_dist",
"Continuous Function" = "conti_func"
)
)
),
## three Variable Pick
conditionalPanel(
condition = "input.n_var == 'three_var'",
selectInput(
inputId = "three_var_pick",
label = "Plot Options",
choices = c("-" = "-",
"Contour" = "geom_contour",
"Contour Filled" = "geom_contour_filled",
"Raster" = "geom_raster",
"Tile" = "geom_tile"
)
)
),
######################
### ONE VAR
## conti Pick
conditionalPanel(
condition = "input.one_var_pick == 'conti' && input.n_var != 'two_var' && input.n_var != 'three_var'",
selectInput(
inputId = "conti_pick",
label = "Plot Options",
choices = c("-" = "-",
"Area Plot" = "geom_area_one",
"Density Plot" = "geom_density",
"Dot Plot" = "geom_dotplot",
"Freqpoly" = "geom_freqpoly",
"Histogram Plot" = "geom_histogram",
"QQ Plot" = "geom_qq"
)
)
),
## disct Pick
conditionalPanel(
condition = "input.one_var_pick == 'disct' && input.n_var != 'two_var' && input.n_var != 'three_var'",
selectInput(
inputId = "disct_pick",
label = "Plot Options",
choices = c("-" = "-",
"Bar Plot" = "geom_bar"
)
)
),
######################
### TWO VAR
## both conti
conditionalPanel(
condition = "input.two_var_pick == 'both_conti' && input.n_var != 'one_var' && input.n_var != 'three_var'",
selectInput(
inputId = "both_conti_pick",
label = "Plot Options",
choices = c("-" = "-",
"Point" = "geom_point",
"Quantile" = "geom_quantile",
"Rug" = "geom_rug",
"Smooth" = "smooth"
)
)
),
## one dist one conti
conditionalPanel(
condition = "input.two_var_pick == 'one_dist_one_conti' && input.n_var != 'one_var' && input.n_var != 'three_var'",
selectInput(
inputId = "one_dist_one_pick",
label = "Plot Options",
choices = c("-" = "-",
"Col" = "geom_col",
"Boxplot" = "geom_boxplot",
"Violin" = "geom_violin"
)
)
),
## both dist
conditionalPanel(
condition = "input.two_var_pick == 'both_dist' && input.n_var != 'one_var' && input.n_var != 'three_var'",
selectInput(
inputId = "both_dist_pick",
label = "Plot Options",
choices = c("-" = "-",
"Count" = "geom_count",
"Jitter" = "geom_jitter"
)
)
),
## conti bivar dist
conditionalPanel(
condition = "input.two_var_pick == 'conti_bivar_dist' && input.n_var != 'one_var' && input.n_var != 'three_var'",
selectInput(
inputId = "conti_bivar_dist_pick",
label = "Plot Options",
choices = c("-" = "-",
"Bin2d" = "geom_bin2d",
"Desity 2d" = "geom_desity_2d"
)
)
),
## conti func
conditionalPanel(
condition = "input.two_var_pick == 'conti_func' && input.n_var != 'one_var' && input.n_var != 'three_var'",
selectInput(
inputId = "conti_func_pick",
label = "Plot Options",
choices = c("-" = "-",
"Area" = "geom_area_two",
"Line" = "geom_line",
"Step" = "geom_step"
)
)
),
######################
## "Empty inputs" - they will be updated after the data is uploaded
## X variable
selectInput('xcol',
'X Variable',
""),
## Y variable
conditionalPanel(
condition = "input.n_var != 'one_var'",
selectInput('ycol',
'Y Variable',
"",
selected = ""
)
),
## Z variable
conditionalPanel(
condition = "input.n_var == 'three_var'",
selectInput('zcol',
'Z Variable',
"",
selected = ""
)
),
## Ymin
conditionalPanel(
condition = "input.n_var == 'two_var' && input.two_var_pick == 'vis_err'",
selectInput('ymin',
'Ymin',
"",
selected = ""
)
),
## Ymax
conditionalPanel(
condition = "input.n_var == 'two_var' && input.two_var_pick == 'vis_err'",
selectInput('ymax',
'Ymax',
"",
selected = ""
)
),
tags$br(),
),
################
mainPanel(
p("Note: the plots only take numeric data!"),
## Plot Out
plotOutput('MyPlot'),
)
)
)
)
)
)
###################################################################################################
server <- shinyServer(function(input, output, session) {
options(shiny.maxRequestSize=30*1024^2)
## added "session" because updateSelectInput requires it
dat <- reactiveVal()
OriginalData <- reactiveVal()
## Initialize the dataset
datainlist <- reactive({
list(input$file1, input$header, input$sep, input$quote)
})
observeEvent(datainlist(), ignoreNULL=T, ignoreInit=T, {
# observeEvent({
inFile <- input$file1
# data <- read.csv(inFile$datapath, header = input$header, sep = input$sep,
# quote = input$quote)
df <- read.csv(inFile$datapath, header = input$header, sep = input$sep,
quote = input$quote)
dat(df)
OriginalData(df)
# For updating the x and y axis feature
updateSelectInput(session, inputId = 'xcol', label = 'X Variable',
choices = names(df), selected = names(df)[1])
updateSelectInput(session, inputId = 'ycol', label = 'Y Variable',
choices = names(df), selected = names(df)[1])
updateSelectInput(session, inputId = 'zcol', label = 'Z Variable',
choices = names(df), selected = names(df)[1])
updateSelectInput(session, inputId = 'ymin', label = 'Ymin',
choices = names(df), selected = names(df)[1])
updateSelectInput(session, inputId = 'ymax', label = 'Ymax',
choices = names(df), selected = names(df)[1])
#choices = names(df), selected = names(df)[2])
noChar <- df[, !sapply(df, is.character)]
updateSelectInput(session, inputId = 'norm_p', label = 'select column:',
choices = names(noChar), selected = names(noChar)[1])
listMiss <- names(which(colSums(is.na(df))>0))
updateSelectInput(session, inputId = 'imptMissVal', label = 'select column:',
choices = listMiss, selected = listMiss[1])
####### Data Mining ####
updateSelectInput(session, inputId = 'fltrCol', label = 'Filter By:',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'selCol', label = 'Select Cloumn',
choices = names(df), selected = names(df)[1])
updateSelectInput(session, inputId = 'Argn', label = 'Arrange By',
choices = names(df), selected = names(df)[1])
updateSelectInput(session, inputId = 'sumVal', label = 'Value',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'Grpby', label = 'Name :',
choices = names(df), selected = names(df)[1])
updateSelectInput(session, inputId = 'olName', label = 'Old Value',
choices = names(df), selected = names(df)[1])
## STATISTICAL TEST
updateSelectInput(session, inputId = 'anovaX', label = 'Dependent Variable (X) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'anovaY', label = 'Independent Variable (Y) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'ttestY', label = '(Y) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'ttestX', label = '(X) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'utestY', label = '(Y) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'utestX', label = '(X) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'PtestY', label = '(Y) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'PtestX', label = '(X) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'cstestY', label = '(Y) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'cstestX', label = '(X) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'gftestY', label = '(Y) :',
choices = names(noChar), selected = names(noChar)[1])
updateSelectInput(session, inputId = 'gftestX', label = '(X) :',
choices = names(noChar), selected = names(noChar)[1])
})
mtydat <- reactive({
return(dat())
})
## Showing Raw Data Summary
output$summary <- renderPrint({
if(is.null(dat())){
return ()
}
summary(dat())
})
##
output$datainfo <- renderPrint({
if(is.null(dat())){
return ()
}
str(dat())
})
## Showing Raw Data Table
output$table <- DT::renderDataTable({
datt <- dat()
tryCatch({
datt
})
return(datt)
})
### Statistical Test ###
output$ANOVArslt <- renderPrint({
if(is.null(dat())){
return ()
}
datt <- dat()
aov.model <- aov(datt[[input$anovaY]] ~ datt[,input$anovaX], data = datt) # Stuck here
br()
print(summary(aov.model))
br()
print(aov.model$coefficients)
})
output$ttestRslt <- renderPrint({
if(is.null(dat())){
return ()
}
datt <- dat()
x <- input$ttestX
y <- input$ttestY
t.test(datt[,x], datt[,y])
})
output$utestRslt <- renderPrint({
if(is.null(dat())){
return ()
}
datt <- dat()
x <- input$utestX
y <- input$utestY
wilcox.test(datt[,x], datt[,y])
})
output$ptRslt <- renderPrint({
if(is.null(dat())){
return ()
}
datt <- dat()
x <- input$PtestX
y <- input$PtestY
t.test(datt[,x], datt[,y], paired = TRUE, var.equal = TRUE)
})
output$cstestRslt <- renderPrint({
if(is.null(dat())){
return ()
}
datt <- dat()
data <- datt[, !sapply(datt, is.character)]
x <- input$cstestX
y <- input$cstestY
csTwo <- chisq.test(datt[,x], datt[,y])
print(csTwo)
print("ALL Columns")
csAll <- chisq.test(data)
csAll
# cs[,x]
})
output$gftRslt <- renderPrint({
if(is.null(dat())){
return ()
}
datt <- dat()
data <- datt[, !sapply(datt, is.character)]
x <- input$gftestX
y <- input$gftestY
gfitTwo <- chisq.test(datt[,x], datt[,y], p = ratio, rescale.p = TRUE)
print(gfitTwo)
print("ALL Columns")
gfitAll <- chisq.test(data, p = ratio, rescale.p = TRUE)
gfitAll
# gfit[,x]
})
########################
## DATA MINING #####
### FILTER ###
observeEvent(input$fltrCol, {
if(is.null(dat())){
return ()
}
datf <- dat()
x <- datf %>% select(!!sym(input$fltrCol))
updateSelectInput(session, inputId = 'fltrVal', label = 'Value',
choices = x, selected = x[1])
})
output$Filter <- DT::renderDataTable({
datt <- dat()
dtPoint <- input$fltrCol
tryCatch({
if (input$fltrBolean=="=="){
datt <- datt[datt[,dtPoint] == input$fltrVal,]
} else if (input$fltrBolean=="!="){
datt <- datt[datt[,dtPoint] != input$fltrVal,]
} else if (input$fltrBolean==">"){
datt <- datt[datt[,dtPoint] > input$fltrVal,]
} else if (input$fltrBolean=="<"){
datt <- datt[datt[,dtPoint] < input$fltrVal,]
}
})
return(datt)
})
### FILTER ###
### SELECT ###
output$Select <- DT::renderDataTable({
datt <- dat()
dtPoint <- input$selCol
DT::datatable(datt[, dtPoint, drop = FALSE])
})
### SELECT ###
### ARRANGE ###
output$Arrange <- DT::renderDataTable({
if(is.null(dat())){
return ()
}
datt <- dat()
dtPoint <- input$Argn
DT::datatable(datt %>% arrange(datt[,dtPoint]))
})
### ARRANGE ###
####MUTATE ####
observeEvent(input$mutApply,{ #HERE
datt <- dat()
colnam <- input$mutName
forml <- input$mutForml
DATT <- "datt"
COLNAM <- "colnam"
FORML <- "forml"
output$Mutate <- DT::renderDataTable({
datUpdate <- eval(parse(text = paste0(DATT, "%>% mutate(", eval(parse(text = COLNAM)), "=", eval(parse(text = FORML)),")")))
DT::datatable(datUpdate)
#dat(datUpdate)
})
})
####MUTATE ####
### SUMMARISE ###
output$Summarise <- renderPrint({
if(is.null(dat())){
return ()
}
datt <- dat()
datt <- na.omit(datt)
#tryCatch({
if (input$sumFunc=='smrMean'){
datt %>% summarise_at(input$sumVal, mean)
} else if (input$sumFunc=='smrMedian') {
datt %>% summarise_at(input$sumVal, median)
} else if (input$sumFunc=='smrVar') {
datt %>% summarise_at(input$sumVal, var)
} else if (input$sumFunc=='smrNum') {
datt %>% summarise_at(input$sumVal, length)
} else if (input$sumFunc=='smrSD') {
datt %>% summarise_at(input$sumVal, sd)
} else if (input$sumFunc=='smrIqr') {
datt %>% summarise_at(input$sumVal, IQR)
} else if (input$sumFunc=='smrMin') {
datt %>% summarise_at(input$sumVal, min)
} else if (input$sumFunc=='smrMax') {
datt %>% summarise_at(input$sumVal, max)
} else if (input$sumFunc=='smrAll') {
dtpoint <- input$sumVal
summary(datt[,dtpoint])
}
})
### SUMMARISE ###
####GROUP BY ####
output$Groupby <- DT::renderDataTable({
if(is.null(dat())){
return ()
}
datt <- dat()
dtPoint <- input$Grpby
datt %>% group_by(datt[,dtPoint])
})
####GROUP BY ####
#### RENAME ####
observeEvent(input$rnmApply, { #HERE
datt <- dat()
ol <- input$olName
nw <- input$nwName
DATT <- "datt"
OL <- "ol"
NW <- "nw"
output$Rename <- DT::renderDataTable({
datUpd <- eval(parse(text = paste0(DATT, "%>% rename(", eval(parse(text = NW) ), "=", eval(parse(text = OL)),")")))
DT::datatable(datUpd)
#dat(datUpd)
})
})
#### RENAME ####
####################
### Impute Missing Value
observeEvent(input$rmv, {
dataUpdate <- dat()
dataUpdate <- na.omit(dataUpdate)
dat(dataUpdate)
print(typeof(dataUpdate))
})
observeEvent(input$rplc, {
dataUpdate <- dat()
dataUpdate[is.na(dataUpdate)] <- 0
dat(dataUpdate)
})
observeEvent(input$avg, {
dataUpdate <- dat()
for (i in 1:ncol(dataUpdate)){
dataUpdate[is.na(dataUpdate[,i]), i] <- mean(dataUpdate[, i], na.rm=T)
}
dat(dataUpdate)
})
### Normalize
observeEvent(input$std, {
dataUpdate <- dat()
rmchar <- dataUpdate[, !sapply(dataUpdate, is.character)]
scl <- scale(rmchar)
scl <- data.frame(scl)
colnm <- colnames(scl)
dataUpdate[colnm] <- scl[colnm]
dat(dataUpdate)
})
observeEvent(input$normlz, {
dataUpdate <- dat()
rmchar <- dataUpdate[, !sapply(dataUpdate, is.character)]
process <- preProcess(as.data.frame(rmchar), method=c("range"))
norm_scale <- predict(process, as.data.frame(rmchar))
colnm <- colnames(norm_scale)
dataUpdate[colnm] <- norm_scale[colnm]
dat(dataUpdate)
})
observeEvent(input$resetData, {
# for resetting the dataset
dat(OriginalData())
})
output$miss <- renderText({
valcnt <- sum(is.na(dat()))
paste0("total missing value: ", valcnt)
})
observeEvent(input$avg_p, {
dataUpdate <- dat()
df1 <- na.omit(dataUpdate)
ft <- input$imptMissVal
avg <- mean(df1[,ft])
dataUpdate[,ft][is.na(dataUpdate[,ft])] <- avg
dat(dataUpdate)
})
observeEvent(input$rplc_p, {
dataUpdate <- dat()
ft <- input$imptMissVal
dataUpdate[,ft][is.na(dataUpdate[,ft])] <- 0
dat(dataUpdate)
})
observeEvent(input$normlz_p, {
dataUpdate <- dat()
ft <- input$norm_p
dataPoint <- dataUpdate[,ft]
process <- preProcess(as.data.frame(dataPoint), method=c("range"))
norm_scale <- predict(process, as.data.frame(dataPoint))
dataUpdate[,ft] <- norm_scale
dat(dataUpdate)
})
observeEvent(input$std_p, {
dataUpdate <- dat()
ft <- input$norm_p
dataUpdate[,ft] <- scale(dataUpdate[,ft])
dat(dataUpdate)
})
## For Plotting
output$MyPlot <- renderPlot({
### Important for updating the layout
### we need to reinitialize the dataset
datt <- dat()[, c(input$xcol, input$ycol, input$zcol)]
### ONE VARIABLE
## conti
conti <- input$conti_pick
disct <- input$disct_pick
if (input$n_var=="one_var"&&input$one_var_pick=="conti"){
if (conti=="geom_histogram"){ # geom_histogram
ggplot(datt, aes_string(x=input$xcol))+geom_histogram(colour='darkblue')
} else if (conti=="geom_density"){ # geom_density
ggplot(datt, aes_string(x=input$xcol))+geom_density(colour='darkblue')
} else if (conti=="geom_area_one") { # geom_area_one
ggplot(datt, aes_string(x=input$xcol))+geom_area(stat="bin")
} else if (conti=="geom_dotplot") { # geom_dotplot
ggplot(datt, aes_string(x=input$xcol))+geom_dotplot()
} else if (conti=="geom_freqpoly") { # geom_freqpoly
ggplot(datt, aes_string(x=input$xcol))+geom_freqpoly()
} else if (conti=="geom_qq") { # geom_qq
ggplot(datt, aes_string(sample=input$xcol))+stat_qq()
}
} else if (input$n_var=="one_var"&&input$one_var_pick=="disct") {
if (disct=="geom_bar"){ ## disct # geom_bar
ggplot(datt, aes_string(x=input$xcol))+geom_bar()
}
} else if (input$n_var=="two_var"&&input$two_var_pick=="both_conti"){
if (input$both_conti_pick=="geom_point"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_point(colour='darkblue')
} else if (input$both_conti_pick=="geom_quantile") {
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_quantile()
} else if (input$both_conti_pick=="geom_rug"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_rug(sides = "bl")
} else if (input$both_conti_pick=="smooth"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_smooth()
}
} else if (input$n_var=="two_var"&&input$two_var_pick=="one_dist_one_conti"){
if (input$one_dist_one_pick=="geom_boxplot"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_boxplot()
} else if (input$one_dist_one_pick=="geom_violin"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_violin()
} else if (input$one_dist_one_pick=="geom_col"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_col()
}
} else if (input$n_var=="two_var"&&input$two_var_pick=="both_dist"){
if (input$both_dist_pick=="geom_count"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_count()
} else if (input$both_dist_pick=="geom_jitter"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_jitter()
}
} else if (input$n_var=="two_var"&&input$two_var_pick=="conti_bivar_dist"){
if (input$conti_bivar_dist_pick=="geom_bin2d"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_bin_2d()
} else if (input$conti_bivar_dist_pick=="geom_desity_2d"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_density_2d()
}
} else if (input$n_var=="two_var"&&input$two_var_pick=="conti_func"){
if (input$conti_func_pick=="geom_area_two"){
ggplot(datt, aes_string(x=input$xcol, y=input$ycol))+geom_area()