inst/server.R
In Kafi1993/Explore: Explore
# server.R
library(shiny)
library(ggplot2)
library(psych)
library(colourpicker)
source("helpers.R")
shinyServer(function(input, output, session) {
# **********************************************************************************************
# Read in datafile =============================================================================
uploadData <- reactive({
inFile <- input$inFile
read.csv(inFile$datapath, header = input$head, sep = input$sep, stringsAsFactors = input$sASf,
quote = input$quote, dec = input$dec, na.strings = input$miss)
})
# **********************************************************************************************
# Showing uploadData =================================================================================
output$datatable <- renderDataTable({
validate(
need(input$inFile != "", "Please load a data set")
)
uploadData()
})
# **********************************************************************************************
# Descriptives Table ============================================================================
output$summary <- renderDataTable({
validate(
need(input$inFile != "", "Please load a data set")
)
list <- getDescriptives(uploadData())
df <- data.frame("Item" = names(list$mean),"Mean" = list$mean, "SD" = list$sd,"Median" = list$median, "Min" = list$min,
"Max" = list$max, "Skew" = list$skew, "Kurtosis" = list$kurtosis ,"Missings" = list$na)
})
# **********************************************************************************************
# Graphics All Items ============================================================================
numData <- reactive({
extractNumeric(uploadData())
})
# Vector containing Item names
RangeChoice <- reactive({
colNum <- 1:ncol(numData())
names(colNum) <- names(numData())
colNum
})
### Dynamic Column Range Panels
output$RangeColSelect1 <- renderUI({
validate(
need(input$inFile != "", "Please load a data set")
)
selectInput("ColRange1", "Show Variables from:", choices = c("", RangeChoice()))
})
output$RangeColSelect2 <- renderUI({
validate(
need(input$inFile != "", " ")
)
selectInput("ColRange2", "to:", choices = c("", RangeChoice()))
})
### Dynamic Plot Setting Panel (for vertical bars)
output$VerticalSettings <- renderUI({
radioButtons("VerticalType", "Should bars be grouped or stacked?", choices = c("Grouped bars", "Stacked bars"))
})
### Subset uploadData with selected Columns
dataForGraph <- reactive({
minC <- as.integer(input$ColRange1)
maxC <- as.integer(input$ColRange2)
numData()[minC:maxC]
})
### Dimensions of Plot for plotOutput
PlotAllDims <- reactive({
c(as.numeric(input$PlotAllHeight), as.numeric(input$PlotAllWidth))
})
observe({
input$SizeReset
updateTextInput(session, "PlotAllHeight", value = "400")
updateTextInput(session, "PlotAllWidth", value = "1600")
})
### Outout
observe(
output$plotAll <- renderPlot({
if (is.null(input$inFile))
return(NULL)
validate(
need(input$ColRange1, "Please choose a lower bound of columns to display"),
need(input$ColRange2, "Please choose an upper bound of columns to display")
)
# Some parameters
col_n <- as.integer(input$ColRange2) # Number of allowed columns
if (input$Rev_Col) ColDir <- -1 else ColDir <- 1 # Direction of color palette
# Horizontal Bars
if (input$PlotOrient == "horizontal") {
if(input$Unit_PlotAll_horiz) FreqType <- position_stack else FreqType <- position_fill
stackedBars(dataForGraph(), type = FreqType, n.col = col_n, palette = input$Col_PlotAll,
direction = ColDir)
# Vertical Bars
} else {
if(input$VerticalType == "Stacked bars" && input$Unit_PlotAll_vert) FreqType <- position_stack()
else if (input$VerticalType == "Stacked bars") FreqType <- position_fill()
else if (input$VerticalType == "Grouped bars") FreqType <- position_dodge()
parallelBars(dataForGraph(), position = FreqType, n.col = col_n, palette = input$Col_PlotAll,
direction = ColDir)
}
}, height = PlotAllDims()[1], width = PlotAllDims()[2]
)
)
# **********************************************************************************************
# Graphics Single Items =========================================================================
## Select Items ----------------------------
### Choices for Item Select Menu
columnChoice <- reactive({
colNum <- 1:ncol(uploadData())
names(colNum) <- names(uploadData())
})
### Dynamic Item Select Panel 1
output$ItemSelect1 <- renderUI({
validate(
need(input$inFile != "", "Please load a data set")
)
selectInput("PlotVar1", "Choose a variable to display", choices = c(Choose = "", columnChoice()))
})
### Dynamic Item Select Panel 2
output$ItemSelect2 <- renderUI({
validate(
need(input$inFile != "", "Please load a data set")
)
selectInput("PlotVar2", "Choose a variable to display", choices = c(Choose = "", columnChoice()))
})
## Dynamic Options for different PlotTypes ---------------------------
### Dynamic Plot Type Panels 1 ----------------
#### For Histogram
output$hist1Breaks <- renderUI({
validate(
need(input$PlotVar1, "Please select a variable to show all options")
)
if (input$Package1) {
numericInput("binwidth_Hist1", "Width of bars:",
value = 1, min = 0, step = .1)
} else
numericInput("Breaks_Hist1", "Number of breaks:",
value = nclass.Sturges(uploadData()[[input$PlotVar1]]), min = 1)
})
#### For Scatterplot
# None
### For Boxplot
output$viewMeanSpecs1_1 <- renderUI({
if(input$showMean1) {
colourInput("Col_BoxMean1", "Choose a color", value = "red")
} else return(NULL)
})
output$viewMeanSpecs1_2 <- renderUI({
if(input$showMean1) {
numericInput("Box_pShape1", "Change shape of points (from R graphics)", value = 15, min = 0, max = 25)
} else return(NULL)
})
### Dynamic Plot Type Panels 2 ---------------
#### For Histogram
output$hist2Breaks <- renderUI({
validate(
need(input$PlotVar2, "Please select a variable to show all options")
)
if (input$Package2) {
numericInput("binwidth_Hist2", "Width of bars:",
value = 1, min = 0, step = .1)
} else
numericInput("Breaks_Hist2", "Number of breaks:",
value = nclass.Sturges(uploadData()[[input$PlotVar2]]), min = 1)
})
#### For Scatterplot
# None
### For Boxplot
output$viewMeanSpecs2_1 <- renderUI({
if(input$showMean2) {
colourInput("Col_BoxMean2", "Choose a color", value = "red")
} else return(NULL)
})
output$viewMeanSpecs2_2 <- renderUI({
if(input$showMean2) {
numericInput("Box_pShape2", "Change shape of points (from R graphics)", value = 15, min = 0, max = 25)
} else return(NULL)
})
## Create Plots =========================================================
### Some Specs for adding mean to Boxplot
showMean <- reactive({
c(input$showMean1, input$showMean2)
})
horiz <- reactive({
c(input$horiz1, input$horiz2)
})
### Define uploadData to plot for R base
plotData1 <- reactive({
uploadData()[[input$PlotVar1]]
})
plotData2 <- reactive({
uploadData()[[input$PlotVar2]]
})
### Plot 1 ------------------------------------------------------------------
output$dataPlot1 <- renderPlot({
if (is.null(input$inFile))
return(NULL)
validate(
need(input$PlotVar1, "Please select a variable to plot")
)
# R base Graphics ----------------------
if (input$Package1 == FALSE){
# Histogram -------------
if (input$PlotType1 == "hist") {
hist(plotData1(), main = paste("Histogram of Variable", input$PlotVar1), freq = input$Unit_Hist1,
xlab = input$PlotVar1, col = input$Col_Hist1, breaks = input$Breaks_Hist1)
# Scatterplot -------------------
} else if (input$PlotType1 == "scatter") {
# Jittered uploadData?
if (input$jitter1 == FALSE) {
plot(plotData1(), main = paste("Scatterplot of Variable", input$PlotVar1), pch = input$pShape1,
ylab = input$PlotVar1, col = input$Col_Scatter1)
} else {
plot(jitter(plotData1()), main = paste("Scatterplot of Variable", input$PlotVar1), pch = input$pShape1,
ylab = input$PlotVar1, col = input$Col_Scatter1)
}
# Boxplot -------------------
} else if (input$PlotType1 == "box") {
# Add mean?
if (showMean()[1] == TRUE) {
boxplot(plotData1(), main = paste("Scatterplot of Variable", input$PlotVar1),
xlab = input$PlotVar1, col = input$Col_Box1,
notch = input$notched1, horizontal = input$horiz1)
if (horiz()[1] == TRUE) {
points(mean(plotData1()), y = 1, col = input$Col_BoxMean1, pch = input$Box_pShape1, cex = 1.5)
} else {
points(mean(plotData1()), col = input$Col_BoxMean1, pch = input$Box_pShape1, cex = 1.5)
}
} else {
boxplot(plotData1(), main = paste("Scatterplot of Variable", input$PlotVar1),
xlab = input$PlotVar1, col = input$Col_Box1,
notch = input$notched1, horizontal = input$horiz1)
}
}
# ggplot 2 Graphics --------------------
} else if (input$Package1 == TRUE) {
# Histogram -------------
if (input$PlotType1 == "hist") {
# Plot frequency
if (input$Unit_Hist1 == TRUE) {
ggplot(data = uploadData(), aes(x = uploadData()[[input$PlotVar1]])) +
geom_histogram(binwidth = input$binwidth_Hist1, fill = input$Col_Hist1) +
xlab(input$PlotVar1) + ggtitle(paste("Histogram of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
# Plot density
} else {
ggplot(data = uploadData(), aes(x = uploadData()[[input$PlotVar1]])) +
geom_histogram(aes( y = ..density..), binwidth = input$binwidth_Hist1, fill = input$Col_Hist1) +
xlab(input$PlotVar1) + ggtitle(paste("Histogram of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
# Scatterplot ---------------------
} else if (input$PlotType1 == "scatter") {
# Jittered uploadData?
if (input$jitter1 == FALSE) {
ggplot(data = uploadData(), aes(y = seq(1,length(uploadData()[[input$PlotVar1]])), x = uploadData()[[input$PlotVar1]])) +
geom_point(color = input$Col_Scatter1, shape = input$pShape1) +
xlab(input$PlotVar1) + ylab("Index") + ggtitle(paste("Scatterplot of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
} else {
ggplot(data = uploadData(), aes(y = seq(1,length(uploadData()[[input$PlotVar1]])), x = uploadData()[[input$PlotVar1]])) +
geom_jitter(color = input$Col_Scatter1, shape = input$pShape1) +
xlab(input$PlotVar1) + ylab("Index") + ggtitle(paste("Scatterplot of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
# Boxplot -------------------
} else if (input$PlotType1 == "box") {
# Add mean?
if (showMean()[1] == TRUE) {
ggBoxplot1 <- ggplot(uploadData(), aes(x = "", y = uploadData()[[input$PlotVar1]])) +
geom_boxplot(fill = input$Col_Box1, notch = input$notched1, width = .3) +
ylab(input$PlotVar1) + ylab("") + ggtitle(paste("Boxplot of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5)) +
stat_summary(fun.y = mean, geom = "point", size = 4, shape =input$Box_pShape1,
color = input$Col_BoxMean1)
} else {
ggBoxplot1 <- ggplot(uploadData(), aes(x = "", y = uploadData()[[input$PlotVar1]])) +
geom_boxplot(fill = input$Col_Box1, notch = input$notched1, width = .3) +
ylab(input$PlotVar1) + ylab(" ") + ggtitle(paste("Boxplot of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
if (input$horiz1 == TRUE) ggBoxplot1 + coord_flip()
else ggBoxplot1
}
}
})
### Plot 2 --------------------------------------------
output$dataPlot2 <- renderPlot({
if (is.null(input$inFile))
return(NULL)
validate(
need(input$PlotVar2, "Please select a variable to plot")
)
# R base Graphics ----------------------
if (input$Package2 == FALSE){
# Histogram -------------
if (input$PlotType2 == "hist") {
hist(plotData2(), main = paste("Histogram of Variable", input$PlotVar2), freq = input$Unit_Hist2,
xlab = input$PlotVar2, col = input$Col_Hist2, breaks = input$Breaks_Hist2)
# Scatterplot -------------------
} else if (input$PlotType2 == "scatter") {
# Jittered uploadData?
if (input$jitter2 == FALSE) {
plot(plotData2(), main = paste("Scatterplot of Variable", input$PlotVar2), pch = input$pShape2,
ylab = input$PlotVar2, col = input$Col_Scatter2)
} else {
plot(jitter(plotData2()), main = paste("Scatterplot of Variable", input$PlotVar2), pch = input$pShape2,
ylab = input$PlotVar2, col = input$Col_Scatter2)
}
# Boxplot -------------------
} else if (input$PlotType2 == "box") {
# Add mean?
if (showMean()[2] == TRUE) {
boxplot(plotData2(), main = paste("Scatterplot of Variable", input$PlotVar2),
xlab = input$PlotVar2, col = input$Col_Box2,
notch = input$notched2, horizontal = input$horiz2)
if (horiz()[2] == TRUE) {
points(mean(plotData2()), y = 1, col = input$Col_BoxMean2, pch = input$Box_pShape2, cex = 1.5)
} else {
points(mean(plotData2()), col = input$Col_BoxMean2, pch = input$Box_pShape2, cex = 1.5)
}
} else {
boxplot(plotData2(), main = paste("Scatterplot of Variable", input$PlotVar2),
xlab = input$PlotVar2, col = input$Col_Box2,
notch = input$notched2, horizontal = input$horiz2)
}
}
# ggplot 2 Graphics --------------------
} else if (input$Package2 == TRUE) {
# Histogram -------------
if (input$PlotType2 == "hist") {
# Plot frequency
if (input$Unit_Hist2 == TRUE) {
ggplot(data = uploadData(), aes(x = uploadData()[[input$PlotVar2]])) +
geom_histogram(binwidth = input$binwidth_Hist2, fill = input$Col_Hist2) +
xlab(input$PlotVar2) + ggtitle(paste("Histogram of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .5))
# Plot density
} else {
ggplot(data = uploadData(), aes(x = uploadData()[[input$PlotVar2]])) +
geom_histogram(aes( y = ..density..), binwidth = input$binwidth_Hist2, fill = input$Col_Hist2) +
xlab(input$PlotVar2) + ggtitle(paste("Histogram of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
# Scatterplot ---------------------
} else if (input$PlotType2 == "scatter") {
# Jittered uploadData?
if (input$jitter2 == FALSE) {
ggplot(data = uploadData(), aes(y = seq(1,length(uploadData()[[input$PlotVar2]])), x = uploadData()[[input$PlotVar2]])) +
geom_point(color = input$Col_Scatter2, shape = input$pShape2) +
xlab(input$PlotVar2) + ylab("Index") + ggtitle(paste("Scatterplot of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .5))
} else {
ggplot(data = uploadData(), aes(y = seq(1,length(uploadData()[[input$PlotVar2]])), x = uploadData()[[input$PlotVar2]])) +
geom_jitter(color = input$Col_Scatter2, shape = input$pShape2) +
xlab(input$PlotVar2) + ylab("Index") + ggtitle(paste("Scatterplot of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
# Boxplot -------------------
} else if (input$PlotType2 == "box") {
# Add mean?
if (showMean()[2] == TRUE) {
ggBoxplot2 <- ggplot(data = uploadData(), aes(x = "", y = uploadData()[[input$PlotVar2]])) +
geom_boxplot(fill = input$Col_Box2, notch = input$notched2) +
ylab(input$PlotVar2) + ylab("") + ggtitle(paste("Boxplot of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .3)) +
stat_summary(fun.y = mean, geom = "point", size = 4, shape =input$Box_pShape2,
color = input$Col_BoxMean2)
} else {
ggBoxplot2 <- ggplot(data = uploadData(), aes(x = "", y = uploadData()[[input$PlotVar2]])) +
geom_boxplot(fill = input$Col_Box2, notch = input$notched2) +
ylab(input$PlotVar2) + ylab(" ") + ggtitle(paste("Boxplot of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .3))
}
if (input$horiz2 == TRUE) ggBoxplot2 + coord_flip()
else ggBoxplot2
}
}
})
})
Kafi1993/Explore documentation built on May 21, 2019, 1:40 a.m.
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# server.R
library(shiny)
library(ggplot2)
library(psych)
library(colourpicker)
source("helpers.R")
shinyServer(function(input, output, session) {
# **********************************************************************************************
# Read in datafile =============================================================================
uploadData <- reactive({
inFile <- input$inFile
read.csv(inFile$datapath, header = input$head, sep = input$sep, stringsAsFactors = input$sASf,
quote = input$quote, dec = input$dec, na.strings = input$miss)
})
# **********************************************************************************************
# Showing uploadData =================================================================================
output$datatable <- renderDataTable({
validate(
need(input$inFile != "", "Please load a data set")
)
uploadData()
})
# **********************************************************************************************
# Descriptives Table ============================================================================
output$summary <- renderDataTable({
validate(
need(input$inFile != "", "Please load a data set")
)
list <- getDescriptives(uploadData())
df <- data.frame("Item" = names(list$mean),"Mean" = list$mean, "SD" = list$sd,"Median" = list$median, "Min" = list$min,
"Max" = list$max, "Skew" = list$skew, "Kurtosis" = list$kurtosis ,"Missings" = list$na)
})
# **********************************************************************************************
# Graphics All Items ============================================================================
numData <- reactive({
extractNumeric(uploadData())
})
# Vector containing Item names
RangeChoice <- reactive({
colNum <- 1:ncol(numData())
names(colNum) <- names(numData())
colNum
})
### Dynamic Column Range Panels
output$RangeColSelect1 <- renderUI({
validate(
need(input$inFile != "", "Please load a data set")
)
selectInput("ColRange1", "Show Variables from:", choices = c("", RangeChoice()))
})
output$RangeColSelect2 <- renderUI({
validate(
need(input$inFile != "", " ")
)
selectInput("ColRange2", "to:", choices = c("", RangeChoice()))
})
### Dynamic Plot Setting Panel (for vertical bars)
output$VerticalSettings <- renderUI({
radioButtons("VerticalType", "Should bars be grouped or stacked?", choices = c("Grouped bars", "Stacked bars"))
})
### Subset uploadData with selected Columns
dataForGraph <- reactive({
minC <- as.integer(input$ColRange1)
maxC <- as.integer(input$ColRange2)
numData()[minC:maxC]
})
### Dimensions of Plot for plotOutput
PlotAllDims <- reactive({
c(as.numeric(input$PlotAllHeight), as.numeric(input$PlotAllWidth))
})
observe({
input$SizeReset
updateTextInput(session, "PlotAllHeight", value = "400")
updateTextInput(session, "PlotAllWidth", value = "1600")
})
### Outout
observe(
output$plotAll <- renderPlot({
if (is.null(input$inFile))
return(NULL)
validate(
need(input$ColRange1, "Please choose a lower bound of columns to display"),
need(input$ColRange2, "Please choose an upper bound of columns to display")
)
# Some parameters
col_n <- as.integer(input$ColRange2) # Number of allowed columns
if (input$Rev_Col) ColDir <- -1 else ColDir <- 1 # Direction of color palette
# Horizontal Bars
if (input$PlotOrient == "horizontal") {
if(input$Unit_PlotAll_horiz) FreqType <- position_stack else FreqType <- position_fill
stackedBars(dataForGraph(), type = FreqType, n.col = col_n, palette = input$Col_PlotAll,
direction = ColDir)
# Vertical Bars
} else {
if(input$VerticalType == "Stacked bars" && input$Unit_PlotAll_vert) FreqType <- position_stack()
else if (input$VerticalType == "Stacked bars") FreqType <- position_fill()
else if (input$VerticalType == "Grouped bars") FreqType <- position_dodge()
parallelBars(dataForGraph(), position = FreqType, n.col = col_n, palette = input$Col_PlotAll,
direction = ColDir)
}
}, height = PlotAllDims()[1], width = PlotAllDims()[2]
)
)
# **********************************************************************************************
# Graphics Single Items =========================================================================
## Select Items ----------------------------
### Choices for Item Select Menu
columnChoice <- reactive({
colNum <- 1:ncol(uploadData())
names(colNum) <- names(uploadData())
})
### Dynamic Item Select Panel 1
output$ItemSelect1 <- renderUI({
validate(
need(input$inFile != "", "Please load a data set")
)
selectInput("PlotVar1", "Choose a variable to display", choices = c(Choose = "", columnChoice()))
})
### Dynamic Item Select Panel 2
output$ItemSelect2 <- renderUI({
validate(
need(input$inFile != "", "Please load a data set")
)
selectInput("PlotVar2", "Choose a variable to display", choices = c(Choose = "", columnChoice()))
})
## Dynamic Options for different PlotTypes ---------------------------
### Dynamic Plot Type Panels 1 ----------------
#### For Histogram
output$hist1Breaks <- renderUI({
validate(
need(input$PlotVar1, "Please select a variable to show all options")
)
if (input$Package1) {
numericInput("binwidth_Hist1", "Width of bars:",
value = 1, min = 0, step = .1)
} else
numericInput("Breaks_Hist1", "Number of breaks:",
value = nclass.Sturges(uploadData()[[input$PlotVar1]]), min = 1)
})
#### For Scatterplot
# None
### For Boxplot
output$viewMeanSpecs1_1 <- renderUI({
if(input$showMean1) {
colourInput("Col_BoxMean1", "Choose a color", value = "red")
} else return(NULL)
})
output$viewMeanSpecs1_2 <- renderUI({
if(input$showMean1) {
numericInput("Box_pShape1", "Change shape of points (from R graphics)", value = 15, min = 0, max = 25)
} else return(NULL)
})
### Dynamic Plot Type Panels 2 ---------------
#### For Histogram
output$hist2Breaks <- renderUI({
validate(
need(input$PlotVar2, "Please select a variable to show all options")
)
if (input$Package2) {
numericInput("binwidth_Hist2", "Width of bars:",
value = 1, min = 0, step = .1)
} else
numericInput("Breaks_Hist2", "Number of breaks:",
value = nclass.Sturges(uploadData()[[input$PlotVar2]]), min = 1)
})
#### For Scatterplot
# None
### For Boxplot
output$viewMeanSpecs2_1 <- renderUI({
if(input$showMean2) {
colourInput("Col_BoxMean2", "Choose a color", value = "red")
} else return(NULL)
})
output$viewMeanSpecs2_2 <- renderUI({
if(input$showMean2) {
numericInput("Box_pShape2", "Change shape of points (from R graphics)", value = 15, min = 0, max = 25)
} else return(NULL)
})
## Create Plots =========================================================
### Some Specs for adding mean to Boxplot
showMean <- reactive({
c(input$showMean1, input$showMean2)
})
horiz <- reactive({
c(input$horiz1, input$horiz2)
})
### Define uploadData to plot for R base
plotData1 <- reactive({
uploadData()[[input$PlotVar1]]
})
plotData2 <- reactive({
uploadData()[[input$PlotVar2]]
})
### Plot 1 ------------------------------------------------------------------
output$dataPlot1 <- renderPlot({
if (is.null(input$inFile))
return(NULL)
validate(
need(input$PlotVar1, "Please select a variable to plot")
)
# R base Graphics ----------------------
if (input$Package1 == FALSE){
# Histogram -------------
if (input$PlotType1 == "hist") {
hist(plotData1(), main = paste("Histogram of Variable", input$PlotVar1), freq = input$Unit_Hist1,
xlab = input$PlotVar1, col = input$Col_Hist1, breaks = input$Breaks_Hist1)
# Scatterplot -------------------
} else if (input$PlotType1 == "scatter") {
# Jittered uploadData?
if (input$jitter1 == FALSE) {
plot(plotData1(), main = paste("Scatterplot of Variable", input$PlotVar1), pch = input$pShape1,
ylab = input$PlotVar1, col = input$Col_Scatter1)
} else {
plot(jitter(plotData1()), main = paste("Scatterplot of Variable", input$PlotVar1), pch = input$pShape1,
ylab = input$PlotVar1, col = input$Col_Scatter1)
}
# Boxplot -------------------
} else if (input$PlotType1 == "box") {
# Add mean?
if (showMean()[1] == TRUE) {
boxplot(plotData1(), main = paste("Scatterplot of Variable", input$PlotVar1),
xlab = input$PlotVar1, col = input$Col_Box1,
notch = input$notched1, horizontal = input$horiz1)
if (horiz()[1] == TRUE) {
points(mean(plotData1()), y = 1, col = input$Col_BoxMean1, pch = input$Box_pShape1, cex = 1.5)
} else {
points(mean(plotData1()), col = input$Col_BoxMean1, pch = input$Box_pShape1, cex = 1.5)
}
} else {
boxplot(plotData1(), main = paste("Scatterplot of Variable", input$PlotVar1),
xlab = input$PlotVar1, col = input$Col_Box1,
notch = input$notched1, horizontal = input$horiz1)
}
}
# ggplot 2 Graphics --------------------
} else if (input$Package1 == TRUE) {
# Histogram -------------
if (input$PlotType1 == "hist") {
# Plot frequency
if (input$Unit_Hist1 == TRUE) {
ggplot(data = uploadData(), aes(x = uploadData()[[input$PlotVar1]])) +
geom_histogram(binwidth = input$binwidth_Hist1, fill = input$Col_Hist1) +
xlab(input$PlotVar1) + ggtitle(paste("Histogram of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
# Plot density
} else {
ggplot(data = uploadData(), aes(x = uploadData()[[input$PlotVar1]])) +
geom_histogram(aes( y = ..density..), binwidth = input$binwidth_Hist1, fill = input$Col_Hist1) +
xlab(input$PlotVar1) + ggtitle(paste("Histogram of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
# Scatterplot ---------------------
} else if (input$PlotType1 == "scatter") {
# Jittered uploadData?
if (input$jitter1 == FALSE) {
ggplot(data = uploadData(), aes(y = seq(1,length(uploadData()[[input$PlotVar1]])), x = uploadData()[[input$PlotVar1]])) +
geom_point(color = input$Col_Scatter1, shape = input$pShape1) +
xlab(input$PlotVar1) + ylab("Index") + ggtitle(paste("Scatterplot of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
} else {
ggplot(data = uploadData(), aes(y = seq(1,length(uploadData()[[input$PlotVar1]])), x = uploadData()[[input$PlotVar1]])) +
geom_jitter(color = input$Col_Scatter1, shape = input$pShape1) +
xlab(input$PlotVar1) + ylab("Index") + ggtitle(paste("Scatterplot of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
# Boxplot -------------------
} else if (input$PlotType1 == "box") {
# Add mean?
if (showMean()[1] == TRUE) {
ggBoxplot1 <- ggplot(uploadData(), aes(x = "", y = uploadData()[[input$PlotVar1]])) +
geom_boxplot(fill = input$Col_Box1, notch = input$notched1, width = .3) +
ylab(input$PlotVar1) + ylab("") + ggtitle(paste("Boxplot of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5)) +
stat_summary(fun.y = mean, geom = "point", size = 4, shape =input$Box_pShape1,
color = input$Col_BoxMean1)
} else {
ggBoxplot1 <- ggplot(uploadData(), aes(x = "", y = uploadData()[[input$PlotVar1]])) +
geom_boxplot(fill = input$Col_Box1, notch = input$notched1, width = .3) +
ylab(input$PlotVar1) + ylab(" ") + ggtitle(paste("Boxplot of Variable", input$PlotVar1)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
if (input$horiz1 == TRUE) ggBoxplot1 + coord_flip()
else ggBoxplot1
}
}
})
### Plot 2 --------------------------------------------
output$dataPlot2 <- renderPlot({
if (is.null(input$inFile))
return(NULL)
validate(
need(input$PlotVar2, "Please select a variable to plot")
)
# R base Graphics ----------------------
if (input$Package2 == FALSE){
# Histogram -------------
if (input$PlotType2 == "hist") {
hist(plotData2(), main = paste("Histogram of Variable", input$PlotVar2), freq = input$Unit_Hist2,
xlab = input$PlotVar2, col = input$Col_Hist2, breaks = input$Breaks_Hist2)
# Scatterplot -------------------
} else if (input$PlotType2 == "scatter") {
# Jittered uploadData?
if (input$jitter2 == FALSE) {
plot(plotData2(), main = paste("Scatterplot of Variable", input$PlotVar2), pch = input$pShape2,
ylab = input$PlotVar2, col = input$Col_Scatter2)
} else {
plot(jitter(plotData2()), main = paste("Scatterplot of Variable", input$PlotVar2), pch = input$pShape2,
ylab = input$PlotVar2, col = input$Col_Scatter2)
}
# Boxplot -------------------
} else if (input$PlotType2 == "box") {
# Add mean?
if (showMean()[2] == TRUE) {
boxplot(plotData2(), main = paste("Scatterplot of Variable", input$PlotVar2),
xlab = input$PlotVar2, col = input$Col_Box2,
notch = input$notched2, horizontal = input$horiz2)
if (horiz()[2] == TRUE) {
points(mean(plotData2()), y = 1, col = input$Col_BoxMean2, pch = input$Box_pShape2, cex = 1.5)
} else {
points(mean(plotData2()), col = input$Col_BoxMean2, pch = input$Box_pShape2, cex = 1.5)
}
} else {
boxplot(plotData2(), main = paste("Scatterplot of Variable", input$PlotVar2),
xlab = input$PlotVar2, col = input$Col_Box2,
notch = input$notched2, horizontal = input$horiz2)
}
}
# ggplot 2 Graphics --------------------
} else if (input$Package2 == TRUE) {
# Histogram -------------
if (input$PlotType2 == "hist") {
# Plot frequency
if (input$Unit_Hist2 == TRUE) {
ggplot(data = uploadData(), aes(x = uploadData()[[input$PlotVar2]])) +
geom_histogram(binwidth = input$binwidth_Hist2, fill = input$Col_Hist2) +
xlab(input$PlotVar2) + ggtitle(paste("Histogram of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .5))
# Plot density
} else {
ggplot(data = uploadData(), aes(x = uploadData()[[input$PlotVar2]])) +
geom_histogram(aes( y = ..density..), binwidth = input$binwidth_Hist2, fill = input$Col_Hist2) +
xlab(input$PlotVar2) + ggtitle(paste("Histogram of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
# Scatterplot ---------------------
} else if (input$PlotType2 == "scatter") {
# Jittered uploadData?
if (input$jitter2 == FALSE) {
ggplot(data = uploadData(), aes(y = seq(1,length(uploadData()[[input$PlotVar2]])), x = uploadData()[[input$PlotVar2]])) +
geom_point(color = input$Col_Scatter2, shape = input$pShape2) +
xlab(input$PlotVar2) + ylab("Index") + ggtitle(paste("Scatterplot of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .5))
} else {
ggplot(data = uploadData(), aes(y = seq(1,length(uploadData()[[input$PlotVar2]])), x = uploadData()[[input$PlotVar2]])) +
geom_jitter(color = input$Col_Scatter2, shape = input$pShape2) +
xlab(input$PlotVar2) + ylab("Index") + ggtitle(paste("Scatterplot of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .5))
}
# Boxplot -------------------
} else if (input$PlotType2 == "box") {
# Add mean?
if (showMean()[2] == TRUE) {
ggBoxplot2 <- ggplot(data = uploadData(), aes(x = "", y = uploadData()[[input$PlotVar2]])) +
geom_boxplot(fill = input$Col_Box2, notch = input$notched2) +
ylab(input$PlotVar2) + ylab("") + ggtitle(paste("Boxplot of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .3)) +
stat_summary(fun.y = mean, geom = "point", size = 4, shape =input$Box_pShape2,
color = input$Col_BoxMean2)
} else {
ggBoxplot2 <- ggplot(data = uploadData(), aes(x = "", y = uploadData()[[input$PlotVar2]])) +
geom_boxplot(fill = input$Col_Box2, notch = input$notched2) +
ylab(input$PlotVar2) + ylab(" ") + ggtitle(paste("Boxplot of Variable", input$PlotVar2)) +
theme(plot.title = element_text(size = 16, hjust = .3))
}
if (input$horiz2 == TRUE) ggBoxplot2 + coord_flip()
else ggBoxplot2
}
}
})
})
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