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fitpal_app.R
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fitpal_app.R
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######################### R Libraries Required #################################
################################################################################
library(shiny)
library(shinyWidgets)
library(shinydashboard)
library(dashboardthemes)
library(openxlsx)
library(readxl)
library(dplyr)
library(tidyr)
library(reshape2)
library(ggplot2)
library(lubridate)
library(sjlabelled)
library(lessR)
library(tidyverse)
library(zoo)
library(forecast)
############################### MAIN APP #######################################
ui <- dashboardPage(
# dashboard title
title = "Fitpal - Fitness Tracker",
dashboardHeader(
title = shinyDashboardLogo(
theme = "purple_gradient",
boldText = "FitPal:",
mainText = "Fitness Tracker",
badgeText = "v1.1"
)),
dashboardSidebar(
sidebarUserPanel(name = textOutput("text1"),
subtitle = a(href = "#",
icon("circle",
class = "text-success"),
"Online")
),
sidebarMenu(
id = "tabs",
# upload data & demographic information
menuItem(text = "Update User Profile", tabName = "user_profile",
icon = icon("id-card")),
# data exploratory analysis & activity review
menuItem(text = "View Activity Dashboard", tabName = "dashboard",
icon = icon("dashboard")),
# set goals
menuItem(text = "Set Your Goals", tabName = "change_goals", icon =
icon("bullseye")),
# view progress
menuItem(text = "Track Your Progress", icon = icon("bar-chart-o"),
menuSubItem("Activity", tabName = "subitem1"),
menuSubItem("Weight Loss", tabName = "subitem2")
)
),
width = "250px",
collapsed = FALSE
),
dashboardBody(
# upload theme
shinyDashboardThemes(
theme = "blue_gradient"),
tabItems(
tabItem(
# User profile & demographic input
tabName = "user_profile",
h3("User Profile", tagList(shiny::icon("id-card"))),
fluidRow(
box(textInput("name", "Name", placeholder = "Enter Your Name")),
box(selectInput("gender", "Select Your Gender",
list("Male", "Female", "Transgender",
"Non-binary","Prefer Not To Respond")
)
)
),
fluidRow(
box(numericInput("height", "Enter Your Height (in)",
value = 60 , min = 20, max = 110, step = 1)),
box(numericInput("weight", "Enter Your Weight (lb)",
value = 170 , min = 5, max = 700, step = 1))
),
# Data Upload or Data Sample Selection
h3("Health Data", tagList(shiny::icon("table"))),
fluidRow(
box(fileInput(inputId = "user_data",
label = "File upload:",
accept = ".xlsx"),
# Use uploaded data set
actionButton(
inputId = "use_uploaded",
label = "Use Uploaded File",
class = "btn-primary")
),
# choose sample data set sheet to preview
box(selectInput("sample_data",
"Choose a sample sheet",
choices = c("Hourly Steps",
"Hourly Calories",
"Hourly Intensities",
"Hourly Stand",
"Daily Steps",
"Daily Intensities",
"Daily Activity",
"Sleep Minutes",
"Daily Sleep",
"Daily Stand")),
# Download 'template' / sample data set
downloadButton("download_sample",
"Download Sample Data"),
# Use sample data set
actionButton(
inputId = "use_sample",
label = "Use Sample Data",
class = "btn-primary")
),
# preview sample data set sheet selected
box(tableOutput("sample_table"), width = 12)
)
),
tabItem(
# Review BMI graph and Set Goals
tabName = "change_goals",
# BMI Graph
h3("BMI Spectrum", tagList(shiny::icon("hand-holding-heart"))),
fluidRow(
box(
plotOutput(outputId = "bmiplot"), width = 12
)
),
# Goal Setting
h3("Set Your Goals", tagList(shiny::icon("bullseye"))),
fluidRow(
box(
knobInput(
inputId = "steps_goal",
label = "Daily Steps",
value = 9000,
min = 0,
max = 100000,
displayPrevious = TRUE,
lineCap = "round",
fgColor = "#428BCA",
inputColor = "#428BCA"
)
),
box(
knobInput(
inputId = "stand_goal",
label = "Daily Standing Hours",
value = 6,
min = 0,
max = 24,
displayPrevious = TRUE,
lineCap = "round",
fgColor = "#428BCA",
inputColor = "#428BCA"
)
),
box(
knobInput(
inputId = "exercise_goal",
label = "Daily Calories Burnt",
value = 1800,
min = 0,
max = 4000,
displayPrevious = TRUE,
lineCap = "round",
fgColor = "#428BCA",
inputColor = "#428BCA"
)
),
box(
knobInput(
inputId = "sleep_goal",
label = "Daily Sleep Hours",
value = 8,
min = 0,
max = 24,
displayPrevious = TRUE,
lineCap = "round",
fgColor = "#428BCA",
inputColor = "#428BCA"
)
)
),
# Update goals
actionButton(
inputId = "set_goal",
label = "Update Goals",
class = "btn-primary"),
h3("Start Your Weight Loss Journey",
tagList(shiny::icon("weight"))),
fluidRow(
box(
knobInput(
inputId = "weight_goal",
label = "Set weight desired at the end of the month(lb)",
value = 127,
min = 60,
max = 204,
displayPrevious = TRUE,
lineCap = "round",
fgColor = "#428BCA",
inputColor = "#428BCA"
)
)
),
actionButton(
inputId = "set_weight_goal",
label = "Update Weight Goal",
class = "btn-primary")
),
tabItem(
# Activity Dashboard & Exploratory Analysis
tabName = "dashboard",
h3("Activity Dashboard", tagList(shiny::icon("tachometer-alt"))),
fluidRow(
# tab for steps analysis
tabBox(
title = tagList(shiny::icon("walking"), "Steps"),
id = "steps", height = "auto",
tabPanel(
title = "Hourly",
plotOutput(outputId = "hourlysteps")),
tabPanel(
title = "Weekly",
plotOutput(outputId = "dailysteps")),
tabPanel(title = "Historic",
plotOutput(outputId = "historicsteps"))
),
# tab for calories burnt analysis
tabBox(
title = tagList(shiny::icon("running"), "Calories"),
id = "cals", height = "auto",
tabPanel(
title = "Hourly",
plotOutput(outputId = "hourlycalories")),
tabPanel(
title = "Weekly",
plotOutput(outputId = "weeklycalories")),
tabPanel(
title = "Historic",
plotOutput(outputId = "historiccalories"))
),
# tab for intensity analysis
tabBox(
title = tagList(shiny::icon("dumbbell"), "Intensity"),
id = "intensity", height = "auto",
tabPanel(
title = "Daily",
plotOutput(outputId = "dailyintensity")),
tabPanel(
title = "Weekly",
plotOutput(outputId = "weeklyintensity")),
tabPanel(
title = "Historic",
plotOutput(outputId = "historicintensity"))
),
# tab for distance analysis
tabBox(
title = tagList(shiny::icon("road"), "Distance"),
id = "distance", height = "auto",
tabPanel(
title = "Daily",
plotOutput(outputId = "dailydist")),
tabPanel(
title = "Weekly",
plotOutput(outputId = "weeklydist")),
tabPanel(
title = "Historic",
plotOutput(outputId = "historicdist"))
),
# tab for sleep analysis
tabBox(
title = tagList(shiny::icon("bed"), "Sleep"),
id = "sleep", height = "auto", width = 12,
tabPanel(
title = "Daily",
plotOutput(outputId = "dailysleep")),
tabPanel(
title = "Weekly",
plotOutput(outputId = "weeklysleep")),
tabPanel(
title = "Historic",
plotOutput(outputId = "historicsleep"))
)
),
),
# DELETE?
tabItem(
tabName = "subitem1",
h3("Don't Break The Chain", tagList(shiny::icon("calendar-check"))),
fluidRow(
box(
h4("Historical Goal Completion"),
plotOutput(outputId = "BreakChain")
),
box(
h4("Streak Count"),
plotOutput(outputId = "activity_streak")
)
),
h3("Daily Tracker", tagList(shiny::icon("watch-fitness"))),
fluidRow(
box(
h4("Daily Steps Goal"),
plotOutput(outputId = "step_goal_plot")
),
box(
h4("Daily Stand Goal"),
plotOutput(outputId = "stand_goal_plot")
),
box(
h4("Daily Excercise Goal"),
plotOutput(outputId = "calories_goal_plot")
)
)
),
tabItem(
tabName = "subitem2",
h3("Historical Weight", tagList(shiny::icon("dumbbell"))),
fluidRow(
box(
plotOutput(outputId = "weightLogInfo_plot") , width = 12
)
),
h3("Weight Loss Tracker", tagList(shiny::icon("bullseye"))),
fluidRow(
box(
valueBoxOutput("calories", width = 12) ,width = 12
),
box(
valueBoxOutput("Target", width = 6),
valueBoxOutput("Prediction", width = 6),width = 12
)
)
)
) # tab items
) # end body
) # end dash page
server <- function(input, output, session) {
############################# USER PROFILE #####################################
sample_Input <- reactive({
input$use_sample
# select data set to show in preview
switch(input$sample_data,
"Hourly Steps" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="hourlySteps",
col_name=T)),
"Hourly Calories" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="hourlyCalories",
col_name=T)),
"Hourly Intensities" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="hourlyIntensities",
col_name=T)),
"Hourly Stand" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="hourlyStand",
col_name=T)),
"Daily Steps" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="dailySteps",
col_name=T)),
"Daily Intensities" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="dailyIntensities",
col_name=T)),
"Daily Activity" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="dailyActivity",
col_name=T)),
"Sleep Minutes" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="minuteSleep",
col_name=T)),
"Daily Sleep" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="sleepDay",
col_name=T)),
"Daily Stand" = as.data.frame(read_excel("Joined_Dataset_V2.xlsx",
sheet="standDay",
col_name=T))
)
})
# sample data set sheet
output$sample_table <- renderTable({
head(sample_Input()[1:ncol(sample_Input())], n = 10)
})
# download template/sample data
sample <- loadWorkbook("Joined_Dataset_V2.xlsx")
output$download_sample <- downloadHandler(
filename = function() {
file <- "FitPal_Sample-Dataset_Template.xlsx"
},
content = function(file) {
# save all workbook including sheets
saveWorkbook(sample, file = file, overwrite = TRUE)
}
)
########################## ACTIVITY DASHVBOARD #################################
# Hourly Steps
hourlySteps <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the hourly steps data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
hsteps <- read_excel(input$user_data$datapath, sheet = "hourlySteps")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
hsteps <- read_excel("Joined_Dataset_V2.xlsx", sheet = "hourlySteps")
}
hsteps <- as.data.frame(hsteps)
print(str(hsteps))
hsteps$ActivityHour <- as.POSIXct(hsteps$ActivityHour, format="%Y-%m-%d")
hsteps<- subset(hsteps, ActivityHour> "2016-05-12")
hsteps
})
# hourly steps graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$hourlysteps <- renderPlot(
hourlySteps() %>%
group_by(ActivityHour) %>%
summarize(StepTotal = mean(StepTotal)) %>%
ggplot(aes(x=ActivityHour, y= StepTotal, fill = StepTotal))+
geom_col()+
scale_fill_continuous(low = '#05fbd7', high = "#17667b") +
labs(title = "Hourly Steps") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Daily Steps
dailySteps <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the daily steps data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
dsteps <- read_excel(input$user_data$datapath, sheet = "dailySteps")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
dsteps <- read_excel("Joined_Dataset_V2.xlsx", sheet = "dailySteps")
}
dsteps <- as.data.frame(dsteps)
print(str(dsteps))
dsteps$ActivityDay <- as.POSIXct(dsteps$ActivityDay, format = "%Y-%m-%d")
dsteps <- subset(dsteps, ActivityDay > "2016-05-05")
dsteps
})
# daily steps graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$dailysteps <- renderPlot(
ggplot(data = dailySteps(), aes(x = ActivityDay, y = StepTotal)) +
geom_bar(stat = "identity", fill = "#27839a") +
labs(title = "Weekly Steps",
x = "Date", y = "Weekly Steps") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Historic Steps
historicSteps <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the historic steps data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
histsteps <- read_excel(input$user_data$datapath, sheet = "dailySteps")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
histsteps <- read_excel("Joined_Dataset_V2.xlsx", sheet = "dailySteps")
}
histsteps <- as.data.frame(histsteps)
print(str(histsteps))
histsteps
})
# historic steps graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$historicsteps <- renderPlot(
ggplot(data = historicSteps(), aes(x = ActivityDay, y = StepTotal)) +
geom_line(color = "#2cdeeb", size = 2) +
xlab("Date")+
ylab("Total Steps")+
labs(title = "Historic Steps") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Hourly Calories
hourlyCalories <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the hourly calories data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
hcal <- read_excel(input$user_data$datapath, sheet = "hourlyCalories")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
hcal <- read_excel("Joined_Dataset_V2.xlsx", sheet = "hourlyCalories")
}
hcal <- as.data.frame(hcal)
print(str(hcal))
hcal$ActivityHour <- as.POSIXct(hcal$ActivityHour, format="%Y-%m-%d")
hcal<- subset(hcal, ActivityHour> "2016-05-12")
hcal
})
# hourly calories graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$hourlycalories <- renderPlot(
hourlyCalories() %>%
group_by(ActivityHour) %>%
summarize(CaloriesTotal = mean(Calories)) %>%
ggplot(aes(x=ActivityHour, y= CaloriesTotal, fill = CaloriesTotal))+
geom_col()+
scale_fill_continuous(low = '#05fbd7', high = "#17667b") +
labs(title = "Hourly Calories") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Weekly Calories
weeklyCalories <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the weekly calories data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
wcal <- read_excel(input$user_data$datapath, sheet = "dailyActivity")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
wcal <- read_excel("Joined_Dataset_V2.xlsx", sheet = "dailyActivity")
}
wcal <- as.data.frame(wcal)
print(str(wcal))
wcal$ActivityDate <-as.POSIXct(wcal$ActivityDate, format = "%Y-%m-%d")
wcal <- subset(wcal, ActivityDate > "2016-05-06")
wcal
})
# weekly calories graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$weeklycalories <- renderPlot(
ggplot(data = weeklyCalories(), aes(x = ActivityDate, y = Calories)) +
geom_bar(stat = "identity", fill = "#27839a") +
labs(title = "Weekly Calories ",
x = "Date", y = "Weekly Calories") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Historic Calories
historicCalories <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the historic calories data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
histcal <- read_excel(input$user_data$datapath, sheet = "dailyActivity")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
histcal <- read_excel("Joined_Dataset_V2.xlsx", sheet = "dailyActivity")
}
histcal <- as.data.frame(histcal)
print(str(histcal))
histcal
})
# historical calories graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$historiccalories <- renderPlot(
ggplot(historicCalories(), aes(x = ActivityDate, y = Calories))+
geom_line(color = "#2cdeeb", size = 2) +
xlab("Date")+
ylab("Calories Burned")+
labs(title = "Historic Calories") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Daily Intensities
dailyIntensity <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the daily intensities data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
dint <- read_excel(input$user_data$datapath, sheet = "hourlyIntensities")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
dint <- read_excel("Joined_Dataset_V2.xlsx", sheet = "hourlyIntensities")
}
dint <- as.data.frame(dint)
print(str(dint))
dint$ActivityHour <- as.POSIXct(dint$ActivityHour, format = "%Y-%m-%d")
dint <- subset(dint, ActivityHour > "2016-05-06")
dint
})
# daily intensity graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$dailyintensity <- renderPlot(
ggplot(data = dailyIntensity(),
aes(x=ActivityHour, y= AverageIntensity, fill = AverageIntensity))+
geom_col()+
scale_fill_continuous(low = '#05fbd7', high = "#17667b") +
labs(title = "Daily Intensities") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Weekly Intensities
weeklyIntensity <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the weekly intensities data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
wint <- read_excel(input$user_data$datapath, sheet = "dailyIntensities")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
wint <- read_excel("Joined_Dataset_V2.xlsx", sheet = "dailyIntensities")
}
wint <- as.data.frame(wint)
print(str(wint))
wint$ActivityDay <- as.POSIXct(wint$ActivityDay, format = "%Y-%m-%d")
wint <- subset(wint, ActivityDay > "2016-05-06")
wint <- wint %>% select(ActivityDay,
VeryActiveMinutes,
FairlyActiveMinutes,
LightlyActiveMinutes) %>% data.frame()
wint <- melt(wint, id.vars = c("ActivityDay"))
wint
})
# weekly intensity graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$weeklyintensity <- renderPlot(
ggplot(data = weeklyIntensity(),
aes(fill = variable, y=value, x = ActivityDay)) +
geom_bar(position = position_fill(reverse = TRUE), stat="identity") +
labs(title = "Weekly Intensities") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4")) +
scale_colour_manual(values = c('LightlyActiveMinutes' = '#05fbd7',
'FairlyActiveMinutes' = '#17667b',
'VeryActiveMinutes' = "#f8766d"),
aesthetics = "fill")
)
)
# Historic Intensities
historicIntensity <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the historic intensities data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
hint <- read_excel(input$user_data$datapath, sheet = "dailyIntensities")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
hint <- read_excel("Joined_Dataset_V2.xlsx", sheet = "dailyIntensities")
}
hint <- as.data.frame(hint)
print(str(hint))
hint <- hint %>% select(ActivityDay,
VeryActiveMinutes,
FairlyActiveMinutes,
LightlyActiveMinutes) %>% data.frame()
hint <- melt(hint, id.vars = c("ActivityDay"))
hint
})
# historic intensity graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$historicintensity <- renderPlot(
ggplot(data = historicIntensity(),
aes(fill = variable, y=value, x = ActivityDay)) +
geom_bar(position = position_fill(reverse = TRUE), stat="identity") +
labs(title = "Historic Intensities") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4")) +
scale_colour_manual(values = c('LightlyActiveMinutes' = '#05fbd7',
'FairlyActiveMinutes' = '#17667b',
'VeryActiveMinutes' = "#f8766d"),
aesthetics = "fill")
)
)
# Weekly Distance
weeklyDistance <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the weekly distance data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
wdist <- read_excel(input$user_data$datapath, sheet = "dailyActivity")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
wdist <- read_excel("Joined_Dataset_V2.xlsx", sheet = "dailyActivity")
}
wdist <- as.data.frame(wdist)
print(str(wdist))
wdist$ActivityDate <- as.POSIXct(wdist$ActivityDate, format = "%Y-%m-%d")
wdist <- subset(wdist, ActivityDate > "2016-05-06")
wdist <- wdist %>% select(ActivityDate,
VeryActiveDistance,
ModeratelyActiveDistance,
LightActiveDistance) %>% data.frame()
wdist <- melt(wdist, id.vars = c("ActivityDate"))
wdist
})
# weekly distance graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$weeklydist <- renderPlot(
ggplot(data = weeklyDistance(),
aes(fill = variable, y=value, x = ActivityDate)) +
geom_bar(position = position_fill(reverse = TRUE), stat="identity") +
labs(title = "Weekly Distance") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4")) +
scale_colour_manual(values = c('LightActiveDistance' = '#05fbd7',
'ModeratelyActiveDistance' = '#17667b',
'VeryActiveDistance' = "#f8766d"),
aesthetics = "fill")
)
)
# Historic Distance
historicDistance <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the historic distance data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
hdist <- read_excel(input$user_data$datapath, sheet = "dailyActivity")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
hdist <- read_excel("Joined_Dataset_V2.xlsx", sheet = "dailyActivity")
}
hdist <- as.data.frame(hdist)
print(str(hdist))
hdist <- hdist %>% select(ActivityDate,
VeryActiveDistance,
ModeratelyActiveDistance,
LightActiveDistance) %>% data.frame()
hdist <- melt(hdist, id.vars = c("ActivityDate"))
hdist
})
# historic distance graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$historicdist <- renderPlot(
ggplot(data = historicDistance(),
aes(fill = variable, y= value, x = ActivityDate)) +
geom_bar(position = position_fill(reverse = TRUE), stat="identity") +
labs(title = "Historic Distance") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4")) +
scale_colour_manual(values = c('LightActiveDistance' = '#05fbd7',
'ModeratelyActiveDistance' = '#17667b',
'VeryActiveDistance' = "#f8766d"),
aesthetics = "fill")
)
)
# Daily Sleep
dailySleep <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the daily sleep data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
dsleep <- read_excel(input$user_data$datapath, sheet = "minuteSleep")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
dsleep <- read_excel("Joined_Dataset_V2.xlsx", sheet = "minuteSleep")
}
dsleep <- dsleep %>% separate(date,sep = " ", c("Days", "Time")) %>%
separate(Time, sep = ":", c("Hours", "Mins", "Seconds"),
extra = "merge", fill = "right") %>%
group_by(Days) %>% summarise(Hours = as.numeric(unique(Hours))) %>%
filter(Days == "2016-05-11")
hours_list <- data.frame(Hour_number = seq(1:24))
dsleep <- merge(hours_list, dsleep, by.x = "Hour_number",
by.y = "Hours", all.x = T)
dsleep <- dsleep %>% transmute(Hour_number = as.numeric(Hour_number),
Num = ifelse(is.na(Days), 0, 1))
print(str(dsleep))
dsleep
})
# daily sleep graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$dailysleep <- renderPlot(
ggplot(data = dailySleep(), aes(x = Hour_number, y = Num)) +
geom_bar(stat="identity", fill = "#27839a") +
labs(title = "Daily Sleep Trend", x = "Hour") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Weekly Sleep
weeklySleep <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the weekly sleep data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
wsleep <- read_excel(input$user_data$datapath, sheet = "sleepDay")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
wsleep <- read_excel("Joined_Dataset_V2.xlsx", sheet = "sleepDay")
}
wsleep$SleepDay <- as.POSIXct(wsleep$SleepDay, format = "%Y-%m-%d")
wsleep <- subset(wsleep, SleepDay > "2016-05-05")
wsleep <- as.data.frame(wsleep)
print(str(wsleep))
wsleep
})
# weekly sleep graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$weeklysleep <- renderPlot(
ggplot(data = weeklySleep(), aes(x = SleepDay, y = TotalMinutesAsleep)) +
geom_bar(stat = "identity", fill = "#27839a") +
labs(title = "Weekly Sleep",
x = "Date", y = "Weekly Sleep") +
geom_abline(slope=0, intercept=420, col = "#f8766d", lty=2) +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
# Historic Sleep
historicSleep <- reactive({
c(input$use_uploaded, input$use_sample)
# prepare the historic sleep data from either uploaded or sample data
if (is.null(input$user_data) == F & is.null(input$use_uploaded) == F) {
hsleep <- read_excel(input$user_data$datapath, sheet = "sleepDay")
}
else if (is.null(input$user_data) == T | is.null(input$use_sample) == F) {
hsleep <- read_excel("Joined_Dataset_V2.xlsx", sheet = "sleepDay")
}
hsleep$SleepDay <- as.POSIXct(hsleep$SleepDay, format = "%Y-%m-%d")
hsleep <- subset(hsleep, SleepDay > "2016-05-05")
hsleep <- as.data.frame(hsleep)
print(str(hsleep))
hsleep
})
# historic sleep graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
output$historicsleep <- renderPlot(
ggplot(data = historicSleep(),
aes(x = SleepDay, y = TotalMinutesAsleep)) +
geom_line(color = "#2cdeeb", size = 2) +
xlab("Date") +
ylab("Sleep Time (in Minutes)") +
geom_abline(slope=0, intercept=420, col = "#f8766d", lty=2) +
labs(title = "Historic Sleep") +
theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12, face = "bold"),
panel.background = element_rect(fill = "white"),
axis.line = element_line(size = 1, colour = "black"),
panel.grid.major = element_line(colour = "#f4f4f4"))
)
)
############################ SET YOUR GOALS ####################################
# BMI Graph
observeEvent(
c(input$use_uploaded, input$use_sample),
ignoreInit = T,
# prepare the BMI calculations for uploaded or sample data
output$bmiplot <- renderPlot({
# calculate BMI
weight_ideal <- 100
lb <- input$weight
inches <- input$height
bmi_output <- (lb / (inches^2)) * 703
# BMI Category
if (inches < 58){
weight_ideal <- round(mean(seq(from = 60, to = 114, by = 1)))
} else if (inches == 58){
weight_ideal <- round(mean(seq(from = 91, to = 118, by = 1)))
} else if (inches == 59){
weight_ideal <- round(mean(seq(from = 94, to = 123, by = 1)))
} else if (inches == 60){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 61){
weight_ideal <- round(mean(seq(from = 100, to = 131, by = 1)))
} else if (inches == 62){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 63){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 64){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 65){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 66){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 67){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 68){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 69){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 70){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 71){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 72){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 73){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 74){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 75){
weight_ideal <- round(mean(seq(from = 97, to = 127, by = 1)))
} else if (inches == 76){