---
title: "diabetes-Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    theme: sandstone
    source_code: embed
---

```{r setup, include=FALSE}
# Importing libraries
library(flexdashboard)
library(tidyverse)
library(highcharter)
library(gt)
library(htmltools)
library(viridis)
library(DT)
library(ggplot2)
library(sunburstR)
library(lubridate)
library(plotly)
library(ggplot2)
library(hrbrthemes)
library(sjPlot)
library(sjmisc)
```

```{r}
diabetes <- read.csv("diabetes.csv")
```

Row
-----------------------------------------------------------------------

### Patient with Diabetes {.value-box}

```{r}
patient <- 500
gauge(patient, min = 0, max = 768, gaugeSectors(
  success = c(0, 250), warning = c(251, 500), danger = c(501, 768)
))
```


### Average Glucose {.value-box}

```{r}
glucose <- 120.89
gauge(glucose, min = 0, max = 200, gaugeSectors(
  success = c(0, 140), warning = c(141, 199), danger = c(200, 210)
))
```


### Average Age {.value-box}

```{r}
age <- 33.24
gauge(age, min = 0, max = 100, gaugeSectors(
  success = c(0,39), warning = c(40, 79), danger = c(80, 100)
))
```

Row {data-width=700}
-----------------------------------------------------------------------
    
### Scater plot of Glucose vs Age with Class by outcome
    
```{r message=FALSE, warning=FALSE}
pal <- c("red", "blue")
pal <- setNames(pal, c("0", "1"))

fig <- plot_ly(data = diabetes, x = ~Age, y = ~Glucose, color = ~Outcome, colors = pal) 

fig

```

   
Row {data-width=350}
-----------------------------------------------------------------------
    
### Predict Values of Glucose
    
```{r message=FALSE, warning=FALSE}
theme_set(theme_sjplot())

# make categorical
diabetes$Outcome <- to_factor(diabetes$Outcome)

# fit model with interaction
fit <- lm(Glucose ~ Age * Outcome * Pregnancies, data = diabetes)

plot_model(fit, type = "pred", terms = c("Age", "Outcome", "Pregnancies"))
```
    
### Glucose Histogram

```{r}
m<-mean(diabetes$Glucose)
std<-sqrt(var(diabetes$Glucose)) 
hist(diabetes$Glucose,prob=T,main="Glucose")
curve(dnorm(x, mean=m, sd=std), col="darkblue", lwd=2, add=TRUE)
```