---
title: "109001014's Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: fill
    social: [ "twitter", "facebook", "menu"]
    source_code: embed
---

```{r setup, include=FALSE}
#設定環境 如果無法設定套件環境，請下載套件，利用install.packages("XXX")指令
library(flexdashboard)
library(knitr)
library(DT)
library(rpivotTable)
library(ggplot2)
library(plotly)
library(dplyr)
library(openintro)
library(highcharter)
library(ggvis)

# 當圖形帶有中文，請安裝此套件
knitr::opts_chunk$set(fig.showtext=TRUE)
library(showtext)
showtext_auto()
```

```{r}
#帶入資料
data <- read.csv("C:/Users/user/Downloads./vehicle.csv")
```

```{r}
#預先指定顏色
mycolors <- c("blue", "#FFC125", "darkgreen", "darkorange")
```

Interactive Data Visualization
=====================================

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

### Car Failure Analysis

```{r}
#顯示文字方塊
valueBox(paste("Car Failure"),
         color = "warning")
```

### Car Failures in US

```{r}
#顯示文字方塊，帶入數值
valueBox(length(data$State),
         icon = "fa-building")
```

### **Labor Cost**

```{r}
#顯示計量表，並指定顏色範圍。lc代表工資labor cost。
gauge(round(mean(data$lc),
            digits = 2),
            min = 0,
            max = 350,
            gaugeSectors(success = c(0, 150),
                         warning = c(150, 200),
                         danger = c(200, 450),
                         colors = c("green", "yellow", "red")))
```

### Massachusetts

```{r}
#顯示文字方塊，帶入特定州別條件下的數值
valueBox(sum(data$State == "MA"),
         icon = 'fa-user')
```

### California

```{r}
#顯示文字方塊，帶入特定州別條件下的數值
valueBox(sum(data$State == "CA"),
         icon = 'fa-user')
```

### Texas

```{r}
#顯示文字方塊，帶入特定州別條件下的數值
valueBox(sum(data$State == "TX"),
         icon = 'fa-user')
```

### Florida

```{r}
#顯示文字方塊，帶入特定州別條件下的數值
valueBox(sum(data$State == "FL"),
         icon = 'fa-user')
```

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

### Failures By State

```{r}
#繪製各州別的汽車故障總數長條圖
p1 <- data %>%
         group_by(State) %>%          #依州別分群計算
         summarise(count = n()) %>%   #計算總數
         plot_ly(x = ~reorder(State,count,desc),     #X軸為州別，並依照數量遞減排序
                 y = ~count,          #Y軸為州別
                 color = "red",       #顏色為紅色
                 type = 'bar') %>%    #圖形類別為長條圖
layout(xaxis = list(title = "Failures By State"),   #X軸的名稱
yaxis = list(title = 'Count'))                      #Y軸的名稱
p1   #呼叫圖形
```

### Top States

```{r}
#繪製汽車故障總數大於50的州佔比甜甜圈圖
p2 <- data %>%
         group_by(State) %>%
         summarise(count = n()) %>%
         filter(count>100) %>%    # 篩選總數大於50
         plot_ly(labels = ~State,
                 values = ~count,
                 marker = list(colors = mycolors)) %>%  #指定顏色
         add_pie(hole = 0.5) %>%  #中間空圈大小
         layout(xaxis = list(zeroline = F,
                             showline = F,
                             showticklabels = F,
                             showgrid = F),
                yaxis = list(zeroline = F,
                             showline = F,
                             showticklabels=F,
                             showgrid=F))
p2
```

Map
========================================

### Map

```{r}
#繪製汽車故障州別(State)的地圖
car <- data %>%
         group_by(State) %>%
         summarize(total = n())
car$State <- abbr2state(car$State)

highchart() %>%
         hc_title(text = "Car Failures in US") %>%
         hc_subtitle(text = "Source: Vehiclefailure.csv") %>%
         hc_add_series_map(usgeojson, car,
                           name = "State",
                           value = "total",
                           joinBy = c("woename", "State")) %>%
         hc_mapNavigation(enabled = T)
```