---
title: "New Zealand Trade Dashboard (2014-2019)"
author: "Varun Khanna"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    social: menu
    source_code: embed

---
```{r global3 setup, include=FALSE}
#Loading Libraries & setting theme of the layout
LoadLibraries <- function(){
  library(highcharter)
  library(dplyr)
  library(viridisLite)
  library(forecast)
  library(treemap)
  library(flexdashboard)
    
}

LoadLibraries()
thm <- 
  hc_theme(
    colors = c("#1a6ecc", "#434348", "#90ed7d"),
    chart = list(
      backgroundColor = "transparent",
      style = list(fontFamily = "Source Sans Pro")
    ),
    xAxis = list(
      gridLineWidth = 1
    )
  )

#Loading in data
df <- read.csv("trade_data.csv")

#exports of goods only
df.exports <- df[df$type == "exports" & df$product_type =="good",]
#changing some factoring
levels(df.exports$country)[levels(df.exports$country)=="China, People's Republic of"] <- "China"
levels(df.exports$country)[levels(df.exports$country)=="Korea, Republic of"] <- "Korea"
```
Exports
======================================================================= 

Column {data-width=500}
-----------------------------------------------------------------------

### Annual Exports

```{r}


df.exports%>%
  group_by(year)%>%
  summarise(value = sum(value))%>%
  arrange(desc(value))%>%
  top_n(20)%>%
  hchart(type = "column", hcaes(x =year,y = value))%>%
  hc_yAxis(title = list(text = "Value in Billions"))


```




### Exports on the world map
```{r}
df.test <-df.exports%>%
  group_by(country)%>%
  summarise(
    value = sum(value))
#levels(df.test$country)[levels(df.test$country)=="China, People's Republic of"] <- "China"
data(worldgeojson, package = "highcharter")

#mapping
highchart(type = "map") %>% 
  hc_add_series_map(map = worldgeojson, df =  df.test, value = "value", joinBy = c("name","country")) %>% 
  hc_colorAxis(stops = color_stops()) %>% 
  hc_tooltip(useHTML = TRUE, headerFormat = "",
             pointFormat = "NZ has exported ${point.value} worth of goods to {point.name} ")

```




Column {.tabset data-width=500}
-----------------------------------------------------------------------

### Export by Products


```{r, fig.keep='none'}



tree.map <- treemap(df.exports, index ="product_description",
                          vSize = "value", vColor = "value",
                          type = "value", palette = rev(viridis(6)))

highchart() %>% 
  hc_add_series_treemap(tree.map, allowDrillToNode = TRUE,
                        layoutAlgorithm = "squarified") %>% 
  hc_add_theme(thm)



```

### Export by Country

```{r}

# tree.map <- treemap(df.exports, index ="country",
#                           vSize = "value", vColor = "value",
#                           type = "value", palette = rev(viridis(6)))
# 
# highchart() %>% 
#   hc_add_series_treemap(tree.map, allowDrillToNode = TRUE,
#                         layoutAlgorithm = "squarified") %>% 
#   hc_add_theme(thm)


df.exports%>%
  group_by(country)%>%
  summarise(value = sum(value))%>%
  arrange(desc(value))%>%
  top_n(20)%>%
  hchart(type = "bar", hcaes(x = country,y = value))%>%
  hc_yAxis(title = list(text = "Value in Billions"))


```


Imports
======================================================================= 

```{r global, include=FALSE}

thm <- 
  hc_theme(
    colors = c("#1a6ecc", "#434348", "#90ed7d"),
    chart = list(
      backgroundColor = "transparent",
      style = list(fontFamily = "Source Sans Pro")
    ),
    xAxis = list(
      gridLineWidth = 1
    )
  )



#exports of goods only
df.imports <- df[df$type == "imports" & df$product_type =="good",]
#changing some factoring
levels(df.imports$country)[levels(df.imports$country)=="China, People's Republic of"] <- "China"
levels(df.imports$country)[levels(df.imports$country)=="Korea, Republic of"] <- "Korea"
```

Column {data-width=500}
-----------------------------------------------------------------------

### Annual Imports

```{r}


df.imports%>%
  group_by(year)%>%
  summarise(value = sum(value))%>%
  arrange(desc(value))%>%
  top_n(20)%>%
  hchart(type = "column", hcaes(x =year,y = value))%>%
  hc_yAxis(title = list(text = "Value in Billions"))


```




### Imports on the world map
```{r}
df.test <-df.imports%>%
  group_by(country)%>%
  summarise(
    value = sum(value))
#levels(df.test$country)[levels(df.test$country)=="China, People's Republic of"] <- "China"
data(worldgeojson, package = "highcharter")

#mapping
highchart(type = "map") %>% 
  hc_add_series_map(map = worldgeojson, df =  df.test, value = "value", joinBy = c("name","country")) %>% 
  hc_colorAxis(stops = color_stops()) %>% 
  hc_tooltip(useHTML = TRUE, headerFormat = "",
             pointFormat = "NZ has imported ${point.value} worth of goods to {point.name} ")

```




Column {.tabset data-width=500}
-----------------------------------------------------------------------

### Import by Products


```{r, fig.keep='none'}



tree.map <- treemap(df.imports, index ="product_description",
                          vSize = "value", vColor = "value",
                          type = "value", palette = rev(viridis(6)))

highchart() %>% 
  hc_add_series_treemap(tree.map, allowDrillToNode = TRUE,
                        layoutAlgorithm = "squarified") %>% 
  hc_add_theme(thm)



```

### Import by Country

```{r}

# tree.map <- treemap(df.imports, index ="country",
#                           vSize = "value", vColor = "value",
#                           type = "value", palette = rev(viridis(6)))
# 
# highchart() %>% 
#   hc_add_series_treemap(tree.map, allowDrillToNode = TRUE,
#                         layoutAlgorithm = "squarified") %>% 
#   hc_add_theme(thm)


df.imports%>%
  group_by(country)%>%
  summarise(value = sum(value))%>%
  arrange(desc(value))%>%
  top_n(20)%>%
  hchart(type = "bar", hcaes(x = country,y = value))%>%
  hc_yAxis(title = list(text = "Value in Billions"))


```