---
title: "Flex Dashboards"
Author : Dhela Asafiani Agatha (20214920009)
output: 
  flexdashboard::flex_dashboard:
    vertical_layout: scroll
    theme: yeti
    source_code: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
library(highcharter)
library(gtable)
library(htmltools)
library(viridis)
library(DT)
library(flexdashboard)
library(shiny)
# From Github
#install.packages("devtools")
#devtools::install_github("dreamRs/shinyWidgets")
library(shinyWidgets)
library(shinyjs)

```


```{r}
# Importing data
library(dplyr)
library(plotly)
library(tidyverse)
df <- read.csv('sales_data_sample.csv')

# Removing duplicates
df <- df %>% 
  distinct(COUNTRY, .keep_all = TRUE) %>% 
  rename(Country = 'COUNTRY')
```


Table {data-orientation=rows}
=======================================================================

### Table {data-height=520}

```{r}
# This is going to be a datatable
df1 <- df %>% 
  filter(Country >= 5 ) %>% 
  arrange(desc(ORDERDATE)) %>% 
  select(Country, QUANTITYORDERED,STATUS, SALES, YEAR_ID, ORDERDATE)


datatable(df1, 
          options=list(scrollX=TRUE),
          caption = htmltools::tags$caption(
    style = 'caption-side: bottom; text-align: center;',
    '', htmltools::em('')
  ))
```

Bar-chart {data-orientation=rows}
=======================================================================


## Column {.tabset .tabset-fade data-height=520}
-----------------------------------------------------------------------

```{r fig.height=5}
# Colors
custom_colors <- viridis::turbo(n = 15)

# Most popular authors by reviews
df %>% 
  group_by(Country) %>% 
  summarise(SALES = sum(SALES)) %>% 
  arrange(desc(SALES)) %>% 
  head(15) %>% 
  hchart('column', hcaes(x = Country, y = SALES,color = custom_colors)) %>%   hc_add_theme(hc_theme_google()) %>% 
  hc_tooltip(pointFormat = '<b>Number of Reviews: </b> {point.y} <br>') %>% 
  hc_title(text = 'Top Sales in Many Country',
           style = list(fontSize = '25px', fontWeight = 'bold')) %>% 
  hc_subtitle(text = 'By Number of Reviews',
              style = list(fontSize = '16px')) %>% 
  hc_credits(enabled = TRUE, text = '@dhelaagatha')
  

```



Donut-chart {data-orientation=rows}
=======================================================================

## Row  
-----------------------------------------------------------------------

```{r fig.height=5}
data1 <- read.csv('sales_data_sample.csv')

# Colors
custom_colors <- viridis::inferno(n = 7)

# Most popular artists by weeks on board
data1 %>% 
  group_by(PRODUCTLINE) %>% 
  summarise(QUANTITYORDERED = sum(QUANTITYORDERED)) %>% 
  arrange(desc(QUANTITYORDERED)) %>% 
  head(10) %>% 
  hchart('pie', hcaes(x = PRODUCTLINE, y = QUANTITYORDERED, color = custom_colors),innerSize = 200) %>% 
  hc_add_theme(hc_theme_google()) %>% 
  hc_tooltip(pointFormat = '<b>Number of Weeks on Board: </b> {point.y} <br>') %>% 
  hc_title(text = 'MOST POPULAR PRODUCTLINE',
           style = list(fontSize = '25px', fontWeight = 'bold')) %>% 
  hc_subtitle(text = 'By Number of QUANTITYORDERED',
              style = list(fontSize = '16px')) %>% 
  hc_credits(enabled = TRUE, text = '@dhelaagatha')
```

Bar-chart {data-orientation=rows}
=======================================================================


## Column {.tabset .tabset-fade data-height=520}
-----------------------------------------------------------------------

```{r}
df %>% 
  count(TERRITORY) %>% 
  mutate(TERRITORY = fct_reorder(TERRITORY, n)) %>% 
  plot_ly(x = ~TERRITORY, y = ~n, color = ~TERRITORY, type = "bar") %>%
  layout(title = 'Frequency of Sales from its Territory',
         xaxis = list(showgrid = FALSE),
         yaxis = list(title = 'Frequency',showgrid = FALSE),
         showlegend = FALSE)
```

Line-chart {data-orientation=rows}
=======================================================================


## Column {.tabset .tabset-fade data-height=520}
-----------------------------------------------------------------------

```{r}
df2 <- df %>% 
  distinct(YEAR_ID, .keep_all = TRUE) %>% 
  rename(YEAR_ID = 'YEAR_ID')

fig <- plot_ly(df2, x = ~YEAR_ID, y = ~QUANTITYORDERED,color= ~QUANTITYORDERED, name = "Gaps", type = 'scatter', mode = 'lines') %>%
   layout(title = 'TOTAL QUANTITY ORDERED BY YEAR',
         xaxis = list(showgrid = FALSE),
         yaxis = list(title = 'Quantity Ordered',showgrid = FALSE),
         showlegend = FALSE)

fig
```