---
title: "Retail Shop"
output: 
  flexdashboard::flex_dashboard:
    vertical_layout: fill
    theme : yeti
    source_code : embed
---

```{r setup, include=FALSE}
pacman::p_load("flexdashboard",
               "ggpubr",
               "plotly",
               "ggplot2",
               "readxl",
               "tidyverse",
               "dplyr",
               "prob",
               "scales")
```


```{r}
data <- read.csv("C:/Users/valen/Desktop/Flex_Dashboard/Tugas1/data_ecommerce.csv")
```

```{r}
new_data <- separate(data,
  col = InvoiceDate,
  into = c("Date", "Time"),
  sep = " "
)

```

```{r}
new_data_Date <- new_data %>% 
  count(Date)

new_data_Date1 <- arrange(new_data_Date, desc(n))
datetop10 <- new_data_Date1[1:20,]
```

```{r}
new_data <- separate(new_data,
  col = Date,
  into = c("Month", "Date", "Year"),
  sep = "/"
)

new_data$Price_Total = new_data$Quantity * new_data$UnitPrice

```






Transaksi by Date {data-orientation=rows}
=======================================================================

### Transaksi Berdasarkan Waktu {data-width=1200}

```{r}
ggplot(datetop10, aes(x = Date, y = n)) +
  geom_point(color = "deepskyblue",
             size = 1,
             alpha = .8) +
  theme_minimal() +
  labs(
       x = "Date",
       y = "Transaksi") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
```


France vs Others {data-orientation=rows}
=======================================================================



### Perbandingan Pendapatan Negara France Dengan Negara Lain {data-width=1200}

```{r}
Price <- new_data %>%
  count(Country)

Country = c("Australia"     ,      "Austria"             , "Bahrain"    , "Belgium"        , "Brazil"  ,
"Canada"        ,      "Channel Islands"     , "Cyprus"     , "Czech Republic" ,  "Denmark"             ,
"EIRE"          ,      "European Community"  , "Finland"    , "France"         ,  "Germany"             ,
"Greece"        ,      "Hong Kong"           , "Iceland"    , "Israel"         ,  "Italy"               ,
"Japan"         ,      "Lebanon"             , "Lithuania"  , "Malta"          ,  "Netherlands"         ,
"Norway"        ,      "Poland"              , "Portugal"   , "RSA"            ,  "Saudi Arabia"        ,
"Singapore"     ,      "Spain"               , "Sweden"     , "Switzerland"    ,  "United Arab Emirates",
"United Kingdom",      "Unspecified"         , "USA" )


pendapatan_negara = data.frame("Negara" = Country,
                               "Penghasilan" = c(137077.3, 10154.32, 548.4, 40910.96, 1143.6, 3666.38, 20086.29, 
                                                 12946.29, 707.72, 18768.14, 263276.8, 1291.75, 22326.74, 197403.9,
                                                 221698.2, 4710.52, 10117.04, 4310, 7907.82, 16890.51, 35340.62, 1693.88,
                                                 1661.06, 2505.47, 284661.5, 35163.46, 7213.14, 29367.02, 1002.31, 131.17,
                                                 9120.39, 54774.58, 36595.91, 56385.35, 1902.28, 8187806, 4749.79, 1730.92))



pendapatan = pendapatan_negara%>%
  mutate(percent = Penghasilan/sum(Penghasilan),
         pert = round(percent,2)*100)

p = subset(pendapatan, subset = Negara!= "France")
pendapatan = data.frame("a" = c("France", "Others"),
                        "b" = c(84, sum(p$pert)))
pendapatan =pendapatan %>%
  mutate(c =cumsum(b) - 0.5*b)

ggplot(pendapatan, aes(x="", y= b, fill=a))+
  geom_bar(width=1, stat="identity", color="white") +
  coord_polar("y", start = 0) +
  geom_text(aes(y= c,label =b), color="white")+
  scale_fill_manual(values = c("purple","orange"))+
  theme_void()
```


Top 10 Negara Penjualan Terbanyak {data-orientation=rows}
=======================================================================

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

```{r}
top10 = arrange(pendapatan_negara, desc(Penghasilan))
top10 = top10[2:11,]
```

### horizontal {data-width=1200}

```{r}
ggplot(top10, 
       aes(x = reorder(Negara,Penghasilan), 
           y = Penghasilan)) +
  geom_bar(stat = "identity", 
           fill = rainbow(10)) +
  geom_text(aes(label = Penghasilan), 
            vjust = -0.25) +
  theme_minimal() +                                  
  labs(
       x = "negara",
       y = "total ($)")+ coord_flip()
```


### vertikal {data-width=1200}

```{r}
ggplot(top10, 
       aes(x = Penghasilan, 
           y = reorder(Negara,Penghasilan))) +
  geom_bar(stat = "identity", 
           fill = rainbow(10)) +
  geom_text(aes(label = Penghasilan), 
            vjust = -0.25) +
  theme_minimal() +                                  
  labs(
       x = "total",
       y = "negara")+ coord_flip()
```


Banyaknya Transaksi Per Bulan {data-orientation=rows}
=======================================================================

### Banyaknya Transaksi Per Bulannya

```{r}
jeki = new_data %>%
  group_by(InvoiceNo, Year, Month)%>%
  dplyr::summarise(n= n())

```
```{r}
t_2010 = subset(jeki, subset= Year == 2010)
t_2011 = setdiff(jeki, t_2010)

library(plyr)
a = count(t_2011, "Month")   
b = count(t_2010, "Month")

a$Year = 2011
b$Year = 2010

jeki = rbind(a,b)
```

```{r}
ggplot(jeki,
       aes(x = reorder(Month,-freq),
           y = freq)) +
  geom_bar(stat = "identity",
           fill = rainbow(13),
           color= "azure4") +
  geom_text(aes(label = freq),
            vjust = -0.25) +
  theme_minimal()+
  labs(x = "Bulan",
       y = "Jumlah Transaksi") +
  theme(axis.text.x = element_text(angle=30, hjust = 1))
```