Load and Clear The Data

raw_data <- readRDS("car_data_aggregate.rds")
raw_data <- raw_data %>% filter(! (startsWith(brand_name, "ODD") | startsWith(brand_name, "TOPLAM")))

#ASTON MARTIN and ASTON MARTİN are same brands
raw_data$brand_name <- str_replace(raw_data$brand_name,"ASTON MARTİN","ASTON MARTIN")

10 Best Selling Car Brands in Turkey

Lets find the best selling 10 brands in Turkey. First we need to group the brands and summarize their sum of totals. After then we need to rank the data by using sum(total_total). Finally we will select 10 best selling brand and arrange them.

raw_data %>% 
  group_by(brand_name) %>% 
  summarize(sum = sum(total_total))%>%
  mutate(rank = rank(-sum)) %>%
  filter(rank <= 10) %>%
  arrange(rank)
## # A tibble: 10 x 3
##    brand_name       sum  rank
##    <chr>          <dbl> <dbl>
##  1 RENAULT       318500     1
##  2 FIAT          275900     2
##  3 FORD          271157     3
##  4 VOLKSWAGEN    262041     4
##  5 HYUNDAI       131666     5
##  6 DACIA         117978     6
##  7 OPEL          117122     7
##  8 TOYOTA        106950     8
##  9 PEUGEOT        98036     9
## 10 MERCEDES-BENZ  93944    10

BMW Sellings in Turkey (month by month)

Let’s examine bmw’s montly sales change. First we need to add new columns (date) for the chart. ggplot is used to draw the chart.

#First filter BMW data
bmw_data = raw_data %>% filter(brand_name == "BMW")

bmw_data %>%
  mutate(date = as.Date(paste(year, month, 1, sep='-'))) %>% 
  ggplot(data = ., aes(x=date, y = total_total)) + 
  labs(y = "BMW Sales", x="Months", fill="Brands") + 
  geom_text(aes(label=total_total), vjust=-0.3, size=2.5) +
  geom_bar(stat="identity", fill="steelblue")

Compare Montly Sales Of BMW, Mercedes and Audi

Let’s examine montly sales change of BMW, Mercedes and Audi. First we need to add new columns (date) for the chart. ggplot is used to draw the chart.

#First filter these brands data
luxury_data = raw_data %>% filter(brand_name %in% c("BMW", "MERCEDES-BENZ", "AUDI"))

luxury_data %>% 
  mutate(date = as.Date(paste(year, month, 1, sep='-'))) %>% 
  ggplot(data = ., aes(x = date, y = total_total, color = brand_name)) + 
  labs(y = "The Sales of Each Brands", x="Months", fill="Brands") + 
  geom_line()

Compare Annual Sales Of BMW, Mercedes and Audi

luxury_data %>% 
  group_by(brand_name, year) %>% 
  summarize(yearly_total = sum(total_total))%>%
  ggplot(data=., aes(x=year, y=yearly_total, fill=brand_name)) +
  geom_bar(stat="identity", position=position_dodge())+
  scale_fill_brewer(palette="Paired")+
  geom_text(aes(label=yearly_total), vjust=1.4, color="white", size=3.5, position = position_dodge(0.9))+
  labs(y = "The Sales of Each Brands", x="Years", fill="Brands") +
  theme_minimal()