Understanding the Gaming Industry Sales.

About the Video Game Industry

A video game is an electronic game that can be played on a computing device, such as a personal computer, gaming console or mobile phone. Depending on the platform, video games can be subcategorized into computer games and console games. In recent years however, the emergence of social networks, smartphones and tablets introduced new categories such as mobile and social games. Video games have come a long way since the first games emerged in the 1970s. Today’s video games offer photorealistic graphics and simulate reality to a degree which is astonishing in many cases.

Video Game Industry - Estimated Growth Projection

Market research firm Newzoo revealed today that it expects the global gaming market to be worth $99.6 billion in 2016. That’s up 8.4 percent when compared to last year. It also expects 2016 to be the first year that mobile overtakes PC and console, with Newzoo expecting that market to make $36.9 billion in 2016, up 21.3 percent from 2015.

Forty-seven percent of that $99.6 billion will come from Asia, as you can see in the chart below. China is seeing exceptional growth. Mobile in that country will be up 41 percent from 2015 to reach $10 billion. Newzoo notes 58 percent of total gaming growth in the worldwide market in 2016 will come from the Asia-Pacific region

About the Data

The dataset was downloaded from Kaggle. The dataset was originally generated from http://www.vgchartz.com/. The variables of the dataset are:

  • Rank - Ranking of overall sales

  • Name - The games name

  • Platform - Platform of the games release (i.e. PC,PS4, etc.)

  • Year - Year of the game’s release

  • Genre - Genre of the game

  • Publisher - Publisher of the game

  • NA_Sales - Sales in North America (in millions)

  • EU_Sales - Sales in Europe (in millions)

  • JP_Sales - Sales in Japan (in millions)

  • Other_Sales - Sales in the rest of the world (in millions)

  • Global_Sales - Total worldwide sales.

vgsales <- read.csv("/users/sharanbhamra/Desktop/SOC 712/vgsales.csv") 
head(vgsales)
Video Game Releases by Year
ggplot(vgsales, aes(Year)) + 
  geom_bar(fill = "green") +
  ggtitle("Video Game Releases by Year")

Understanding what consoles are most games realesed.
ggplot(data = vgsales) + 
  geom_bar(mapping = aes(x = Platform , fill = Platform),
    show.legend = FALSE,
    width = NULL
  ) +        
  theme(aspect.ratio = 1) +
  labs(x = NULL, y = NULL) +
  coord_flip() +
  ggtitle("Game Consoles")

Sales of the Video Games by Genre
v.sales<- vgsales %>%
  filter(Platform %in% c("X360", "Wii", "PSP", "PS3", "PS2","DS", "PS", "PC"))
ggplot(data=v.sales, aes(x=Genre, y=Global_Sales, fill=Platform)) + 
  stat_summary(fun.y=sum, geom="bar", position="stack") +
  coord_flip() +
  ggtitle("Global Sales in millions by Genre")

ggplot(data=v.sales, aes(x=Genre, y=NA_Sales, fill=Platform)) + 
  stat_summary(fun.y=sum, geom="bar", position="stack") +
  coord_flip() +
  ggtitle("North-America Total Sales in millions by Genre")

ggplot(data=v.sales, aes(x=Genre, y=EU_Sales, fill=Platform)) + 
  stat_summary(fun.y=sum, geom="bar", position="stack") +
  coord_flip() +
  ggtitle("Europe Total Sales in millions by Genre")

ggplot(data=v.sales, aes(x=Genre, y=JP_Sales, fill=Platform)) + 
  stat_summary(fun.y=sum, geom="bar", position="stack") +
  coord_flip() +
  ggtitle("Japan Total Sales in millions by Genre")

ggplot(data=v.sales, aes(x=Genre, y=Other_Sales, fill=Platform)) + 
  stat_summary(fun.y=sum, geom="bar", position="stack") +
  coord_flip() +
  ggtitle("Sales in the rest of the world in millions by Genre")

Yearly Released Video Games
v2 <- vgsales %>% 
  group_by(Year, Genre) %>% 
  summarize(released = n())

ggplot(v2, aes(x=Genre, y = released, fill=Genre)) +
  geom_boxplot() + theme(legend.position="none") +
  coord_flip() +
  ggtitle("Yearly Released Videogames split on Genre")

Yearly Sales by Publisher of Top 20 Publishers
ys <- vgsales %>% group_by(Publisher) %>% 
  summarize(P_NA = sum(NA_Sales),
            P_EU = sum(EU_Sales),
            P_JP = sum(JP_Sales),
            P_Other = sum(Other_Sales),
            P_Global = sum(Global_Sales)) %>% arrange(desc(P_Global))

ggplot(ys[1:20,], aes(x=Publisher, y=P_NA, fill=Publisher)) +
  geom_bar(stat="identity") + 
  theme(legend.position="none") +
  coord_flip() +
  ggtitle("Video Games North America Sales in millions")

ggplot(ys[1:20,], aes(x=Publisher, y=P_EU, fill=Publisher)) +
  geom_bar(stat="identity") + 
  theme(legend.position="none") +
  coord_flip() +
  ggtitle("Video Games Europe Sales in millions")

ggplot(ys[1:20,], aes(x=Publisher, y=P_JP, fill=Publisher)) +
  geom_bar(stat="identity") + 
  theme(legend.position="none") +
  coord_flip() +
  ggtitle("Video Games Japan Sales in millions")

ggplot(ys[1:20,], aes(x=Publisher, y=P_Other, fill=Publisher)) +
  geom_bar(stat="identity") + 
  theme(legend.position="none") +
  coord_flip() +
  ggtitle("Video Games Other Sales in millions")

ggplot(ys[1:20,], aes(x=Publisher, y=P_Global, fill=Publisher)) +
  geom_bar(stat="identity") + 
  theme(legend.position="none") +
  coord_flip() +
  ggtitle("Video Games Global Sales in millions")

Conclusion

The above data will be good to understand the video game industry. Such data can be useful to a marketing department of a video game company, who wants to understand the sales generated by diffrent genre of video games by what consoles. This data can also be useful to make projections about the new games coming in the industry and how likely are they to perform in the industry. One can also understand the trends of the competitor.