22 lines
970 B
Plaintext
22 lines
970 B
Plaintext
Year.Release <- game$Year.Release
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counts <- data.frame(table(Year.Release))
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p <- game %>%
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select(Year.Release, Global.Sales) %>%
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group_by(Year.Release) %>%
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summarise(Total.Sales = sum(Global.Sales))
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q <- cbind.data.frame(p, counts[2]) # Add counts to data frame
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names(q)[3] <- "count"
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q$count <- as.numeric(q$count)
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ggplot(q, aes(x = Year.Release, y = Total.Sales, label = q$count)) +
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geom_col(fill = "green") +
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geom_point(y = q$count * 500000, size = 3, shape = 21, fill = "Yellow" ) +
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geom_text(y = (q$count + 50) * 500000) + # Position of the text: count of games each year
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theme(axis.text.x = element_text(angle = 90),
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panel.background = element_rect(fill = "purple"),
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panel.grid.major = element_blank(),
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panel.grid.minor = element_blank()) +
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scale_x_discrete("Year.Release", labels = as.character(Year.Release), breaks = Year.Release)
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# From https://gexijin.github.io/learnR/the-game-sales-dataset.html#analysis-of-sales
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