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ggplot and the GRAMMAR OF GRAPHICS MAPPING vs SETTING AESTHETICS - - PowerPoint PPT Presentation
ggplot and the GRAMMAR OF GRAPHICS MAPPING vs SETTING AESTHETICS - - PowerPoint PPT Presentation
ggplot and the GRAMMAR OF GRAPHICS MAPPING vs SETTING AESTHETICS p <- ggplot (data = gapminder, mapping = aes (x = gdpPercap, y = lifeExp, color = "purple")) p + geom_point () + geom_smooth (method = "loess") +
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p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp, color = "purple")) p + geom_point() + geom_smooth(method = "loess") + scale_x_log10()
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What has gone wrong here?
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p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp) p + geom_point(color = "purple") + geom_smooth(method = "loess")) + scale_x_log10()
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p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) p + geom_point(alpha = 0.3) + geom_smooth(color = "orange", se = FALSE, size = 2, method = "lm") + scale_x_log10()
Here, some elements are mapped to variables, while others are set to values geom functions can take many different arguments
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p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp, color = continent, fill = continent)) p + geom_point() + geom_smooth(method = "loess") + scale_x_log10()
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MAP or SET AESTHETICS per geom
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p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) p + geom_point(mapping = aes(color = continent)) + geom_smooth(method = "loess") + scale_x_log10()
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PAY CLOSE ATTENTION TO WHICH SCALES AND GUIDES ARE DRAWN, AND WHY THAT HAPPENS
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p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp, color = continent, fill = continent)) p + geom_point() + geom_smooth(method = "loess") + scale_x_log10()
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p <- ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) p + geom_point(mapping = aes(color = continent)) + geom_smooth(method = "loess") + scale_x_log10()
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REMEMBER: EVERY MAPPED VARIABLE HAS A SCALE
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IMPLEMENTS A GRAMMAR OF GRAPHICS ggplot
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The grammar is a set of rules for how produce graphics from data, taking pieces of data and mapping them to geometric objects (like points and lines) that have aesthetic attributes (like position, color and size), together with further rules for transforming the data if needed, adjusting scales, or projecting the results onto a coordinate system.
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Like other rules of syntax, the grammar limits what you can validly say, but it doesn’t make what you say sensible or meaningful.
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Grouped Data and the group aesthetic
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p <- ggplot(data = gapminder, mapping = aes(x = year, y = gdpPercap)) p + geom_line()
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p <- ggplot(data = gapminder, mapping = aes(x = year, y = gdpPercap)) p + geom_line(mapping = aes(group = country))
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p <- ggplot(data = gapminder, mapping = aes(x = year, y = gdpPercap)) p + geom_line(mapping = aes(group = country)) + facet_wrap(~ continent)
A facet is not a
- geom. It’s a way
- f arranging geoms.
Facets use R’s ‘formula’ syntax. Read the ~ as “on” or “by”.
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p + geom_line(color = "gray70", mapping = aes(group = country)) + geom_smooth(size = 1.1, method = "loess", se = FALSE) + scale_y_log10(labels=scales::dollar) + facet_wrap(~ continent, ncol = 5) + labs(x = "Year", y = "GDP per capita", title = "GDP per capita on Five Continents")
The labs() function lets you name labels, title, subtitle, etc.
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