ggplot guidance. For users who are new to ggplot2., Summaries of Statistics

Download ggplot guidance. For users who are new to ggplot2. and more Summaries Statistics in PDF only on Docsity! Data visualization with ggplot2 : : CHEATSHEET ggplot2 is based on the grammar of graphics, the idea that you can build every graph from the same components: a data set, a coordinate system, and geoms—visual marks that represent data points. Basics GRAPHICAL PRIMITIVES a + geom_blank() and a + expand_limits() Ensure limits include values across all plots. b + geom_curve(aes(yend = lat + 1, xend = long + 1), curvature = 1) - x, xend, y, yend, alpha, angle, color, curvature, linetype, size a + geom_path(lineend = "butt", linejoin = "round", linemitre = 1) x, y, alpha, color, group, linetype, size a + geom_polygon(aes(alpha = 50)) - x, y, alpha, color, fill, group, subgroup, linetype, size b + geom_rect(aes(xmin = long, ymin = lat, xmax = long + 1, ymax = lat + 1)) - xmax, xmin, ymax, ymin, alpha, color, fill, linetype, size a + geom_ribbon(aes(ymin = unemploy - 900, ymax = unemploy + 900)) - x, ymax, ymin, alpha, color, fill, group, linetype, size + = To display values, map variables in the data to visual properties of the geom (aesthetics) like size, color, and x and y locations. + = data geom x = F · y = A coordinate system plot data geom x = F · y = A color = F size = A coordinate system plot Complete the template below to build a graph. required ggplot(data = mpg, aes(x = cty, y = hwy)) Begins a plot that you finish by adding layers to. Add one geom function per layer. last_plot() Returns the last plot. ggsave("plot.png", width = 5, height = 5) Saves last plot as 5’ x 5’ file named "plot.png" in working directory. Matches file type to file extension. F M A F M A LINE SEGMENTS common aesthetics: x, y, alpha, color, linetype, size b + geom_abline(aes(intercept = 0, slope = 1)) b + geom_hline(aes(yintercept = lat)) b + geom_vline(aes(xintercept = long)) b + geom_segment(aes(yend = lat + 1, xend = long + 1)) b + geom_spoke(aes(angle = 1:1155, radius = 1)) a <- ggplot(economics, aes(date, unemploy)) b <- ggplot(seals, aes(x = long, y = lat)) ONE VARIABLE continuous c <- ggplot(mpg, aes(hwy)); c2 <- ggplot(mpg) c + geom_area(stat = "bin") x, y, alpha, color, fill, linetype, size c + geom_density(kernel = "gaussian") x, y, alpha, color, fill, group, linetype, size, weight c + geom_dotplot() x, y, alpha, color, fill c + geom_freqpoly() x, y, alpha, color, group, linetype, size c + geom_histogram(binwidth = 5) x, y, alpha, color, fill, linetype, size, weight c2 + geom_qq(aes(sample = hwy)) x, y, alpha, color, fill, linetype, size, weight discrete d <- ggplot(mpg, aes(fl)) d + geom_bar() x, alpha, color, fill, linetype, size, weight e + geom_label(aes(label = cty), nudge_x = 1, nudge_y = 1) - x, y, label, alpha, angle, color, family, fontface, hjust, lineheight, size, vjust e + geom_point() x, y, alpha, color, fill, shape, size, stroke e + geom_quantile() x, y, alpha, color, group, linetype, size, weight e + geom_rug(sides = “bl") x, y, alpha, color, linetype, size e + geom_smooth(method = lm) x, y, alpha, color, fill, group, linetype, size, weight e + geom_text(aes(label = cty), nudge_x = 1, nudge_y = 1) - x, y, label, alpha, angle, color, family, fontface, hjust, lineheight, size, vjust one discrete, one continuous f <- ggplot(mpg, aes(class, hwy)) f + geom_col() x, y, alpha, color, fill, group, linetype, size f + geom_boxplot() x, y, lower, middle, upper, ymax, ymin, alpha, color, fill, group, linetype, shape, size, weight f + geom_dotplot(binaxis = "y", stackdir = “center") x, y, alpha, color, fill, group f + geom_violin(scale = “area") x, y, alpha, color, fill, group, linetype, size, weight both discrete g <- ggplot(diamonds, aes(cut, color)) g + geom_count() x, y, alpha, color, fill, shape, size, stroke e + geom_jitter(height = 2, width = 2) x, y, alpha, color, fill, shape, size THREE VARIABLES seals$z <- with(seals, sqrt(delta_long^2 + delta_lat^2)); l <- ggplot(seals, aes(long, lat)) l + geom_raster(aes(fill = z), hjust = 0.5, vjust = 0.5, interpolate = FALSE) x, y, alpha, fill l + geom_tile(aes(fill = z)) x, y, alpha, color, fill, linetype, size, width h + geom_bin2d(binwidth = c(0.25, 500)) x, y, alpha, color, fill, linetype, size, weight h + geom_density_2d() x, y, alpha, color, group, linetype, size h + geom_hex() x, y, alpha, color, fill, size continuous function i <- ggplot(economics, aes(date, unemploy)) visualizing error df <- data.frame(grp = c("A", "B"), fit = 4:5, se = 1:2) j <- ggplot(df, aes(grp, fit, ymin = fit - se, ymax = fit + se)) maps data <- data.frame(murder = USArrests$Murder, state = tolower(rownames(USArrests))) map <- map_data("state") k <- ggplot(data, aes(fill = murder)) k + geom_map(aes(map_id = state), map = map) + expand_limits(x = map$long, y = map$lat) map_id, alpha, color, fill, linetype, size Not required, sensible defaults supplied Geoms Use a geom function to represent data points, use the geom’s aesthetic properties to represent variables. Each function returns a layer. TWO VARIABLES both continuous e <- ggplot(mpg, aes(cty, hwy)) continuous bivariate distribution h <- ggplot(diamonds, aes(carat, price)) CC BY SA Posit Software, PBC • info@posit.co • posit.co • Learn more at ggplot2.tidyverse.org • HTML cheatsheets at pos.it/cheatsheets  • ggplot2 3.4.2 • Updated: 2023-07 ggplot (data = <DATA> ) + <GEOM_FUNCTION> (mapping = aes( <MAPPINGS> ), stat = <STAT> , position = <POSITION> ) + <COORDINATE_FUNCTION> + <FACET_FUNCTION> + <SCALE_FUNCTION> + <THEME_FUNCTION> l + geom_contour(aes(z = z)) x, y, z, alpha, color, group, linetype, size, weight l + geom_contour_filled(aes(fill = z)) x, y, alpha, color, fill, group, linetype, size, subgroup i + geom_area() x, y, alpha, color, fill, linetype, size i + geom_line() x, y, alpha, color, group, linetype, size i + geom_step(direction = "hv") x, y, alpha, color, group, linetype, size j + geom_crossbar(fatten = 2) - x, y, ymax, ymin, alpha, color, fill, group, linetype, size j + geom_errorbar() - x, ymax, ymin, alpha, color, group, linetype, size, width Also geom_errorbarh(). j + geom_linerange() x, ymin, ymax, alpha, color, group, linetype, size j + geom_pointrange() - x, y, ymin, ymax, alpha, color, fill, group, linetype, shape, size Aes color and fill - string ("red", "#RRGGBB") linetype - integer or string (0 = "blank", 1 = "solid", 2 = "dashed", 3 = "dotted", 4 = "dotdash", 5 = "longdash", 6 = "twodash") size - integer (line width in mm) shape - integer/shape name or a single character ("a") Common aesthetic values.