From a27e69c976509b4af5c9866e4e3e8dc0c0e8b67a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mine=20=C3=87etinkaya-Rundel?= Date: Thu, 30 May 2024 23:58:55 -0400 Subject: [PATCH] Update layout to bslib --- .../execute-results/html.json | 8 +- _freeze/html/shiny/execute-results/html.json | 4 +- html/images/logo-shiny.png | Bin 24710 -> 24710 bytes html/shiny.qmd | 107 ++++++------------ keynotes/shiny.key | Bin 10117059 -> 10198624 bytes shiny.pdf | Bin 1288343 -> 1294279 bytes 6 files changed, 41 insertions(+), 78 deletions(-) diff --git a/_freeze/html/data-visualization/execute-results/html.json b/_freeze/html/data-visualization/execute-results/html.json index 908b2f00..5ae67afb 100644 --- a/_freeze/html/data-visualization/execute-results/html.json +++ b/_freeze/html/data-visualization/execute-results/html.json @@ -1,9 +1,11 @@ { - "hash": "3a3bc073f43b39c6874b4ccf230fe462", + "hash": "c8acd89d048d336f7a03d3ca847dd6a8", "result": { "engine": "knitr", - "markdown": "---\ntitle: \"Data visualization with ggplot2 :: Cheat Sheet\"\ndescription: \" \"\nexecute:\n eval: true\n output: false\n warning: false\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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\n* Chinese\n* Dutch\n* French\n* German\n* Japanese\n* Portuguese\n* Spanish\n* Turkish\n* Vietnamese\n:::\n\n\n\n\n\n## Basics\n\n**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.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(ggplot2)\n```\n:::\n\n\n\n\n\nTo display values, map variables in the data to visual properties of the geom (**aesthetics**) like **size**, **color**, and **x** and **y** locations.\n\nComplete the template below to build a graph.\n\n``` \nggplot(data = ) +\n (mapping = aes(),\n stat = ,\n position = ) +\n +\n +\n +\n \n```\n\nData, a Geom Function, and Aes Mappings are required.\nStat, Position, and the Coordinate, Facet, Scale, and Theme functions are not required and will supply sensible defaults.\n\n- `ggplot(data = mpg, aes(x = cty, y = hwy))`: Begins a plot that you finish by adding layers to.\n Add one geom function per layer.\n\n- `last_plot()`: Returns the last plot.\n\n- `ggsave(\"plot.png\", width = 5, height = 5)`: Saves last plot as 5' x 5' file named \"plot.png\" in working directory.\n Matches file type to file extension.\n\n## Aes\n\nCommon aesthetic values.\n\n- `color` and `fill`: String (`\"red\"`, `\"#RRGGBB\"`).\n\n- `linetype`: Integer or string (0 = `\"blank\"`, 1 = `\"solid\"`, 2 = `\"dashed\"`, 3 = `\"dotted\"`, 4 = `\"dotdash\"`, 5 = `\"longdash\"`, 6 = `\"twodash\"`).\n\n- `size`: Integer (in mm for size of points and text).\n\n- `linewidth`: Integer (in mm for widths of lines).\n\n- `shape`: Integer/shape name or a single character (`\"a\"`).\n\n - `shape` integer/name pairs: 0 = `\"square open\"`, 1 = `\"circle open\"`, 2 = `\"triangle open\"`, 3 = `\"plus\"`, 4 = `\"cross\"`, 5 = `\"diamond open\"`, 6 = `\"triangle down open\"`, 7 = `\"square cross\"`, 8 = `\"asterisk\"`, 9 = `\"diamond plus\"`, 10 = `\"circle plus\"`, 11 = `\"star\"`, 12 = `\"square plus\"`, 13 = `\"circle cross\"`, 14 = `\"square triangle\"`, 15 = `\"square\"`, 16 = `\"circle\"`, 17 = `\"triangle\"`, 18 = `\"diamond\"`, 19 = `\"circle small\"`, 20 = `\"bullet\"`, 21 = `\"circle filled\"`, 22 = `\"square filled\"`, 23 = `\"diamond filled\"`, 24 = `\"triangle filled\"`, 25 = `\"triangle down filled\"`\n\n## Geoms\n\nUse a geom function to represent data points, use the geom's aesthetic properties to represent variables.\nEach function returns a layer.\n\n### Graphical Primitives\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\na <- ggplot(economics, aes(date, unemploy))\n\nb <- ggplot(seals, aes(x = long, y = lat))\n```\n:::\n\n\n\n- `a + geom_blank()` and `a + expand_limits()`: Ensure limits include values across all plots.\n\n- `b + geom_curve(aes(yend = lat + 1, xend = long + 1), curvature = 1)`: Draw a curved line from `(x, y)` to `(xend, yend)`.\n `aes()` arguments: `x`, `xend`, `y`, `yend`, `alpha`, `angle`, `color`, `curvature`, `linetype`, `size`.\n\n- `a + geom_path(lineend = \"butt\", linejoin = \"round\", linemitre = 1)`: Connect observations in the order they appear.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `size`.\n\n- `a + geom_polygon(aes(alpha = 50))`: Connect points into polygons.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `subgroup`, `linetype`, `size`.\n\n- `b + geom_rect(aes(xmin = long, ymin = lat, xmax = long + 1, ymax = lat + 1))`: Draw a rectangle by connecting four corners (`xmin`, `xmax`, `ymin`, `ymax`).\n `aes()` arguments: `xmax`, `xmin`, `ymax`, `ymin`, `alpha`, `color`, `fill`, `linetype`, `size`.\n\n- `a + geom_ribbon(aes(ymin = unemploy - 900, ymax = unemploy + 900)`: For each `x`, plot an interval from `ymin` to `ymax`.\n `aes()` arguments: `x`, `ymax`, `ymin`, `alpha`, `color`, `fill`, `group`, `linetype`, `size`.\n\n#### Line Segments\n\nCommon aesthetics: `x`, `y`, `alpha`, `color`, `linetype`, `size`, `linewidth`.\n\n- `b + geom_abline(aes(intercept = 0, slope = 1))`: Draw a diagonal reference line with a given `slope` and `intercept`.\n\n- `b + geom_hline(aes(yintercept = lat))`: Draw a horizontal reference line with a given `yintercept`.\n\n- `b + geom_vline(aes(xintercept = long))`: Draw a vertical reference line with a given `xintercept`.\n\n- `b + geom_segment(aes(yend = lat + 1, xend = long + 1))`: Draw a straight line from `(x, y)` to `(xend, yend)`.\n\n- `b + geom_spoke(aes(angle = 1:1155, radius = 1))`: Draw line segments using polar coordinates (`angle` and `radius`).\n\n### One Variable - Continuous\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nc <- ggplot(mpg, aes(hwy))\nc2 <- ggplot(mpg)\n```\n:::\n\n\n\n- `c + geom_area(stat = \"bin\")`: Draw an area plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `linewidth`.\n\n- `c + geom_density(kernel = \"gaussian\")`: Compute and draw kernel density estimates.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`, `weight`.\n\n- `c + geom_dotplot()`: Draw a dot plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`.\n\n- `c + geom_freqpoly()`: Draw a frequency polygon.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n- `c + geom_histogram(binwidth = 5)`: Draw a histogram.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `linewidth`, `weight`.\n\n- `c2 + geom_qq(aes(sample = hwy))`: Draw a quantile-quantile plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `size`, `weight`.\n\n### One Variable - Discrete\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nd <- ggplot(mpg, aes(fl))\n```\n:::\n\n\n\n- `d + geom_bar()`: Draw a bar chart. `aes()` arguments: `x`, `alpha`, `color`, `fill`, `linetype`, `linewidth`, `weight`.\n\n### Two Variables - Both Continuous\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ne <- ggplot(mpg, aes(cty, hwy))\n```\n:::\n\n\n\n- `e + geom_label(aes(label = cty), nudge_x = 1, nudge_y = 1)`: Add text with a rectangle background.\n `aes()` arguments: - `x`, `y`, `label`, `alpha`, `angle`, `color`, `family`, `fontface`, `hjust`, `lineheight`, `size`, `vjust`.\n\n- `e + geom_point()`: Draw a scatter plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `shape`, `size`, `stroke`.\n\n- `e + geom_quantile()`: Fit and draw quantile regression for the plot data.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`, `weight`.\n\n- `e + geom_rug(sides = \"bl\")`: Draw a rug plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `linetype`, `linewidth`.\n\n- `e + geom_smooth(method = lm)`: Plot smoothed conditional means.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`, `weight`.\n\n- `e + geom_text(aes(label = cty), nudge_x = 1, nudge_y = 1)`: Add text to a plot.\n `aes()` arguments: `x`, `y`, `label`, `alpha`, `angle`, `color`, `family`, `fontface`, `hjust`, `lineheight`, `size`, `vjust`.\n\n### Two Variables - One Discrete, One Continuous\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nf <- ggplot(mpg, aes(class, hwy))\n```\n:::\n\n\n\n- `f + geom_col()`: Draw a bar plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`.\n\n- `f + geom_boxplot()`: Draw a box plot.\n `aes()` arguments: `x`, `y`, `lower`, `middle`, `upper`, `ymax`, `ymin`, `alpha`, `color`, `fill`, `group`, `linetype`, `shape`, `linewidth`, `weight`.\n\n- `f + geom_dotplot(binaxis =\"y\", stackdir = \"center\")`: Draw a dot plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`.\n\n- `f + geom_violin(scale = \"area\")`: Draw a violin plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`, `weight`.\n\n### Two Variables - Both Discrete\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ng <- ggplot(diamonds, aes(cut, color))\n```\n:::\n\n\n\n- `g + geom_count()`: Plot a count of points in an area to address over plotting.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `shape`, `size`, `stroke`.\n\n- `e + geom_jitter(height = 2, width = 2)`: Jitter points in a plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `shape`, `size`.\n\n### Two Variables - Continuous Bivariate Distribution\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nh <- ggplot(diamonds, aes(carat, price))\n```\n:::\n\n\n\n- `h + geom_bin2d(binwidth = c(0.25, 500))`: Draw a heatmap of 2D rectangular bin counts.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `size`, `weight`.\n\n- `h + geom_density_2d()`: Plot contours from 2D kernel density estimation.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n- `h + geom_hex()`: Draw a heatmap of 2D hexagonal bin counts.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linewidth`.\n\n### Two Variables - Continuous Function\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ni <- ggplot(economics, aes(date, unemploy))\n```\n:::\n\n\n\n- `i + geom_area()`: Draw an area plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `linewidth`.\n\n- `i + geom_line()`: Connect data points, ordered by the x axis variable.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n- `i + geom_step(direction = \"hv\"`: Draw a stairstep plot. `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n### Two Variables - Visualizing Error\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndf <- data.frame(grp = c(\"A\", \"B\"), fit = 4:5, se = 1:2)\nj <- ggplot(df, aes(grp, fit, ymin = fit - se, ymax = fit + se))\n```\n:::\n\n\n\n- `j + geom_crossbar(fatten = 2)`: Draw a crossbar.\n `aes()` arguments: `x`, `y`, `ymax`, `ymin`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`.\n\n- `j + geom_errorbar()`: Draw an errorbar.\n Also `geom_errorbarh()`.\n `aes()` arguments: `x`, `ymax`, `ymin`, `alpha`, `color`, `group`, `linetype`, `linewidth`, `width`.\n\n- `j + geom_linerange()`: Draw a line range.\n `aes()` arguments: `x`, `ymin`, `ymax`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n- `j + geom_pointrange()`: Draw a point range.\n `aes()` arguments: `x`, `y`, `ymin`, `ymax`, `alpha`, `color`, `fill`, `group`, `linetype`, `shape`, `linewidth`.\n\n### Two Variables - Maps\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nmurder_data <- data.frame(\n murder = USArrests$Murder, \n state = tolower(rownames(USArrests))\n)\nmap <- map_data(\"state\")\nk <- ggplot(murder_data, aes(fill = murder))\n```\n:::\n\n\n\n- `k + geom_map(aes(map_id = state), map = map) + expand_limits(x = map$long, y = map$lat)`: Draw polygons as a map. `aes()` arguments: `map_id`, `alpha`, `color`, `fill`, `linetype`, `linewidth`.\n\n### Three Variables\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nseals$z <- with(seals, sqrt(delta_long^2 + delta_lat^2))\nl <- ggplot(seals, aes(long, lat))\n```\n:::\n\n\n\n- `l + geom_contour(aes(z = z))`: Draw 2D contour plot.\n `aes()` arguments: `x`, `y`, `z`, `alpha`, `color`, `group`, `linetype`, `linewidth`, `weight`.\n\n- `l + geom_contour_filled(aes(fill = z))`: Draw 2D contour plot with the space between lines filled.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`, `subgroup`.\n\n- `l + geom_raster(aes(fill = z), hjust = 0.5, vjust = 0.5, interpolate = FALSE)`: Draw a raster plot.\n `aes()` arguments: `x`, `y`, `alpha`, `fill`.\n\n- `l + geom_tile(aes(fill = z))`: Draw a tile plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `linewidth`, `width`.\n\n\n\n## Stats\n\nAn alternative way to build a layer.\n\nA stat builds new variables to plot (e.g., count, prop).\n\nVisualize a stat by changing the default stat of a geom function, `geom_bar(stat = \"count\")`, or by using a stat function, `stat_count(geom = \"bar\")`, which calls a default geom to make a layer (equivalent to a geom function).\nUse `after_stat(name)` syntax to map the stat variable `name` to an aesthetic.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ni + stat_density_2d(aes(fill = after_stat(level)), geom = \"polygon\")\n```\n:::\n\n\n\nIn this example, `\"polygon\"` is the geom to use, `stat_density_2d()` is the stat function, `aes()` contains the geom mappings, and `level` is the variable created by stat.\n\n- `c + stat_bin(binwidth = 1, boundary = 10)`: `x`, `y` \\| `count`, `ncount`, `density`, `ndensity`\n\n- `c + stat_count(width = 1)`: `x`, `y` \\| `count`, `density`\n\n- `c + stat_density(adjust = 1, kernel = \"gaussian\")`: `x`, `y` \\| `count`, `density`, `scaled`\n\n- `e + stat_bin_2d(bins = 30, drop = T)`: `x`, `y`, `fill` \\| `count`, `density`\n\n- `e + stat_bin_hex(bins =30)`: `x`, `y`, `fill` \\| `count`, `density`\n\n- `e + stat_density_2d(contour = TRUE, n = 100)`: `x`, `y`, `color`, `linewidth` \\| `level`\n\n- `e + stat_ellipse(level = 0.95, segments = 51, type = \"t\")`\n\n- `l + stat_contour(aes(z = z))`: `x`, `y`, `z`, `order` \\| `level`\n\n- `l + stat_summary_hex(aes(z = z), bins = 30, fun = max)`: `x`, `y`, `z`, `fill` \\| `value`\n\n- `l + stat_summary_2d(aes(z = z), bins = 30, fun = mean)`: `x`, `y`, `z`, `fill` \\| `value`\n\n- `f + stat_boxplot(coef = 1.5)`: `x`, `y` \\| `lower`, `middle`, `upper`, `width`, `ymin`, `ymax`\n\n- `f + stat_ydensity(kernel = \"gaussian\", scale = \"area\")`: `x`, `y` \\| `density`, `scaled`, `count`, `n`, `violinwidth`, `width`\n\n- `e + stat_ecdf(n = 40)`: `x`, `y` \\| `x`, `y`\n\n- `e + stat_quantile(quantiles = c(0.1, 0.9), formula = y ~ log(x), method = \"rq\")`: `x`, `y` \\| `quantile`\n\n- `e + stat_smooth(method = \"lm\", formula = y ~ x, se = T, level = 0.95)`: `x`, `y` \\| `se`, `x`, `y`, `ymin`, `ymax`\n\n- `ggplot() + xlim(-5, 5) + stat_function(fun = dnorm, n = 20, geom = \"point\")`: `x` \\| `x`, `y`\n\n- `ggplot() + stat_qq(aes(sample = 1:100))`: `x`, `y`, `sample` \\| `sample`, `theoretical`\n\n- `e + stat_sum()`: `x`, `y`, `size` \\| `n`, `prop`\n\n- `e + stat_summary(fun.data = \"mean_cl_boot\")`\n\n- `h + stat_summary_bin(fun = \"mean\", geom = \"bar\")`\n\n- `e + stat_identity()`\n\n- `e + stat_unique()`\n\n## Scales\n\nOverride defaults with **scales** package.\n\n**Scales** map data values to the visual values of an aesthetic.\nTo change a mapping, add a new scale.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nn <- d + geom_bar(aes(fill = fl))\n\nn + scale_fill_manual(\n value = c(),\n limits = c(), \n breaks = c(),\n name = \"fuel\", \n labels = c(\"D\", \"E\", \"P\", \"R\")\n)\n```\n:::\n\n\n\nIn this example, `scale_` specifies a scale function, `fill` is the aesthetic to adjust, and `manual` is the prepackaged scale to use.\n\n`values` contains scale-specific arguments, `limits` specifies the range of values to include in mappings, `breaks` specifies the breaks to use in legend/axis, and `name` and `labels` specify the title and labels to use in the legend/axis.\n\n### General Purpose Scales\n\nUse with most aesthetics.\n\n- `scale_*_continuous()`: Map continuous values to visual ones.\n\n- `scale_*_discrete()`: Map discrete values to visual ones.\n\n- `scale_*_binned()`: Map continuous values to discrete bins.\n\n- `scale_*_identity()`: Use data values as visual ones.\n\n- `scale_*_manual(values = c())`: Map discrete values to manually chosen visual ones.\n\n- `scale_*_date(date_labels = \"%m/%d\", date_breaks = \"2 weeks\")`: Treat data values as dates.\n\n- `scale_*_datetime()`: Treat data values as date times.\n Same as `scale_*_date()`.\n See `?strptime` for label formats.\n\n### X & Y Location Scales\n\nUse with x or y aesthetics (x shown here).\n\n- `scale_x_log10()`: Plot `x` on log10 scale.\n\n- `scale_x_reverse()`: Reverse the direction of the x axis.\n\n- `scale_x_sqrt()`: Plot `x` on square root scale.\n\n### Color and Fill Scales (Discrete)\n\n- `n + scale_fill_brewer(palette = \"Blues\")`: Use color scales from ColorBrewer.\n For palette choices `RColorBrewer::display.brewer.all()`.\n\n- `n + scale_fill_grey(start = 0.2, end = 0.8, na.value = \"red\")`: Use a grey gradient color scale.\n\n### Color and Fill Scales (Continuous)\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\no <- c + geom_dotplot(aes(fill = ..x..))\n```\n:::\n\n\n\n- `o + scale_fill_distiller(palette = \"Blues\")`: Interpolate a palette into a continuous scale.\n\n- `o + scale_fill_gradient(low = \"red\", high = \"yellow\")`: Create a two color gradient.\n\n- `o + scale_fill_gradient2(low = \"red\", high = \"blue\", mid = \"white\", midpoint = 25)`: Create a diverging color gradient.\n\n- `o + scale_fill_gradientn(colors = topo.colors(6))`: Create a n-color gradient.\n Also `rainbow()`, `heat.colors()`, `terrain.colors()`, `cm.colors()`, `RColorBrewer::brewer.pal()`.\n\n### Shape and Size Scales\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- e + geom_point(aes(shape = fl, size = cyl))\n```\n:::\n\n\n\n- `p + scale_shape() + scale_size()`: Map discrete values to shape and size aesthetics.\n\n- `p + scale_shape_manual(values = c(3:7))`: Map discrete values to specified shape values.\n\n- `p + scale_radius(range = c(1,6))`: Map values to a shape's radius.\n\n- `p + scale_size_area(max_size = 6)`: Like `scale_size()` but maps zero values to zero size.\n\nShapes used here are the same as the ones listed in the Aes section.\n\n## Coordinate Systems\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nu <- d + geom_bar()\n```\n:::\n\n\n\n- `u + coord_cartesian(xlim = c(0, 5))`: `xlim`, `ylim`.\n The default Cartesian coordinate system.\n\n- `u + coord_fixed(ratio = 1/2)`: `ratio`, `xlim`, `ylim`.\n Cartesian coordinates with fixed aspect ration between x and y units.\n\n- `ggplot(mpg, aes(y = fl)) + geom_bar()`: Flip Cartesian coordinates by switching x and y aesthetic mappings.\n\n- `u + coord_polar(theta = \"x\", direction = 1)`: `theta`, `start`, `direction`.\n Polar coordinates.\n\n- `u + coord_trans(y = \"sqrt\")`: `x`, `y`, `xlim`, `ylim`.\n Transformed Cartesian coordinates.\n Set `xtrans` and `ytrans` to the name of a window function.\n\n- `π + coord_quickmap(); π + coord_map(projection = \"ortho\", orientation = c(41, -74, 0))`: `projection`, `xlim`, `ylim`.\n Map projections from the **mapproj** packages (`mercator` (default), `azequalarea`, `lagrange`, etc.).\n\n## Position Adjustments\n\nPosition adjustments determine how to arrange geoms that would otherwise occupy the same space.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ns <- ggplot(mpg, aes(fl, fill = drv))\n```\n:::\n\n\n\n- `s + geom_bar(position = \"dodge\")`: Arrange elements side by side.\n\n- `s + geom_bar(position = \"fill\")`: Stack elements on top of one another, normalize height.\n\n- `e + geom_point(position = \"jitter\")`: Add random noise to X and Y position of each element to avoid over plotting.\n\n- `e + geom_label(position = \"nudge\")`: Nudge labels away from points.\n\n- `s + geom_bar(position = \"stack\")`: Stack elements on top of one another.\n\nEach position adjustment can be recast as a function with manual `width` and `height` arguments:\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ns + geom_bar(position = position_dodge(width = 1))\n```\n:::\n\n\n\n## Themes\n\n- `u + theme_bw()`: White background with grid lines.\n\n- `u + theme_gray()`: Grey background with white grid lines (default theme).\n\n- `u + theme_dark()`: Dark grey background and grid lines for contrast.\n\n- `u + theme_classic()`: No grid lines.\n\n- `u + theme_light()`: Light grey axes and grid lines.\n\n- `u + theme_linedraw()`: Uses only black lines.\n\n- `u + theme_minimal()`: Minimal theme.\n\n- `u + theme_void()`: Empty theme.\n\n- `u + theme()`: Customize aspects of the theme such as axis, legend, panel, and facet properties.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n r + ggtitle(\"Title\") + theme(plot.title.postion = \"plot\")\n \n r + theme(panel.background = element_rect(fill = \"blue\"))\n ```\n :::\n\n\n\n## Faceting\n\nFacets divide a plot into subplots based on the values of one or more discrete variables.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nt <- ggplot(mpg, aes(cty, hwy)) + geom_point()\n```\n:::\n\n\n\n- `t + facet_grid(. ~ fl)`: Facet into a column based on fl.\n\n- `t + facet_grid(year ~ .)`: Facet into rows based on year.\n\n- `t + facet_grid(year ~ fl)`: Facet into both rows and columns.\n\n- `t + facet_wrap(~ fl)`: Wrap facets into a rectangular layout.\n\n- `t + facet_grid(drv ~ fl, scales = \"free\")`: Set **scales** to let axis limits vary across facets.\n Also `\"free_x\"` for x axis limits adjust to individual facets and `\"free_y\"` for y axis limits adjust to individual facets.\n\nSet **labeller** to adjust facet label:\n\n- `t + facet_grid(. ~ fl, labeller = label_both)`: Labels each facet as \"fl: c\", \"fl: d\", etc.\n\n- `t + facet_grid(fl ~ ., labeller = label_bquote(alpha ^ .(fl)))`: Labels each facet as \"𝛼^c^\", \"𝛼^d^\", etc.\n\n## Labels and Legends\n\nUse `labs()` to label elements of your plot.\n\n``` \nt + labs(x = \"New x axis label\", \n y = \"New y axis label\",\n title =\"Add a title above the plot\",\n subtitle = \"Add a subtitle below title\",\n caption = \"Add a caption below plot\",\n alt = \"Add alt text to the plot\",\n = \"New legend title\")\n```\n\n- `t + annotate(geom = \"text\", x = 8, y = 9, label = \"A\")`: Places a geom with manually selected aesthetics.\n\n- `p + guides(x = guide_axis(n.dodge = 2))`: Avoid crowded or overlapping labels with `guide_axis(n.dodge or angle)`.\n\n- `n + guides(fill = \"none\")`: Set legend type for each aesthetic: `colorbar`, `legend`, or `none` (no legend).\n\n- `n + theme(legend.position = \"bottom\")`: Place legend at \"bottom\", \"top\", \"left\", or \"right\".\n\n- `n + scale_fill_discrete(name = \"Title\", labels = c(\"A\", \"B\", \"C\", \"D\", \"E\"))`: Set legend title and labels with a scale function.\n\n## Zooming\n\n- `t + coord_cartesian(xlim = c(0, 100), ylim = c(10,20))`: Zoom without clipping (preferred).\n\n- `t + xlim(0, 100) + ylim(10, 20)` or `t + scale_x_continuous(limits = c(0, 100)) + scale_y_continuous(limits = c(0, 100))`: Zoom with clipping (removes unseen data points).\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [ggplot2.tidyverse.org](https://ggplot2.tidyverse.org).\n\nUpdated: 2024-05.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"ggplot2\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '3.5.1'\n```\n\n\n:::\n:::\n\n\n\n------------------------------------------------------------------------\n", - "supporting": [], + "markdown": "---\ntitle: \"Data visualization with ggplot2 :: Cheat Sheet\"\ndescription: \" \"\nexecute:\n eval: true\n output: false\n warning: false\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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\n* Chinese\n* Dutch\n* French\n* German\n* Japanese\n* Portuguese\n* Spanish\n* Turkish\n* Vietnamese\n:::\n\n\n\n\n\n## Basics\n\n**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.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(ggplot2)\n```\n:::\n\n\n\nTo display values, map variables in the data to visual properties of the geom (**aesthetics**) like **size**, **color**, and **x** and **y** locations.\n\nComplete the template below to build a graph.\n\n``` \nggplot(data = ) +\n (mapping = aes(),\n stat = ,\n position = ) +\n +\n +\n +\n \n```\n\nData, a Geom Function, and Aes Mappings are required.\nStat, Position, and the Coordinate, Facet, Scale, and Theme functions are not required and will supply sensible defaults.\n\n- `ggplot(data = mpg, aes(x = cty, y = hwy))`: Begins a plot that you finish by adding layers to.\n Add one geom function per layer.\n\n- `last_plot()`: Returns the last plot.\n\n- `ggsave(\"plot.png\", width = 5, height = 5)`: Saves last plot as 5' x 5' file named \"plot.png\" in working directory.\n Matches file type to file extension.\n\n## Aes\n\nCommon aesthetic values.\n\n- `color` and `fill`: String (`\"red\"`, `\"#RRGGBB\"`).\n\n- `linetype`: Integer or string (0 = `\"blank\"`, 1 = `\"solid\"`, 2 = `\"dashed\"`, 3 = `\"dotted\"`, 4 = `\"dotdash\"`, 5 = `\"longdash\"`, 6 = `\"twodash\"`).\n\n- `size`: Integer (in mm for size of points and text).\n\n- `linewidth`: Integer (in mm for widths of lines).\n\n- `shape`: Integer/shape name or a single character (`\"a\"`).\n\n - `shape` integer/name pairs: 0 = `\"square open\"`, 1 = `\"circle open\"`, 2 = `\"triangle open\"`, 3 = `\"plus\"`, 4 = `\"cross\"`, 5 = `\"diamond open\"`, 6 = `\"triangle down open\"`, 7 = `\"square cross\"`, 8 = `\"asterisk\"`, 9 = `\"diamond plus\"`, 10 = `\"circle plus\"`, 11 = `\"star\"`, 12 = `\"square plus\"`, 13 = `\"circle cross\"`, 14 = `\"square triangle\"`, 15 = `\"square\"`, 16 = `\"circle\"`, 17 = `\"triangle\"`, 18 = `\"diamond\"`, 19 = `\"circle small\"`, 20 = `\"bullet\"`, 21 = `\"circle filled\"`, 22 = `\"square filled\"`, 23 = `\"diamond filled\"`, 24 = `\"triangle filled\"`, 25 = `\"triangle down filled\"`\n\n## Geoms\n\nUse a geom function to represent data points, use the geom's aesthetic properties to represent variables.\nEach function returns a layer.\n\n### Graphical Primitives\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\na <- ggplot(economics, aes(date, unemploy))\n\nb <- ggplot(seals, aes(x = long, y = lat))\n```\n:::\n\n\n\n- `a + geom_blank()` and `a + expand_limits()`: Ensure limits include values across all plots.\n\n- `b + geom_curve(aes(yend = lat + 1, xend = long + 1), curvature = 1)`: Draw a curved line from `(x, y)` to `(xend, yend)`.\n `aes()` arguments: `x`, `xend`, `y`, `yend`, `alpha`, `angle`, `color`, `curvature`, `linetype`, `size`.\n\n- `a + geom_path(lineend = \"butt\", linejoin = \"round\", linemitre = 1)`: Connect observations in the order they appear.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `size`.\n\n- `a + geom_polygon(aes(alpha = 50))`: Connect points into polygons.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `subgroup`, `linetype`, `size`.\n\n- `b + geom_rect(aes(xmin = long, ymin = lat, xmax = long + 1, ymax = lat + 1))`: Draw a rectangle by connecting four corners (`xmin`, `xmax`, `ymin`, `ymax`).\n `aes()` arguments: `xmax`, `xmin`, `ymax`, `ymin`, `alpha`, `color`, `fill`, `linetype`, `size`.\n\n- `a + geom_ribbon(aes(ymin = unemploy - 900, ymax = unemploy + 900)`: For each `x`, plot an interval from `ymin` to `ymax`.\n `aes()` arguments: `x`, `ymax`, `ymin`, `alpha`, `color`, `fill`, `group`, `linetype`, `size`.\n\n#### Line Segments\n\nCommon aesthetics: `x`, `y`, `alpha`, `color`, `linetype`, `size`, `linewidth`.\n\n- `b + geom_abline(aes(intercept = 0, slope = 1))`: Draw a diagonal reference line with a given `slope` and `intercept`.\n\n- `b + geom_hline(aes(yintercept = lat))`: Draw a horizontal reference line with a given `yintercept`.\n\n- `b + geom_vline(aes(xintercept = long))`: Draw a vertical reference line with a given `xintercept`.\n\n- `b + geom_segment(aes(yend = lat + 1, xend = long + 1))`: Draw a straight line from `(x, y)` to `(xend, yend)`.\n\n- `b + geom_spoke(aes(angle = 1:1155, radius = 1))`: Draw line segments using polar coordinates (`angle` and `radius`).\n\n### One Variable - Continuous\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nc <- ggplot(mpg, aes(hwy))\nc2 <- ggplot(mpg)\n```\n:::\n\n\n\n- `c + geom_area(stat = \"bin\")`: Draw an area plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `linewidth`.\n\n- `c + geom_density(kernel = \"gaussian\")`: Compute and draw kernel density estimates.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`, `weight`.\n\n- `c + geom_dotplot()`: Draw a dot plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`.\n\n- `c + geom_freqpoly()`: Draw a frequency polygon.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n- `c + geom_histogram(binwidth = 5)`: Draw a histogram.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `linewidth`, `weight`.\n\n- `c2 + geom_qq(aes(sample = hwy))`: Draw a quantile-quantile plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `size`, `weight`.\n\n### One Variable - Discrete\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nd <- ggplot(mpg, aes(fl))\n```\n:::\n\n\n\n- `d + geom_bar()`: Draw a bar chart. `aes()` arguments: `x`, `alpha`, `color`, `fill`, `linetype`, `linewidth`, `weight`.\n\n### Two Variables - Both Continuous\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ne <- ggplot(mpg, aes(cty, hwy))\n```\n:::\n\n\n\n- `e + geom_label(aes(label = cty), nudge_x = 1, nudge_y = 1)`: Add text with a rectangle background.\n `aes()` arguments: - `x`, `y`, `label`, `alpha`, `angle`, `color`, `family`, `fontface`, `hjust`, `lineheight`, `size`, `vjust`.\n\n- `e + geom_point()`: Draw a scatter plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `shape`, `size`, `stroke`.\n\n- `e + geom_quantile()`: Fit and draw quantile regression for the plot data.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`, `weight`.\n\n- `e + geom_rug(sides = \"bl\")`: Draw a rug plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `linetype`, `linewidth`.\n\n- `e + geom_smooth(method = lm)`: Plot smoothed conditional means.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`, `weight`.\n\n- `e + geom_text(aes(label = cty), nudge_x = 1, nudge_y = 1)`: Add text to a plot.\n `aes()` arguments: `x`, `y`, `label`, `alpha`, `angle`, `color`, `family`, `fontface`, `hjust`, `lineheight`, `size`, `vjust`.\n\n### Two Variables - One Discrete, One Continuous\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nf <- ggplot(mpg, aes(class, hwy))\n```\n:::\n\n\n\n- `f + geom_col()`: Draw a bar plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`.\n\n- `f + geom_boxplot()`: Draw a box plot.\n `aes()` arguments: `x`, `y`, `lower`, `middle`, `upper`, `ymax`, `ymin`, `alpha`, `color`, `fill`, `group`, `linetype`, `shape`, `linewidth`, `weight`.\n\n- `f + geom_dotplot(binaxis =\"y\", stackdir = \"center\")`: Draw a dot plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`.\n\n- `f + geom_violin(scale = \"area\")`: Draw a violin plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`, `weight`.\n\n### Two Variables - Both Discrete\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ng <- ggplot(diamonds, aes(cut, color))\n```\n:::\n\n\n\n- `g + geom_count()`: Plot a count of points in an area to address over plotting.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `shape`, `size`, `stroke`.\n\n- `e + geom_jitter(height = 2, width = 2)`: Jitter points in a plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `shape`, `size`.\n\n### Two Variables - Continuous Bivariate Distribution\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nh <- ggplot(diamonds, aes(carat, price))\n```\n:::\n\n\n\n- `h + geom_bin2d(binwidth = c(0.25, 500))`: Draw a heatmap of 2D rectangular bin counts.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `size`, `weight`.\n\n- `h + geom_density_2d()`: Plot contours from 2D kernel density estimation.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n- `h + geom_hex()`: Draw a heatmap of 2D hexagonal bin counts.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linewidth`.\n\n### Two Variables - Continuous Function\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ni <- ggplot(economics, aes(date, unemploy))\n```\n:::\n\n\n\n- `i + geom_area()`: Draw an area plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `linewidth`.\n\n- `i + geom_line()`: Connect data points, ordered by the x axis variable.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n- `i + geom_step(direction = \"hv\"`: Draw a stairstep plot. `aes()` arguments: `x`, `y`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n### Two Variables - Visualizing Error\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndf <- data.frame(grp = c(\"A\", \"B\"), fit = 4:5, se = 1:2)\nj <- ggplot(df, aes(grp, fit, ymin = fit - se, ymax = fit + se))\n```\n:::\n\n\n\n- `j + geom_crossbar(fatten = 2)`: Draw a crossbar.\n `aes()` arguments: `x`, `y`, `ymax`, `ymin`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`.\n\n- `j + geom_errorbar()`: Draw an errorbar.\n Also `geom_errorbarh()`.\n `aes()` arguments: `x`, `ymax`, `ymin`, `alpha`, `color`, `group`, `linetype`, `linewidth`, `width`.\n\n- `j + geom_linerange()`: Draw a line range.\n `aes()` arguments: `x`, `ymin`, `ymax`, `alpha`, `color`, `group`, `linetype`, `linewidth`.\n\n- `j + geom_pointrange()`: Draw a point range.\n `aes()` arguments: `x`, `y`, `ymin`, `ymax`, `alpha`, `color`, `fill`, `group`, `linetype`, `shape`, `linewidth`.\n\n### Two Variables - Maps\n\nDraw the appropriate geometric object depending on the simple features present in the data.\n`aes()` arguments: `map_id`, `alpha`, `color`, `fill`, `linetype`, `linewidth`.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnc <- sf::st_read(system.file(\"shape/nc.shp\", package = \"sf\"))\nggplot(nc) +\n geom_sf(aes(fill = AREA))\n```\n:::\n\n\n\n### Three Variables\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nseals$z <- with(seals, sqrt(delta_long^2 + delta_lat^2))\nl <- ggplot(seals, aes(long, lat))\n```\n:::\n\n\n\n- `l + geom_contour(aes(z = z))`: Draw 2D contour plot.\n `aes()` arguments: `x`, `y`, `z`, `alpha`, `color`, `group`, `linetype`, `linewidth`, `weight`.\n\n- `l + geom_contour_filled(aes(fill = z))`: Draw 2D contour plot with the space between lines filled.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `group`, `linetype`, `linewidth`, `subgroup`.\n\n- `l + geom_raster(aes(fill = z), hjust = 0.5, vjust = 0.5, interpolate = FALSE)`: Draw a raster plot.\n `aes()` arguments: `x`, `y`, `alpha`, `fill`.\n\n- `l + geom_tile(aes(fill = z))`: Draw a tile plot.\n `aes()` arguments: `x`, `y`, `alpha`, `color`, `fill`, `linetype`, `linewidth`, `width`.\n\n\n\n## Stats\n\nAn alternative way to build a layer.\n\nA stat builds new variables to plot (e.g., count, prop).\n\nVisualize a stat by changing the default stat of a geom function, `geom_bar(stat = \"count\")`, or by using a stat function, `stat_count(geom = \"bar\")`, which calls a default geom to make a layer (equivalent to a geom function).\nUse `after_stat(name)` syntax to map the stat variable `name` to an aesthetic.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ni + stat_density_2d(aes(fill = after_stat(level)), geom = \"polygon\")\n```\n:::\n\n\n\nIn this example, `\"polygon\"` is the geom to use, `stat_density_2d()` is the stat function, `aes()` contains the geom mappings, and `level` is the variable created by stat.\n\n- `c + stat_bin(binwidth = 1, boundary = 10)`: `x`, `y` \\| `count`, `ncount`, `density`, `ndensity`\n\n- `c + stat_count(width = 1)`: `x`, `y` \\| `count`, `density`\n\n- `c + stat_density(adjust = 1, kernel = \"gaussian\")`: `x`, `y` \\| `count`, `density`, `scaled`\n\n- `e + stat_bin_2d(bins = 30, drop = T)`: `x`, `y`, `fill` \\| `count`, `density`\n\n- `e + stat_bin_hex(bins =30)`: `x`, `y`, `fill` \\| `count`, `density`\n\n- `e + stat_density_2d(contour = TRUE, n = 100)`: `x`, `y`, `color`, `linewidth` \\| `level`\n\n- `e + stat_ellipse(level = 0.95, segments = 51, type = \"t\")`\n\n- `l + stat_contour(aes(z = z))`: `x`, `y`, `z`, `order` \\| `level`\n\n- `l + stat_summary_hex(aes(z = z), bins = 30, fun = max)`: `x`, `y`, `z`, `fill` \\| `value`\n\n- `l + stat_summary_2d(aes(z = z), bins = 30, fun = mean)`: `x`, `y`, `z`, `fill` \\| `value`\n\n- `f + stat_boxplot(coef = 1.5)`: `x`, `y` \\| `lower`, `middle`, `upper`, `width`, `ymin`, `ymax`\n\n- `f + stat_ydensity(kernel = \"gaussian\", scale = \"area\")`: `x`, `y` \\| `density`, `scaled`, `count`, `n`, `violinwidth`, `width`\n\n- `e + stat_ecdf(n = 40)`: `x`, `y` \\| `x`, `y`\n\n- `e + stat_quantile(quantiles = c(0.1, 0.9), formula = y ~ log(x), method = \"rq\")`: `x`, `y` \\| `quantile`\n\n- `e + stat_smooth(method = \"lm\", formula = y ~ x, se = T, level = 0.95)`: `x`, `y` \\| `se`, `x`, `y`, `ymin`, `ymax`\n\n- `ggplot() + xlim(-5, 5) + stat_function(fun = dnorm, n = 20, geom = \"point\")`: `x` \\| `x`, `y`\n\n- `ggplot() + stat_qq(aes(sample = 1:100))`: `x`, `y`, `sample` \\| `sample`, `theoretical`\n\n- `e + stat_sum()`: `x`, `y`, `size` \\| `n`, `prop`\n\n- `e + stat_summary(fun.data = \"mean_cl_boot\")`\n\n- `h + stat_summary_bin(fun = \"mean\", geom = \"bar\")`\n\n- `e + stat_identity()`\n\n- `e + stat_unique()`\n\n## Scales\n\nOverride defaults with **scales** package.\n\n**Scales** map data values to the visual values of an aesthetic.\nTo change a mapping, add a new scale.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nn <- d + geom_bar(aes(fill = fl))\n\nn + scale_fill_manual(\n value = c(),\n limits = c(), \n breaks = c(),\n name = \"fuel\", \n labels = c(\"D\", \"E\", \"P\", \"R\")\n)\n```\n:::\n\n\n\nIn this example, `scale_` specifies a scale function, `fill` is the aesthetic to adjust, and `manual` is the prepackaged scale to use.\n\n`values` contains scale-specific arguments, `limits` specifies the range of values to include in mappings, `breaks` specifies the breaks to use in legend/axis, and `name` and `labels` specify the title and labels to use in the legend/axis.\n\n### General Purpose Scales\n\nUse with most aesthetics.\n\n- `scale_*_continuous()`: Map continuous values to visual ones.\n\n- `scale_*_discrete()`: Map discrete values to visual ones.\n\n- `scale_*_binned()`: Map continuous values to discrete bins.\n\n- `scale_*_identity()`: Use data values as visual ones.\n\n- `scale_*_manual(values = c())`: Map discrete values to manually chosen visual ones.\n\n- `scale_*_date(date_labels = \"%m/%d\", date_breaks = \"2 weeks\")`: Treat data values as dates.\n\n- `scale_*_datetime()`: Treat data values as date times.\n Same as `scale_*_date()`.\n See `?strptime` for label formats.\n\n### X & Y Location Scales\n\nUse with x or y aesthetics (x shown here).\n\n- `scale_x_log10()`: Plot `x` on log10 scale.\n\n- `scale_x_reverse()`: Reverse the direction of the x axis.\n\n- `scale_x_sqrt()`: Plot `x` on square root scale.\n\n### Color and Fill Scales (Discrete)\n\n- `n + scale_fill_brewer(palette = \"Blues\")`: Use color scales from ColorBrewer.\n For palette choices `RColorBrewer::display.brewer.all()`.\n\n- `n + scale_fill_grey(start = 0.2, end = 0.8, na.value = \"red\")`: Use a grey gradient color scale.\n\n### Color and Fill Scales (Continuous)\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\no <- c + geom_dotplot(aes(fill = ..x..))\n```\n:::\n\n\n\n- `o + scale_fill_distiller(palette = \"Blues\")`: Interpolate a palette into a continuous scale.\n\n- `o + scale_fill_gradient(low = \"red\", high = \"yellow\")`: Create a two color gradient.\n\n- `o + scale_fill_gradient2(low = \"red\", high = \"blue\", mid = \"white\", midpoint = 25)`: Create a diverging color gradient.\n\n- `o + scale_fill_gradientn(colors = topo.colors(6))`: Create a n-color gradient.\n Also `rainbow()`, `heat.colors()`, `terrain.colors()`, `cm.colors()`, `RColorBrewer::brewer.pal()`.\n\n### Shape and Size Scales\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\np <- e + geom_point(aes(shape = fl, size = cyl))\n```\n:::\n\n\n\n- `p + scale_shape() + scale_size()`: Map discrete values to shape and size aesthetics.\n\n- `p + scale_shape_manual(values = c(3:7))`: Map discrete values to specified shape values.\n\n- `p + scale_radius(range = c(1,6))`: Map values to a shape's radius.\n\n- `p + scale_size_area(max_size = 6)`: Like `scale_size()` but maps zero values to zero size.\n\nShapes used here are the same as the ones listed in the Aes section.\n\n## Coordinate Systems\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nu <- d + geom_bar()\n```\n:::\n\n\n\n- `u + coord_cartesian(xlim = c(0, 5))`: `xlim`, `ylim`.\n The default Cartesian coordinate system.\n\n- `u + coord_fixed(ratio = 1/2)`: `ratio`, `xlim`, `ylim`.\n Cartesian coordinates with fixed aspect ration between x and y units.\n\n- `ggplot(mpg, aes(y = fl)) + geom_bar()`: Flip Cartesian coordinates by switching x and y aesthetic mappings.\n\n- `u + coord_polar(theta = \"x\", direction = 1)`: `theta`, `start`, `direction`.\n Polar coordinates.\n\n- `u + coord_trans(y = \"sqrt\")`: `x`, `y`, `xlim`, `ylim`.\n Transformed Cartesian coordinates.\n Set `xtrans` and `ytrans` to the name of a window function.\n\n- `π + coord_sf()`: `xlim`, `ylim`, `crs`.\n Ensures all layers use a common Coordinate Reference System.\n\n## Position Adjustments\n\nPosition adjustments determine how to arrange geoms that would otherwise occupy the same space.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ns <- ggplot(mpg, aes(fl, fill = drv))\n```\n:::\n\n\n\n- `s + geom_bar(position = \"dodge\")`: Arrange elements side by side.\n\n- `s + geom_bar(position = \"fill\")`: Stack elements on top of one another, normalize height.\n\n- `e + geom_point(position = \"jitter\")`: Add random noise to X and Y position of each element to avoid over plotting.\n\n- `e + geom_label(position = \"nudge\")`: Nudge labels away from points.\n\n- `s + geom_bar(position = \"stack\")`: Stack elements on top of one another.\n\nEach position adjustment can be recast as a function with manual `width` and `height` arguments:\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ns + geom_bar(position = position_dodge(width = 1))\n```\n:::\n\n\n\n## Themes\n\n- `u + theme_bw()`: White background with grid lines.\n\n- `u + theme_gray()`: Grey background with white grid lines (default theme).\n\n- `u + theme_dark()`: Dark grey background and grid lines for contrast.\n\n- `u + theme_classic()`: No grid lines.\n\n- `u + theme_light()`: Light grey axes and grid lines.\n\n- `u + theme_linedraw()`: Uses only black lines.\n\n- `u + theme_minimal()`: Minimal theme.\n\n- `u + theme_void()`: Empty theme.\n\n- `u + theme()`: Customize aspects of the theme such as axis, legend, panel, and facet properties.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n r + ggtitle(\"Title\") + theme(plot.title.postion = \"plot\")\n \n r + theme(panel.background = element_rect(fill = \"blue\"))\n ```\n :::\n\n\n\n## Faceting\n\nFacets divide a plot into subplots based on the values of one or more discrete variables.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nt <- ggplot(mpg, aes(cty, hwy)) + geom_point()\n```\n:::\n\n\n\n- `t + facet_grid(. ~ fl)`: Facet into a column based on fl.\n\n- `t + facet_grid(year ~ .)`: Facet into rows based on year.\n\n- `t + facet_grid(year ~ fl)`: Facet into both rows and columns.\n\n- `t + facet_wrap(~ fl)`: Wrap facets into a rectangular layout.\n\n- `t + facet_grid(drv ~ fl, scales = \"free\")`: Set **scales** to let axis limits vary across facets.\n Also `\"free_x\"` for x axis limits adjust to individual facets and `\"free_y\"` for y axis limits adjust to individual facets.\n\nSet **labeller** to adjust facet label:\n\n- `t + facet_grid(. ~ fl, labeller = label_both)`: Labels each facet as \"fl: c\", \"fl: d\", etc.\n\n- `t + facet_grid(fl ~ ., labeller = label_bquote(alpha ^ .(fl)))`: Labels each facet as \"𝛼^c^\", \"𝛼^d^\", etc.\n\n## Labels and Legends\n\nUse `labs()` to label elements of your plot.\n\n``` \nt + labs(x = \"New x axis label\", \n y = \"New y axis label\",\n title =\"Add a title above the plot\",\n subtitle = \"Add a subtitle below title\",\n caption = \"Add a caption below plot\",\n alt = \"Add alt text to the plot\",\n = \"New legend title\")\n```\n\n- `t + annotate(geom = \"text\", x = 8, y = 9, label = \"A\")`: Places a geom with manually selected aesthetics.\n\n- `p + guides(x = guide_axis(n.dodge = 2))`: Avoid crowded or overlapping labels with `guide_axis(n.dodge or angle)`.\n\n- `n + guides(fill = \"none\")`: Set legend type for each aesthetic: `colorbar`, `legend`, or `none` (no legend).\n\n- `n + theme(legend.position = \"bottom\")`: Place legend at \"bottom\", \"top\", \"left\", or \"right\".\n\n- `n + scale_fill_discrete(name = \"Title\", labels = c(\"A\", \"B\", \"C\", \"D\", \"E\"))`: Set legend title and labels with a scale function.\n\n## Zooming\n\n- `t + coord_cartesian(xlim = c(0, 100), ylim = c(10,20))`: Zoom without clipping (preferred).\n\n- `t + xlim(0, 100) + ylim(10, 20)` or `t + scale_x_continuous(limits = c(0, 100)) + scale_y_continuous(limits = c(0, 100))`: Zoom with clipping (removes unseen data points).\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [ggplot2.tidyverse.org](https://ggplot2.tidyverse.org).\n\nUpdated: 2024-05.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"ggplot2\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '3.5.1'\n```\n\n\n:::\n:::\n\n\n\n------------------------------------------------------------------------\n", + "supporting": [ + "data-visualization_files" + ], "filters": [ "rmarkdown/pagebreak.lua" ], diff --git a/_freeze/html/shiny/execute-results/html.json b/_freeze/html/shiny/execute-results/html.json index 9a0b3e18..a509c786 100644 --- a/_freeze/html/shiny/execute-results/html.json +++ b/_freeze/html/shiny/execute-results/html.json @@ -1,8 +1,8 @@ { - "hash": "de6b722bd2f644521749eb42b857e2b7", + "hash": "3a8a53c6e6fae5f74ab594c5bfbd7aa7", "result": { "engine": "knitr", - "markdown": "---\ntitle: \"Shiny for R :: Cheatsheet\"\ndescription: \" \"\nimage-alt: \"\"\nexecute:\n eval: true\n output: false\n warning: true\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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\n* French\n* German\n* Spanish\n* Turkish\n* Vietnamese\n:::\n\n\n\n## Building an App\n\nA **Shiny** app is a web page (`ui`) connected to a computer running a live R session (`server`).\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(shiny)\n```\n:::\n\n\n\nUsers can manipulate the UI, which will cause the server to update the UI's display (by running R code).\n\nSave your template as `app.R`.\nKeep your app in a directory along with optional extra files.\n\n- **app-name:** The directory name is the app name\n- **app.R**\n- DESCRIPTION and README: (optional) used in showcase mode\n- R/: (optional) directory of supplemental .R files that are sourced automatically, must be named `R`\n- www/: (optional) directory of files to share with web browsers (images, CSS, .js, etc.), must be named `www`\n\nLaunch apps stored in a directory with `runApp()`.\n\nTo generate the template, type `shinyApp` and press `Tab` in the RStudio IDE or go to **File \\> New Project \\> New Directory \\> Shiny Application**.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# app.R \nlibrary(shiny)\n\n#In ui nest R functions to build an HTML interface\nui <- fluidPage(\n numericInput(inputId = \"n\", \"Sample size\", value = 25),\n plotOutput(outputId = \"hist\")\n)\n# Customize the UI with Layout Functions\n# Add Inputs with *Input() functions\n# Add Outputs with *Output() functions\n\n\n# Tell the server how to render outputs and respond to inputs with R\nserver <- function(input, output, session) {\n output$hist <- renderPlot({\n hist(rnorm(input$n))\n })\n}\n# Wrap code in render*() functions before saving to output\n# Refer to UI inputs with input$ and outputs with output$\n \n# Call shinyApp() to combine ui and server into an interactive app!\nshinyApp(ui = ui, server = server)\n```\n:::\n\n\n\nSee annotated examples of Shiny apps by running `runExample()`.\nRun `runExample()` with no arguments for a list of example names.\n\n## Share\n\nShare your app in three ways:\n\n1. Host it on [shinyapps.io](shinyapps.io), a cloud based service from Posit. To deploy Shiny apps:\n - Create a free or professional account at [shinyapps.io](shinyapps.io)\n\n - Click the Publish icon in RStudio IDE, or run: `rsconnect::deployApp(\"\")`\n2. Purchase Posit Connect, a publishing platform for R and Python. [posit.co/products/enterprise/connect/](posit.co/products/enterprise/connect/)\n3. Build your own Shiny Server. [posit.co/products/open-source/shinyserver/](posit.co/products/open-source/shinyserver/)\n\n## Outputs\n\n`render*()` and `*Output()` functions work together to add R output to the UI.\n\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `render*()` Functions | `*Output()` Functions |\n+==================================================================================================================================+===============================================================================+\n| `DT::renderDataTable(expr, options, searchDelay, callback, escape, env, quoted, outputArgs)` | `dataTableOutput(outputId)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderImage(expr, env, quoted, deleteFile, outputArgs)` | `imageOutput(outputId, width, height, click, dblclick, hover, brush, inline)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderPlot(expr, width, height, res, …, alt, env, quoted, execOnResixe, outputArgs` | `plotOutput(outputId, width, height, click, dblclick, hover, brush, inline)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderPrint(expr, env, quoted, width, outputArgs)` | `verbatimTextOutput(outputId, placeholder)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderTable(expr, striped, hover, bordered, spacing, width, align, rownames, colnames, digits, na, …, env, quoted, outputArgs)` | `tableOutput(outputId)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderText(expr, env, quoted, outputArgs, sep)` | `textOutput(outputId, container, inline)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderUI(expr, env, quoted, outputArgs)` | `uiOutput(outputId, inline, container, …)`\\ |\n| | `htmlOutput(outputId, inline, container, …)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n\n: Table of render\\*() functions and their associated \\*Output() functions.\n\nThese are the core output types.\nSee [htmlwidgets.org](https://www.htmlwidgets.org/) for many more options.\n\n## Inputs\n\nCollect values from the user.\n\nAccess the current value of an input object with `input$`.\nInput values are **reactive**.\n\n- `actionButton(inputId, label, icon, width, ...)`\n\n- `actionLink(inputId, label, icon, ...)`\n\n- `checkboxGroupInput(inputId, label, choices, selected, inline, width, choiceNames, choiceValues)`\n\n- `checkboxInput(inputId, label, value, width)`\n\n- `dateInput(inputId, label, value, min, max, format, startview, weekstart, language, width, autoclose, datesdisabled, daysofweekdisabled)`\n\n- `dateRangeInput(inputId, label, start, end, min, max, format, startview, weekstart, language, separator, width, autoclose)`\n\n- `fileInput(inputId, label, multiple, accept, width, buttonLabel, placeholder)`\n\n- `numericInput(inputId, label, value, min, max, step, width)`\n\n- `passwordInput(inputId, label, value, width, placeholder)`\n\n- `radioButtons(inputId, label, choices, selected, inline, width, choiceNames, choiceValues)`\n\n- `selectInput(inputId, label, choices, selected, multiple, selectize, width, size)`: Also `selectizeInput()`\n\n- `sliderInput(inputId, label, min, max, value, step, round, format, locale, ticks, animate, width, sep, pre, post, timeFormat, timezone, dragRange)`\n\n- `textInput(inputId, label, value, width, placeholder)`: Also `textAreaInput()`\n\n\n\n## Reactivity\n\nReactive values work together with reactive functions.\nCall a reactive value from within the arguments of one of these functions to avoid the error `Operation not allowed without an active reactive context`**.**\n\n![](images/reactivity-diagram.png){fig-align=\"center\"}\n\n::: {.callout-note appearance=\"minimal\" icon=\"false\" collapse=\"true\"}\n## Expand to read about the reactivity diagram {aria-hidden=\"true\"}\n\n### Phases in the reactivity diagram\n\n- Create your own reactive values\n - `reactiveValues()`\n - `reactiveFileReader()`\n - `reactivePoll()`\n - `*Input()`\n- Perform side effects\n - `observeEvent()`\n - `observe()`\n- Schedule updates\n - `invalidateLater()`\n- Create reactive expressions\n - `reactive()`\n- Remove reactivity\n - `isolate()`\n- React based on event\n - `eventReactive()`\n- Render reactive output\n - `render*()`\n:::\n\n### Create Your own Reactive Values\n\n- `*Input()` functions: Each input function creates a reactive value stored as `input$`.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n # *Input() example\n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\")\n )\n ```\n :::\n\n\n\n- `reactiveVal():` Creates a single reactive values object.\n\n `reactiveValues(...)`: Creates a list of reactive values whose values you can set.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n # reactiveVal example\n server <- function(input,output){\n rv <- reactiveValues() \n rv$number <- 5\n }\n ```\n :::\n\n\n\n### Create Reactive Expressions\n\n- `reactive(x, env, quoted, label, domain)`:\n\n - Reactive expressions:\n\n - cache their value to reduce computation\n\n - can be called elsewhere\n\n - notify dependencies when invalidated\n\n Call the expression with function syntax, e.g. `re()`.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\"), \n textInput(\"z\",\"\",\"Z\"), \n textOutput(\"b\")\n )\n \n server <- function(input,output){\n re <- reactive({ \n paste(input$a,input$z)\n })\n output$b <- renderText({\n re()\n }) \n }\n \n shinyApp(ui, server)\n ```\n :::\n\n\n\n### React Based on Event\n\n- `eventReactive(eventExpr, valueExpr, event.env, event.quoted, value.env, value.quoted, ..., label, domain, ignoreNULL, ignoreInit)`: Creates reactive expression with code in 2nd argument that only invalidates when reactive values in 1st argument change.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\"), \n actionButton(\"go\",\"Go\"), \n textOutput(\"b\")\n )\n \n server <- function(input,output){\n re <- eventReactive(\n input$go,{input$a}\n )\n output$b <- renderText({\n re()\n }) \n }\n ```\n :::\n\n\n\n### Render Reactive Output\n\n- `render*()` functions: (see front page) Builds an object to display.\n Will rerun code in body to rebuild the object whenever a reactive value in the code changes.\n Save the results to `output$`.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\"), \n textOutput(\"b\")\n )\n \n server <- function(input,output){\n output$b <-\n renderText({\n input$a\n })\n }\n \n shinyApp(ui, server)\n ```\n :::\n\n\n\n### Perform Side Effects\n\n- `observe(x, env)`: Creates an observer from the given expression.\n\n- `observeEvent(eventExpr, handlerExpr, event.env, event.quoted, handler.env, handler.quoted, ..., label, suspended, priority, domain, autoDestroy, ignoreNULL, ignoreInit, once)`: Runs code in 2nd argument when reactive values in 1st argument change.\n Alternative to ``` observe``() ```.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(textInput(\"a\",\"\",\"A\"), actionButton(\"go\",\"Go\"))\n \n server <- function(input,output){\n observeEvent(input$go, {\n print(input$a)\n })\n }\n \n shinyApp(ui, server)\n ```\n :::\n\n\n\n### Remove Reactivity\n\n- `isolate(expr)`: Runs a code block.\n Returns a **non-reactive** copy of the results.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\"), \n textOutput(\"b\")\n )\n \n server <- function(input,output){ \n output$b <- \n renderText({\n isolate({input$a})\n })\n }\n \n shinyApp(ui, server)\n ```\n :::\n\n\n\n## UI\n\nAn app's UI is an HTML document.\n\nUse Shiny's functions to assemble this HTML with R.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nfluidPage(\n textInput(\"a\",\"\")\n)\n```\n:::\n\n\n\nReturns HTML:\n\n``` html\n
\n
\n \n \n
\n
\n```\n\nAdd static HTML elements with **tags**, a list of functions that parallel common HTML tags, e.g. `tags$a()`.\nUnnamed arguments will be passed into the tag; named arguments will become tag attributes.\n\nRun `names(tags)` for a complete list.\n`tags$h1(\"Header\")` -\\> `

Header

`\n\nThe most common tags have wrapper functions.\nYou do not need to prefix their names with `tags$`.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nui <- fluidPage(\n h1(\"Header 1\"), #

Header 1

\n hr(), #
\n br(), #
\n p(strong(\"bold\")), #

bold

\n p(em(\"italic\")), #

italic

\n p(code(\"code\")), #

code

\n a(href=\"\", \"link\"), # link\n HTML(\"

Raw html

\") # display raw html\n)\n```\n:::\n\n\n\nTo include a CSS file, use `includeCSS()`, or\n\n1. Place the file in the `www` subdirectory\n\n2. Link to it with:\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n tags$head(\n tags$link(\n rel = \"stylesheet\", \n type = \"text/css\", \n href = \"\"\n )\n )\n ```\n :::\n\n\n\nTo include JavaScript, use `includeScript()`, or\n\n1. Place the file in the `www` subdirectory\n\n2. Link to it with:\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n tags$head(tags$script(src = \"\"))\n ```\n :::\n\n\n\nTo include an image:\n\n1. Place the file in the `www` subdirectory\n\n2. Link to it with:\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n img(src = \"\")\n ```\n :::\n\n\n\n## Layouts\n\nCombine multiple elements into a \"single element\" that has its own properties with a panel function, e.g.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nwellPanel(\n dateInput(\"a\", \"\"),\n submitButton()\n)\n```\n:::\n\n\n\nOther elements:\n\n- `absolutePanel()`\n- `conditionalPanel()`\n- `fixedPanel()`\n- `headerPanel()`\n- `inputPanel()`\n- `mainPanel()`\n- `navlistPanel()`\n- `sidebarPanel()`\n- `tabPanel()`\n- `tabsetPanel()`\n- `titlePanel()`\n- `wellPanel()`\n\nOrganize panels and elements into a layout with a layout function.\nAdd elements as arguments of the layout functions.\n\n- `sidebarLayout()`\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ui <- fluidPage(\n sidebarLayout(\n sidebarPanel(),\n mainPanel()\n )\n )\n ```\n :::\n\n\n\n- `fluidRow()`\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n ui <- fluidPage(\n fluidRow(column(width = 4),\n column(width = 2, offset = 3)),\n fluidRow(column(width = 12))\n )\n ```\n :::\n\n\n\nAlso `flowLayout()`, `splitLayout()`, `verticalLayout()`, `fixedPage()`, and `fixedRow()`.\n\nLayer tabPanels on top of each other, and navigate between them with:\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nui <- fluidPage(\n tabsetPanel(\n tabPanel(\"tab1\", \"contents\"),\n tabPanel(\"tab2\", \"contents\"),\n tabPanel(\"tab3\", \"contents\")\n )\n)\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nui <- fluidPage(\n navlistPanel(\n tabPanel(\"tab1\", \"contents\"),\n tabPanel(\"tab2\", \"contents\"),\n tabPanel(\"tab3\", \"contents\")\n )\n)\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nui <- navbarPage(\n title = \"Page\",\n tabPanel(\"tab1\", \"contents\"),\n tabPanel(\"tab2\", \"contents\"),\n tabPanel(\"tab3\", \"contents\")\n)\n```\n:::\n\n\n\n## Themes\n\nUse the **bslib** package to add existing themes to your Shiny app ui, or make your own.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(bslib)\nui <- fluidPage(\n theme = bs_theme(\n boothswatch = \"darkly\",\n ...\n )\n)\n```\n:::\n\n\n\n- `bootswatch_themes()`: Get a list of themes.\n\nBuild your own theme by customizing individual arguments.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nbs_theme(\n bg = \"#558AC5\",\n fg = \"#F9B02D\",\n ...\n)\n```\n:::\n\n\n\n- `?bs_theme` for a full list of arguments.\n\n- `bs_themer()`: Place within the server function ot use the interactive theming widget.\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [shiny.rstudio.com](https://shiny.rstudio.com/)\n\nUpdated: 2024-05.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"shiny\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '1.8.1.1'\n```\n\n\n:::\n:::\n\n\n\n------------------------------------------------------------------------\n", + "markdown": "---\ntitle: \"Shiny for R :: Cheatsheet\"\ndescription: \" \"\nimage-alt: \"\"\nexecute:\n eval: true\n output: false\n warning: true\n---\n\n::: {.cell .column-margin}\n\"Hex\n

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Translations (PDF)

\n* French\n* German\n* Spanish\n* Turkish\n* Vietnamese\n:::\n\n\n\n## Building an App\n\nA **Shiny** app is a web page (`ui`) connected to a computer running a live R session (`server`).\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(shiny)\n```\n:::\n\n\n\nUsers can manipulate the UI, which will cause the server to update the UI's display (by running R code).\n\nSave your template as `app.R`.\nKeep your app in a directory along with optional extra files.\n\n- **app-name:** The directory name is the app name\n- **app.R**\n- DESCRIPTION and README: (optional) used in showcase mode\n- R/: (optional) directory of supplemental .R files that are sourced automatically, must be named `R`\n- www/: (optional) directory of files to share with web browsers (images, CSS, .js, etc.), must be named `www`\n\nLaunch apps stored in a directory with `runApp()`.\n\nTo generate the template, type `shinyApp` and press `Tab` in the RStudio IDE or go to **File \\> New Project \\> New Directory \\> Shiny Application**.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# app.R \nlibrary(shiny)\n\n#In ui nest R functions to build an HTML interface\nui <- fluidPage(\n numericInput(inputId = \"n\", \"Sample size\", value = 25),\n plotOutput(outputId = \"hist\")\n)\n# Customize the UI with Layout Functions\n# Add Inputs with *Input() functions\n# Add Outputs with *Output() functions\n\n\n# Tell the server how to render outputs and respond to inputs with R\nserver <- function(input, output, session) {\n output$hist <- renderPlot({\n hist(rnorm(input$n))\n })\n}\n# Wrap code in render*() functions before saving to output\n# Refer to UI inputs with input$ and outputs with output$\n \n# Call shinyApp() to combine ui and server into an interactive app!\nshinyApp(ui = ui, server = server)\n```\n:::\n\n\n\nSee annotated examples of Shiny apps by running `runExample()`.\nRun `runExample()` with no arguments for a list of example names.\n\n## Share\n\nShare your app in three ways:\n\n1. Host it on [shinyapps.io](shinyapps.io), a cloud based service from Posit. To deploy Shiny apps:\n - Create a free or professional account at [shinyapps.io](shinyapps.io)\n\n - Click the Publish icon in RStudio IDE, or run: `rsconnect::deployApp(\"\")`\n2. Purchase Posit Connect, a publishing platform for R and Python. [posit.co/products/enterprise/connect/](posit.co/products/enterprise/connect/)\n3. Build your own Shiny Server. [posit.co/products/open-source/shinyserver/](posit.co/products/open-source/shinyserver/)\n\n## Outputs\n\n`render*()` and `*Output()` functions work together to add R output to the UI.\n\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `render*()` Functions | `*Output()` Functions |\n+==================================================================================================================================+===============================================================================+\n| `DT::renderDataTable(expr, options, searchDelay, callback, escape, env, quoted, outputArgs)` | `dataTableOutput(outputId)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderImage(expr, env, quoted, deleteFile, outputArgs)` | `imageOutput(outputId, width, height, click, dblclick, hover, brush, inline)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderPlot(expr, width, height, res, …, alt, env, quoted, execOnResixe, outputArgs` | `plotOutput(outputId, width, height, click, dblclick, hover, brush, inline)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderPrint(expr, env, quoted, width, outputArgs)` | `verbatimTextOutput(outputId, placeholder)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderTable(expr, striped, hover, bordered, spacing, width, align, rownames, colnames, digits, na, …, env, quoted, outputArgs)` | `tableOutput(outputId)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderText(expr, env, quoted, outputArgs, sep)` | `textOutput(outputId, container, inline)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n| `renderUI(expr, env, quoted, outputArgs)` | `uiOutput(outputId, inline, container, …)`\\ |\n| | `htmlOutput(outputId, inline, container, …)` |\n+----------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------------------------+\n\n: Table of render\\*() functions and their associated \\*Output() functions.\n\nThese are the core output types.\nSee [htmlwidgets.org](https://www.htmlwidgets.org/) for many more options.\n\n## Inputs\n\nCollect values from the user.\n\nAccess the current value of an input object with `input$`.\nInput values are **reactive**.\n\n- `actionButton(inputId, label, icon, width, ...)`\n\n- `actionLink(inputId, label, icon, ...)`\n\n- `checkboxGroupInput(inputId, label, choices, selected, inline, width, choiceNames, choiceValues)`\n\n- `checkboxInput(inputId, label, value, width)`\n\n- `dateInput(inputId, label, value, min, max, format, startview, weekstart, language, width, autoclose, datesdisabled, daysofweekdisabled)`\n\n- `dateRangeInput(inputId, label, start, end, min, max, format, startview, weekstart, language, separator, width, autoclose)`\n\n- `fileInput(inputId, label, multiple, accept, width, buttonLabel, placeholder)`\n\n- `numericInput(inputId, label, value, min, max, step, width)`\n\n- `passwordInput(inputId, label, value, width, placeholder)`\n\n- `radioButtons(inputId, label, choices, selected, inline, width, choiceNames, choiceValues)`\n\n- `selectInput(inputId, label, choices, selected, multiple, selectize, width, size)`: Also `selectizeInput()`\n\n- `sliderInput(inputId, label, min, max, value, step, round, format, locale, ticks, animate, width, sep, pre, post, timeFormat, timezone, dragRange)`\n\n- `textInput(inputId, label, value, width, placeholder)`: Also `textAreaInput()`\n\n\n\n## Reactivity\n\nReactive values work together with reactive functions.\nCall a reactive value from within the arguments of one of these functions to avoid the error `Operation not allowed without an active reactive context`**.**\n\n![](images/reactivity-diagram.png){fig-align=\"center\"}\n\n::: {.callout-note appearance=\"minimal\" icon=\"false\" collapse=\"true\"}\n## Expand to read about the reactivity diagram {aria-hidden=\"true\"}\n\n### Phases in the reactivity diagram\n\n- Create your own reactive values\n - `reactiveValues()`\n - `reactiveFileReader()`\n - `reactivePoll()`\n - `*Input()`\n- Perform side effects\n - `observeEvent()`\n - `observe()`\n- Schedule updates\n - `invalidateLater()`\n- Create reactive expressions\n - `reactive()`\n- Remove reactivity\n - `isolate()`\n- React based on event\n - `eventReactive()`\n- Render reactive output\n - `render*()`\n:::\n\n### Create Your own Reactive Values\n\n- `*Input()` functions: Each input function creates a reactive value stored as `input$`.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n # *Input() example\n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\")\n )\n ```\n :::\n\n\n\n- `reactiveVal():` Creates a single reactive values object.\n\n `reactiveValues(...)`: Creates a list of reactive values whose values you can set.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n # reactiveVal example\n server <- function(input,output){\n rv <- reactiveValues() \n rv$number <- 5\n }\n ```\n :::\n\n\n\n### Create Reactive Expressions\n\n- `reactive(x, env, quoted, label, domain)`:\n\n - Reactive expressions:\n\n - cache their value to reduce computation\n\n - can be called elsewhere\n\n - notify dependencies when invalidated\n\n Call the expression with function syntax, e.g. `re()`.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\"), \n textInput(\"z\",\"\",\"Z\"), \n textOutput(\"b\")\n )\n \n server <- function(input,output){\n re <- reactive({ \n paste(input$a,input$z)\n })\n output$b <- renderText({\n re()\n }) \n }\n \n shinyApp(ui, server)\n ```\n :::\n\n\n\n### React Based on Event\n\n- `eventReactive(eventExpr, valueExpr, event.env, event.quoted, value.env, value.quoted, ..., label, domain, ignoreNULL, ignoreInit)`: Creates reactive expression with code in 2nd argument that only invalidates when reactive values in 1st argument change.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\"), \n actionButton(\"go\",\"Go\"), \n textOutput(\"b\")\n )\n \n server <- function(input,output){\n re <- eventReactive(\n input$go,{input$a}\n )\n output$b <- renderText({\n re()\n }) \n }\n ```\n :::\n\n\n\n### Render Reactive Output\n\n- `render*()` functions: (see front page) Builds an object to display.\n Will rerun code in body to rebuild the object whenever a reactive value in the code changes.\n Save the results to `output$`.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\"), \n textOutput(\"b\")\n )\n \n server <- function(input,output){\n output$b <-\n renderText({\n input$a\n })\n }\n \n shinyApp(ui, server)\n ```\n :::\n\n\n\n### Perform Side Effects\n\n- `observe(x, env)`: Creates an observer from the given expression.\n\n- `observeEvent(eventExpr, handlerExpr, event.env, event.quoted, handler.env, handler.quoted, ..., label, suspended, priority, domain, autoDestroy, ignoreNULL, ignoreInit, once)`: Runs code in 2nd argument when reactive values in 1st argument change.\n Alternative to ``` observe``() ```.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(textInput(\"a\",\"\",\"A\"), actionButton(\"go\",\"Go\"))\n \n server <- function(input,output){\n observeEvent(input$go, {\n print(input$a)\n })\n }\n \n shinyApp(ui, server)\n ```\n :::\n\n\n\n### Remove Reactivity\n\n- `isolate(expr)`: Runs a code block.\n Returns a **non-reactive** copy of the results.\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n library(shiny)\n \n ui <- fluidPage(\n textInput(\"a\",\"\",\"A\"), \n textOutput(\"b\")\n )\n \n server <- function(input,output){ \n output$b <- \n renderText({\n isolate({input$a})\n })\n }\n \n shinyApp(ui, server)\n ```\n :::\n\n\n\n## UI\n\nAn app's UI is an HTML document.\n\nUse Shiny's functions to assemble this HTML with R.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nfluidPage(\n textInput(\"a\",\"\")\n)\n```\n:::\n\n\n\nReturns HTML:\n\n``` html\n
\n
\n \n \n
\n
\n```\n\nAdd static HTML elements with **tags**, a list of functions that parallel common HTML tags, e.g. `tags$a()`.\nUnnamed arguments will be passed into the tag; named arguments will become tag attributes.\n\nRun `names(tags)` for a complete list.\n`tags$h1(\"Header\")` -\\> `

Header

`\n\nThe most common tags have wrapper functions.\nYou do not need to prefix their names with `tags$`.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nui <- fluidPage(\n h1(\"Header 1\"), #

Header 1

\n hr(), #
\n br(), #
\n p(strong(\"bold\")), #

bold

\n p(em(\"italic\")), #

italic

\n p(code(\"code\")), #

code

\n a(href=\"\", \"link\"), # link\n HTML(\"

Raw html

\") # display raw html\n)\n```\n:::\n\n\n\nTo include a CSS file, use `includeCSS()`, or\n\n1. Place the file in the `www` subdirectory\n\n2. Link to it with:\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n tags$head(\n tags$link(\n rel = \"stylesheet\", \n type = \"text/css\", \n href = \"\"\n )\n )\n ```\n :::\n\n\n\nTo include JavaScript, use `includeScript()`, or\n\n1. Place the file in the `www` subdirectory\n\n2. Link to it with:\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n tags$head(tags$script(src = \"\"))\n ```\n :::\n\n\n\nTo include an image:\n\n1. Place the file in the `www` subdirectory\n\n2. Link to it with:\n\n\n\n ::: {.cell}\n \n ```{.r .cell-code}\n img(src = \"\")\n ```\n :::\n\n\n\n## Layouts\n\nUse the **bslib** package to lay out the your app and its components.\n\n### Page layouts\n\n#### Dashboard layouts\n\n- `page_sidebar()` - A sidebar page\n\n- `page_navbar()` - Multi-page app with a top navigation bar\n\n- `page_fillable()` - A screen-filling page layout\n\n#### Basic layouts\n\n- `page()`\n\n- `page_fluid()`\n\n- `page_fixed()`\n\n### User interface layouts\n\n#### Multiple columns\n\n- `layout_columns()` - Organize UI elements into Bootstrap’s 12-column CSS grid\n\n- `layout_column_wrap()` - Organize elements into a grid of equal-width columns\n\n#### Multiple panels\n\n- `navset_tab()` - Tabbed navigation container\n\n- `navset_pill()` - Creates a navigation container that behaves exactly like `navset_tab()`, but the tab toggles are *pills* or button-shaped\n\n- `navset_underline()` - Creates a navigation container that behaves exactly like `navset_tab()` and `navset_pill()`, but the active/focused navigation links are styled with an underline\n\n- `nav_panel()` - Content to display when given item is selected\n\n- `nav_menu()` - Create a menu of nav items\n\n- `nav_item()` - Place arbitrary content in the nav panel\n\n- `nav_spacer()` - Add spacing between nav items\n\nAlso dynamically update nav containers with `nav_select()`, `nav_insert()`, `nav_remove()`, `nav_show()`, `nav_hide()`.\n\n#### Sidebar layout\n\n- `sidebar()`\n\n- `layout_sidebar()`\n\n- `toggle_sidebar()`\n\n## Themes\n\nUse the **bslib** package to add existing themes to your Shiny app ui, or make your own.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(bslib)\nui <- fluidPage(\n theme = bs_theme(\n boothswatch = \"darkly\",\n ...\n )\n)\n```\n:::\n\n\n\n- `bootswatch_themes()`: Get a list of themes.\n\nBuild your own theme by customizing individual arguments.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nbs_theme(\n bg = \"#558AC5\",\n fg = \"#F9B02D\",\n ...\n)\n```\n:::\n\n\n\n- `?bs_theme` for a full list of arguments.\n\n- `bs_themer()`: Place within the server function ot use the interactive theming widget.\n\n------------------------------------------------------------------------\n\nCC BY SA Posit Software, PBC • [info\\@posit.co](mailto:info@posit.co) • [posit.co](https://posit.co)\n\nLearn more at [shiny.rstudio.com](https://shiny.rstudio.com/)\n\nUpdated: 2024-05.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\npackageVersion(\"shiny\")\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] '1.8.1.1'\n```\n\n\n:::\n:::\n\n\n\n------------------------------------------------------------------------\n", "supporting": [], "filters": [ "rmarkdown/pagebreak.lua" diff --git a/html/images/logo-shiny.png b/html/images/logo-shiny.png index a9128b8a38b5d050143900738365934893c0eae4..30ab98e1df07a5ce42bf61947b1639e7b75e1750 100644 GIT binary patch delta 21 ccmZoW$k=v}aY7b{JhK(=diLkp8;e8|098c?n*aa+ delta 21 ccmZoW$k=v}aY7b{oPd(GOVxzu8;e8|09K_3>Hq)$ diff --git a/html/shiny.qmd b/html/shiny.qmd index d762ac44..3699c687 100644 --- a/html/shiny.qmd +++ b/html/shiny.qmd @@ -438,98 +438,59 @@ To include an image: ## Layouts -Combine multiple elements into a "single element" that has its own properties with a panel function, e.g. +Use the **bslib** package to lay out the your app and its components. -```{r} -#| eval: false +### Page layouts -wellPanel( - dateInput("a", ""), - submitButton() -) -``` +#### Dashboard layouts -Other elements: +- `page_sidebar()` - A sidebar page -- `absolutePanel()` -- `conditionalPanel()` -- `fixedPanel()` -- `headerPanel()` -- `inputPanel()` -- `mainPanel()` -- `navlistPanel()` -- `sidebarPanel()` -- `tabPanel()` -- `tabsetPanel()` -- `titlePanel()` -- `wellPanel()` +- `page_navbar()` - Multi-page app with a top navigation bar -Organize panels and elements into a layout with a layout function. -Add elements as arguments of the layout functions. +- `page_fillable()` - A screen-filling page layout -- `sidebarLayout()` +#### Basic layouts - ```{r} - #| eval: false +- `page()` - ui <- fluidPage( - sidebarLayout( - sidebarPanel(), - mainPanel() - ) - ) - ``` +- `page_fluid()` -- `fluidRow()` +- `page_fixed()` - ```{r} - #| eval: false +### User interface layouts - ui <- fluidPage( - fluidRow(column(width = 4), - column(width = 2, offset = 3)), - fluidRow(column(width = 12)) - ) - ``` +#### Multiple columns -Also `flowLayout()`, `splitLayout()`, `verticalLayout()`, `fixedPage()`, and `fixedRow()`. +- `layout_columns()` - Organize UI elements into Bootstrap’s 12-column CSS grid -Layer tabPanels on top of each other, and navigate between them with: +- `layout_column_wrap()` - Organize elements into a grid of equal-width columns -```{r} -#| eval: false +#### Multiple panels -ui <- fluidPage( - tabsetPanel( - tabPanel("tab1", "contents"), - tabPanel("tab2", "contents"), - tabPanel("tab3", "contents") - ) -) -``` +- `navset_tab()` - Tabbed navigation container -```{r} -#| eval: false +- `navset_pill()` - Creates a navigation container that behaves exactly like `navset_tab()`, but the tab toggles are *pills* or button-shaped -ui <- fluidPage( - navlistPanel( - tabPanel("tab1", "contents"), - tabPanel("tab2", "contents"), - tabPanel("tab3", "contents") - ) -) -``` +- `navset_underline()` - Creates a navigation container that behaves exactly like `navset_tab()` and `navset_pill()`, but the active/focused navigation links are styled with an underline -```{r} -#| eval: false +- `nav_panel()` - Content to display when given item is selected -ui <- navbarPage( - title = "Page", - tabPanel("tab1", "contents"), - tabPanel("tab2", "contents"), - tabPanel("tab3", "contents") -) -``` +- `nav_menu()` - Create a menu of nav items + +- `nav_item()` - Place arbitrary content in the nav panel + +- `nav_spacer()` - Add spacing between nav items + +Also dynamically update nav containers with `nav_select()`, `nav_insert()`, `nav_remove()`, `nav_show()`, `nav_hide()`. + +#### Sidebar layout + +- `sidebar()` + +- `layout_sidebar()` + +- `toggle_sidebar()` ## Themes diff --git a/keynotes/shiny.key b/keynotes/shiny.key index 82385e06ac4eb9654c1692e5f1960ab386f126a8..89c746e7e9c23104ba37711a7d4e551d4d3bc30b 100644 GIT binary patch delta 188884 zcmbTebyOTdvp&2?kN`n~1$X!0?iwVxySqC~fW_T|2Pe3@yAwPt?g{QLKl0xDp8Ng% z?K!u% z!1Q1SFe8`=%nW7$vx3>cpTX>44lpN}3(O7X0rP_S!2DnVupn3nEDRO_i-N_#;$R7| zBv=Y84VD4Rg5|(p!17=Pup(Fq{1vPWRspMm)xhdt4X`Fy3#<*+0qcVG!1`bVup!t8 zYz#I5n}W^2=3oo3CD;mV4YmQ>g6+WeUyeM7rt2RM>CW zrpxj07+Bymm>90Utt*rZ0#}f`)z+M43cC?cM#BHFC~{`=f_O`nyG?W50hNBF!@5k- zErBc^$i;Wr{LPzY%2#6*FSZYr@QKByC=rJ^_Ii2fSnCK#FwWrqF2tdFmR1hEdfBS*GVIjT6N4_GB+aZexI#AXsFA* z`~YV%lorY;V@M}C+j$Z3gx~QBs!*I@>q5Dh^mZJ#lD#^vr+5WnRycI7>G5_2y@G0) zd#6I`#3~O(1#C3JLbc3cM#Dorw|PFn=W{ALMLbE|^*mB~5^qs8l~^ZqGo0>ZE8CO7 z>;sfj4+DSJ^*gU0SI-m;?qOC1#AQ0@B6I@t&hTR>lM5}DwU`U~CbfGlG z&M`5_*Z7RHm}VfbR`^n89}|~ie-}2!X`$02kUNp3&zwU~_BLa8p0CXMs8wflXwEaJ 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