Author: Daniel Lüdecke
Date: 2020-01-23

# Customize Plot Appearance

#### Daniel Lüdecke

#### 2020-01-23

This vignette shows how the plots created by the `sjp.*` and `plot_model()` functions of the sjPlot package can be customized.

The examples refer to `plot_grpfrq()`, but most arguments are similar across all plotting function of the sjPlot package.

## Tweaking plot appearance

The base function to globally change theme option for all sjp-function is `set_theme()`. Except for geom-colors and geom-sizes, all theme-options can be set via this function. This new theme will be applied to all following plots created with the sjPlot package.

There are various arguments to change colors, sizes, angles etc. of labels. Following example show changes to colors, sizes, angles, geom-outlines and theme.

    # load libraries
    library(sjPlot)  # for plotting
    library(sjmisc)  # for sample data
    library(ggplot2) # to access ggplot-themes

    # load sample data set
    data(efc)

    set_theme(
      geom.outline.color = "antiquewhite4",
      geom.outline.size = 1,
      geom.label.size = 2,
      geom.label.color = "grey50",
      title.color = "red",
      title.size = 1.5,
      axis.angle.x = 45,
      axis.textcolor = "blue",
      base = theme_bw()
    )

    plot_grpfrq(
      efc$e42dep,
      efc$e16sex,
      title = NULL,
      geom.colors = c("cadetblue", "coral"),
      geom.size = 0.4
    )

## Using the Color Brewer palettes

All plotting functions support the usage of the Colorbrewer palettes. To apply a color brewer palette, use specify the palette as `geom.colors`. Any valid color brewer palette is recognized automatically.

    # blank theme
    set_theme(
      base = theme_blank(),
      axis.title.size = .9,
      axis.textsize = .9,
      legend.size = .7,
      legend.title.size = .8,
      geom.label.size = 3
    )

    plot_grpfrq(
      efc$e42dep,
      efc$e15relat,
      geom.colors = "PuRd",
      show.values = FALSE
    )

An overview of all supported color codes can be obtained with `display.brewer.all()` from the `RColorBrewer` package.

    library(RColorBrewer)
    display.brewer.all()

## Plot with flipped coordinates

The plot’s axes can be flipped using `coord.flip = TRUE`. If needed, labels can be placed inside the bars with the `vjust` or `hjust` arguments. In such cases, you might need to adjust the label colors with `geom.label.color = "white"`.

    set_theme(geom.label.color = "white", geom.label.size = 3)

    # labels appear very large due to export metrics
    plot_grpfrq(efc$e42dep, efc$e16sex, coord.flip = TRUE)

## Adding plot margins

Plots with no margins towards the axes may look strange to some people (not to me, though). To restore the ggplot-default behaviour, use the `expand.grid` argument:

    plot_grpfrq(efc$e42dep, efc$e16sex, expand.grid = TRUE)

## Theme options

You can use any pre-defined theme from ggplot, like `theme_bw()`, `theme_classic()` or `theme_minimal()` as default theme.

    set_theme(base = theme_light())
    plot_frq(efc$e42dep)

## Pre-defined themes

There is a set of pre-defined themes from the sjPlot-package. See `?"sjPlot-themes"` for a complete list.

    library(sjmisc)
    data(efc)
    efc <- to_factor(efc, e42dep, c172code)
    m <- lm(neg_c_7 ~ pos_v_4 + c12hour + e42dep + c172code, data = efc)

    # reset theme
    set_theme(base = theme_grey())

    # forest plot of regression model
    p <- plot_model(m)

    # default theme
    p

    # pre-defined theme
    p + theme_sjplot()

## Pre-defined scales

There is also a new scale for ggplot-objects, `scale_color_sjplot()` and `scale_fill_sjplot()`.

    p +
      theme_sjplot2() +
      scale_color_sjplot("simply")

To see all currently available color sets, use `show_sjplot_pals()`.

    show_sjplot_pals()

## Set up own themes based on existing themes

If you want to use a specific theme as base for building your own theme, use the `base` argument. When using `base` instead of `theme`, further arguments for settings colors etc. are not ignored.

    set_theme(base = theme_bw(), axis.linecolor = "darkgreen")
    plot_frq(efc$e42dep)

## Further customization options

Each plotting function invisibly returns the ggplot-object. You can further add options to customize the appearance of the plot, like in the following example, where the count axis is hidden (color set to white):

    set_theme(
      base = theme_classic(),
      axis.tickslen = 0, # hides tick marks
      axis.title.size = .9,
      axis.textsize = .9,
      legend.size = .7,
      legend.title.size = .8,
      geom.label.size = 3.5
    )

    plot_grpfrq(
      efc$e42dep,
      efc$e16sex,
      coord.flip = TRUE,
      show.axis.values = FALSE
    ) +
      theme(axis.line.x = element_line(color = "white"))

## Plot legend

The plot’s legend can be customized via various `legend.`-arguments, see following examples:

    set_theme(
      base = theme_classic(),
      legend.title.face = "italic", # title font face
      legend.inside = TRUE,         # legend inside plot
      legend.color = "grey50",      # legend label color
      legend.pos = "bottom right",  # legend position inside plot
      axis.title.size = .9,
      axis.textsize = .9,
      legend.size = .7,
      legend.title.size = .8,
      geom.label.size = 3
    )

    plot_grpfrq(efc$e42dep, efc$e16sex, coord.flip = TRUE)

    set_theme(
      base = theme_classic(),
      axis.linecolor = "white",     # "remove" axis lines
      axis.textcolor.y = "darkred", # set axis label text only for y axis
      axis.tickslen = 0,            # "remove" tick marks
      legend.title.color = "red",   # legend title color
      legend.title.size = 2,        # legend title size
      legend.color = "green",       # legend label color
      legend.pos = "top",           # legend position above plot
      axis.title.size = .9,
      axis.textsize = .9,
      legend.size = .7,
      geom.label.size = 3
    )

    plot_grpfrq(efc$e42dep, efc$e16sex)