### Discrete Scale with Guide Customization

Source: https://context7.com/jtlandis/ggside/llms.txt

Uses a discrete scale for the xside panel with customized axis guide.

```r
# Discrete scale with guide customization
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point() +
  geom_xsideboxplot(aes(y = class), orientation = "y") +
  theme(ggside.panel.scale = .3) +
  scale_xsidey_discrete(guide = guide_axis(angle = 45))
```

--------------------------------

### Control Panel Scaling Example

Source: https://context7.com/jtlandis/ggside/llms.txt

Demonstrates basic control panel scaling with ggside, including density and boxplot layers.

```r
ggplot(iris, aes(Sepal.Width, Sepal.Length, fill = Species)) +
  geom_point(aes(color = Species)) +
  geom_xsidedensity(alpha = .3, position = "stack") +
  geom_ysideboxplot(aes(x = Species), orientation = "x") +
  theme(ggside.panel.scale = .3)
```

--------------------------------

### Install ggside Package

Source: https://context7.com/jtlandis/ggside/llms.txt

Install the ggside package from CRAN for the stable version or from GitHub for the development version.

```r
install.packages("ggside")
```

```r
devtools::install_github("jtlandis/ggside")
```

--------------------------------

### Install ggside Package

Source: https://github.com/jtlandis/ggside/blob/main/README.md

Install the ggside package from CRAN or GitHub. Use the CRAN version for the latest stable release or GitHub for development versions.

```r
utils::install.packages("ggside")
```

```r
devtools::install_github("jtlandis/ggside")
```

--------------------------------

### Customizing ggside Panel Themes

Source: https://github.com/jtlandis/ggside/blob/main/README.md

Applies custom theme elements to ggside panels for enhanced visual control, including panel scaling, borders, grids, and backgrounds. This example uses geom_xsidedensity and geom_ysideboxplot.

```r
ggplot(iris, aes(Sepal.Width, Sepal.Length, fill = Species)) +
  geom_point(aes(color = Species)) +
  geom_xsidedensity(alpha = .3, position = "stack") +
  geom_ysideboxplot(aes(x = Species), orientation = "x") +
  scale_ysidex_discrete(guide = guide_axis(angle = 45)) +
  theme_dark() +
  theme(ggside.panel.scale = .3,
        ggside.panel.border = element_rect(NA, "red", linewidth = 2),
        ggside.panel.grid = element_line("black", linewidth = .1, linetype = "dotted"),
        ggside.panel.background = element_blank()) +
  guides(color = "none", fill = "none")
```

--------------------------------

### Using ggside Complete Themes

Source: https://context7.com/jtlandis/ggside/llms.txt

Applies pre-defined ggside themes like `theme_ggside_classic`, `theme_ggside_void`, and `theme_ggside_linedraw`.

```r
# Using ggside complete themes
p <- ggplot(iris, aes(Sepal.Width, Petal.Length, color = Species)) +
  geom_point() +
  geom_xsidedensity() +
  geom_ysidedensity() +
  theme_dark()

p + theme_ggside_classic()
p + theme_ggside_void()
p + theme_ggside_linedraw() +
  theme(ggside.panel.border = element_rect(colour = "red"))
```

--------------------------------

### Reproduce positional scale warning in ggside

Source: https://github.com/jtlandis/ggside/blob/main/README.md

This snippet demonstrates a scenario where a discrete side panel scale fails to initialize correctly when the main panel scale is computed later.

```r
ggplot(iris, aes(Sepal.Width)) + 
  # main panel y scale initializes later
  geom_density() + 
  # xsidey scale is discrete but misses initial training
  geom_xsidepoint(aes(y = Species))
```

--------------------------------

### Separate Side Panel Fill Scale

Source: https://context7.com/jtlandis/ggside/llms.txt

Demonstrates using `scale_xfill` for distinct fill mappings in side panels.

```r
library(ggplot2)
library(ggside)

# Using xfill for separate side panel fill scale
ggplot(iris, aes(Sepal.Width, Sepal.Length)) +
  geom_point(aes(color = Species)) +
  geom_xsidedensity(aes(xfill = Species), alpha = 0.5) +
  scale_xfill_manual(values = c("setosa" = "red",
                                "versicolor" = "blue",
                                "virginica" = "green"))
```

--------------------------------

### Free Scales with Faceting

Source: https://context7.com/jtlandis/ggside/llms.txt

Combines faceting with free scales for both main and side panels using `facet_wrap` and `ggside(scales = "free_y")`.

```r
# Free scales with faceting
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point() +
  geom_xsidedensity() +
  facet_wrap(~cyl, scales = "free") +
  ggside(scales = "free_y")
```

--------------------------------

### Facet Grid with Collapsed Side Panels

Source: https://context7.com/jtlandis/ggside/llms.txt

Uses `facet_grid` with `ggside(collapse = "all")` to manage collapsed side panels.

```r
# Facet grid with collapsed side panels
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point() +
  geom_xsidedensity() +
  geom_ysidedensity() +
  facet_grid(drv ~ cyl) +
  ggside(collapse = "all") +
  theme(ggside.panel.scale = .15)
```

--------------------------------

### scale_xfill / scale_yfill / scale_xcolour / scale_ycolour

Source: https://context7.com/jtlandis/ggside/llms.txt

Separate aesthetic scales for side panel fill and colour mappings, enabling side panels to use different color mappings than the main panel.

```APIDOC
## scale_xfill / scale_yfill / scale_xcolour / scale_ycolour

### Description
Separate aesthetic scales for side panel fill and colour mappings. These allow side panels to use different color mappings than the main panel without conflicts.

### Request Example
scale_xfill_manual(values = c("setosa" = "red", "versicolor" = "blue", "virginica" = "green"))
scale_colour_steps(aesthetics = "xcolour", guide = guide_colorbar(available_aes = "xcolour"))
```

--------------------------------

### Configure ggside Panel Options

Source: https://context7.com/jtlandis/ggside/llms.txt

Configures side panel behavior including position, scale settings, collapse options, axis rendering, and label spacing using the ggside() function. Ensure ggplot2 and ggside libraries are loaded.

```r
library(ggplot2)
library(ggside)

# Configure side panel positions and collapse behavior
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point(size = 2) +
  geom_xsidedensity(position = "stack") +
  geom_ysidedensity(position = "stack") +
  ggside(
    x.pos = "bottom",           # xside panel at bottom (default: "top")
    y.pos = "left",             # yside panel at left (default: "right")
    scales = "free",            # free scales for side panels
    collapse = "all",           # collapse both x and y side panels
    draw_x_on = "main",         # render x-axis on main panel
    draw_y_on = "side",         # render y-axis on side panel
    respect_side_labels = "all" # respect labels on all side panels
  )
```

--------------------------------

### Basic ggside Usage with Density Plots

Source: https://github.com/jtlandis/ggside/blob/main/README.md

Demonstrates adding density plots to the x and y sides of a ggplot using geom_xsidedensity and geom_ysidedensity. The side panels share the x-axis with the main panel but have independent y-axes.

```r
library(ggplot2)
library(ggside)

ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point(size = 2) +
  geom_xsidedensity(aes(y = after_stat(density)), position = "stack") +
  geom_ysidedensity(aes(x = after_stat(density)), position = "stack") +
  theme(axis.text.x = element_text(angle = 90, vjust = .5))
```

--------------------------------

### Continuous Scale with Limits

Source: https://context7.com/jtlandis/ggside/llms.txt

Applies a continuous scale to the xside panel with specified limits.

```r
library(ggplot2)
library(ggside)

# Continuous scale with limits
ggplot(mpg, aes(hwy, class, colour = class)) +
  geom_boxplot() +
  geom_xsidedensity(position = "stack") +
  theme(ggside.panel.scale = .3) +
  scale_xsidey_continuous(minor_breaks = NULL, limits = c(NA, 1))
```

--------------------------------

### Separate Side Panel Colour Scale

Source: https://context7.com/jtlandis/ggside/llms.txt

Illustrates using `scale_xcolour` for separate color mappings in side panels.

```r
# Using xcolour for side panel colour
ggplot(iris, aes(Sepal.Width, Sepal.Length)) +
  geom_point() +
  geom_xsidepoint(aes(y = Petal.Width, xcolour = Petal.Length)) +
  scale_colour_steps(aesthetics = "xcolour",
                     guide = guide_colorbar(available_aes = "xcolour"))
```

--------------------------------

### Create Side Bar and Column Charts with ggplot2

Source: https://context7.com/jtlandis/ggside/llms.txt

Generates side bar and column charts using geom_xsidebar, geom_ysidebar, geom_xsidecol, and geom_ysidecol. Bar charts use stat_count by default, while column variants use stat_identity for pre-computed values. Load ggplot2 and ggside libraries.

```r
library(ggplot2)
library(ggside)

# Basic side bars (using stat_count)
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species, fill = Species)) +
  geom_point() +
  geom_xsidebar() +
  geom_ysidebar()
```

```r
# Side columns (using stat_identity with global mapping)
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species, fill = Species)) +
  geom_point() +
  geom_xsidecol() +
  geom_ysidecol()
```

--------------------------------

### Basic ggside Theme Customization

Source: https://context7.com/jtlandis/ggside/llms.txt

Applies custom theme elements to ggside panels, including scale, border, grid, and background.

```r
library(ggplot2)
library(ggside)

# Basic theme customization
ggplot(iris, aes(Sepal.Width, Sepal.Length, fill = Species)) +
  geom_point(aes(color = Species)) +
  geom_xsidedensity(alpha = .3, position = "stack") +
  geom_ysideboxplot(aes(x = Species), orientation = "x") +
  scale_ysidex_discrete(guide = guide_axis(angle = 45)) +
  theme_dark() +
  theme(
    ggside.panel.scale = .3,                                    # panel size ratio
    ggside.panel.border = element_rect(NA, "red", linewidth = 2), # border styling
    ggside.panel.grid = element_line("black", linewidth = .1, linetype = "dotted"),
    ggside.panel.background = element_blank()
  ) +
  guides(color = "none", fill = "none")
```

--------------------------------

### Basic Side Density Plots

Source: https://context7.com/jtlandis/ggside/llms.txt

Displays basic kernel density estimates on both the x and y sides of the main panel. Uses `geom_xsidedensity` and `geom_ysidedensity` with `position = "stack"`.

```r
library(ggplot2)
library(ggside)

# Basic density distributions on both sides
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point(size = 2) +
  geom_xsidedensity(aes(y = after_stat(density)), position = "stack") +
  geom_ysidedensity(aes(x = after_stat(density)), position = "stack") +
  theme(axis.text.x = element_text(angle = 90, vjust = .5))
```

--------------------------------

### Density-Scaled Side Histograms

Source: https://context7.com/jtlandis/ggside/llms.txt

Displays side histograms with density scaling using `aes(y = after_stat(density))` and `aes(x = after_stat(density))`.

```r
library(ggplot2)
library(ggside)

# Density-scaled histograms
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species, fill = Species)) +
  geom_point() +
  geom_xsidehistogram(aes(y = after_stat(density)), binwidth = 0.1) +
  geom_ysidehistogram(aes(x = after_stat(density)), binwidth = 0.1)
```

--------------------------------

### Create Side Line and Path Plots with ggplot2

Source: https://context7.com/jtlandis/ggside/llms.txt

Generates side line and path plots using geom_xsideline, geom_ysideline, geom_xsidepath, and geom_ysidepath for displaying connected data points in side panels. Lines connect points in order of the x variable, while paths connect points in data order. Requires ggplot2 and ggside libraries.

```r
library(ggplot2)
library(ggside)

# Side line with time series data
ggplot(economics, aes(date, pop)) +
  geom_xsideline(aes(y = unemploy)) +
  geom_col()
```

--------------------------------

### scale_xsidey_* / scale_ysidex_* Functions

Source: https://context7.com/jtlandis/ggside/llms.txt

These functions provide position scales for controlling the independent axis of side panels, allowing fine-grained control over the y-axis of xside panels and the x-axis of yside panels.

```APIDOC
## scale_xsidey_* / scale_ysidex_*

### Description
Position scales for controlling the independent axis of side panels. These scales allow fine-grained control over the y-axis of xside panels (xsidey) and the x-axis of yside panels (ysidex).

### Request Example
scale_xsidey_continuous(minor_breaks = NULL, limits = c(NA, 1))
scale_xsidey_discrete(guide = guide_axis(angle = 45))
scale_xsidey_log10()
scale_xsidey_binned(n.breaks = 4)
```

--------------------------------

### Facet Wrap with Side Panels

Source: https://context7.com/jtlandis/ggside/llms.txt

Integrates ggside panels with `facet_wrap` for creating faceted plots with side panels.

```r
library(ggplot2)
library(ggside)

# Facet wrap with side panels
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point() +
  geom_xsidedensity() +
  geom_ysidedensity() +
  facet_wrap(~cyl) +
  theme(ggside.panel.scale = .2)
```

--------------------------------

### Binned Scale for Side Panels

Source: https://context7.com/jtlandis/ggside/llms.txt

Utilizes a binned scale for the xside panel.

```r
# Binned scale
ggplot(iris, aes(Sepal.Width, Sepal.Length)) +
  geom_point() +
  geom_xsidepoint(aes(y = Petal.Width)) +
  scale_xsidey_binned(n.breaks = 4)
```

--------------------------------

### Create Side Tile Plots with ggplot2

Source: https://context7.com/jtlandis/ggside/llms.txt

Generates side tile plots using geom_xsidetile and geom_ysidetile for displaying rectangular tiles filled with color in side panels. Useful for showing categorical metadata or heatmap-style information. Requires ggplot2, ggside, dplyr, and tidyr libraries.

```r
library(ggplot2)
library(ggside)
library(dplyr)
library(tidyr)

# Tile plot with side metadata
df <- mutate(diamonds,
             colclar = interaction(color, clarity, sep = "_", drop = TRUE)) %>%
      group_by(color, clarity, colclar, cut) %>%
      summarise(m_price = mean(price))

xside_data <- df %>%
  ungroup() %>%
  select(colclar, clarity, color) %>%
  mutate_all(~factor(as.character(.x), levels = levels(.x))) %>%
  pivot_longer(cols = c(clarity, color)) %>%
  distinct()

ggplot(df, aes(x = colclar, cut)) +
  geom_tile(aes(fill = m_price)) +
  viridis::scale_fill_viridis(option = "magma") +
  theme(axis.text.x = element_blank()) +
  geom_xsidetile(data = xside_data, aes(y = name, xfill = value)) +
  guides(xfill = guide_legend(nrow = 8))
```

--------------------------------

### Side Density Plots with Scaled Output

Source: https://context7.com/jtlandis/ggside/llms.txt

Demonstrates density plots with different scaled outputs for y-axis (`after_stat(count)`) and x-axis (`after_stat(scaled)`).

```r
library(ggplot2)
library(ggside)

# Density with scaled output
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point(size = 2) +
  geom_xsidedensity(aes(y = after_stat(count)), position = "stack") +
  geom_ysidedensity(aes(x = after_stat(density))) + 
  theme(axis.text.x = element_text(angle = 90, vjust = .5))
```

--------------------------------

### Basic Side Histograms

Source: https://context7.com/jtlandis/ggside/llms.txt

Generates basic side histograms using `geom_xsidehistogram` and `geom_ysidehistogram` to display frequency distributions alongside scatter plots.

```r
library(ggplot2)
library(ggside)

# Basic side histograms with scatter plot
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species, fill = Species)) +
  geom_point() +
  geom_xsidehistogram(binwidth = 0.1) +
  geom_ysidehistogram(binwidth = 0.1)
```

--------------------------------

### Faceting with ggside

Source: https://context7.com/jtlandis/ggside/llms.txt

Integration with ggplot2's faceting system, including support for facet_wrap and facet_grid with options for scale sharing and panel collapse.

```APIDOC
## Faceting with ggside

### Description
ggside works seamlessly with ggplot2's faceting system including facet_wrap and facet_grid, with options to control scale sharing and panel collapse behavior.

### Parameters
- **collapse** (string) - Options like "all" to collapse side panels
- **scales** (string) - Options like "free_y" to control scale sharing
```

--------------------------------

### Separate Side Panel Scaling

Source: https://context7.com/jtlandis/ggside/llms.txt

Customizes the scaling and spacing for x and y side panels independently.

```r
# Separate x and y side panel scaling
ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  geom_xsidedensity() +
  geom_ysidehistogram() +
  theme(
    ggside.panel.scale.x = .2,  # xside panel scale
    ggside.panel.scale.y = .4,  # yside panel scale
    ggside.panel.spacing.x = unit(5, "pt"),  # spacing between main and yside
    ggside.panel.spacing.y = unit(2, "pt")   # spacing between main and xside
  )
```

--------------------------------

### Independent Side Panel Scales

Source: https://context7.com/jtlandis/ggside/llms.txt

Demonstrates how to prevent the main scale from affecting side panels using `scale_ysidex_continuous()` for an independent x-axis scale in the y-side panel.

```r
library(ggplot2)
library(ggside)

ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  geom_xsidehistogram() +
  geom_ysidehistogram() +
  scale_x_continuous(
    breaks = seq(1, 6, 1),
    limits = c(1, 6)
  ) +
  scale_ysidex_continuous()  # ensures independent x-axis for y-side panel
```

--------------------------------

### Create Side Violin Plots with ggplot2

Source: https://context7.com/jtlandis/ggside/llms.txt

Generates side violin plots using geom_xsideviolin and geom_ysideviolin to display kernel density estimates. Useful for comparing distributions across groups in side panels. Ensure ggplot2 and ggside libraries are loaded.

```r
library(ggplot2)
library(ggside)

# Basic side violins
df <- expand.grid(UpperCase = LETTERS, LowerCase = letters)
df$Combo_Index <- as.integer(df$UpperCase) * as.integer(df$LowerCase)

ggplot(df, aes(UpperCase, LowerCase)) +
  geom_tile(aes(fill = Combo_Index)) +
  geom_xsideviolin(aes(y = Combo_Index)) +
  geom_ysideviolin(aes(x = Combo_Index))
```

```r
# Violins with swapped orientation
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species)) +
  geom_xsideviolin(aes(y = Species), orientation = "y") +
  geom_point()
```

```r
# Mixing discrete and continuous with type recasting
ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species)) +
  geom_point() +
  geom_xsideviolin(aes(y = as.numeric(Species)), orientation = "y") +
  geom_ysideviolin(aes(x = as.numeric(Species)), orientation = "x")
```

--------------------------------

### Log Transform on Side Scales

Source: https://context7.com/jtlandis/ggside/llms.txt

Applies a logarithmic transformation to the xside panel scale.

```r
# Log transform on side scales
ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  geom_xsidehistogram() +
  scale_xsidey_log10()
```

--------------------------------

### Mixing Discrete and Continuous Axes with ggside

Source: https://github.com/jtlandis/ggside/blob/main/README.md

Illustrates mixing discrete and continuous axes in ggside plots without needing explicit scale functions. geom_xsideboxplot and geom_ysidedensity are used here.

```r
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point(size = 2) +
  geom_xsideboxplot(aes(y =class), orientation = "y") +
  geom_ysidedensity(aes(x = after_stat(density)), position = "stack") +
  scale_ysidex_continuous(guide = guide_axis(angle = 90), minor_breaks = NULL) +
  theme(ggside.panel.scale = .3)
```

--------------------------------

### Create Side Point Plots with ggplot2

Source: https://context7.com/jtlandis/ggside/llms.txt

Generates side point plots using geom_xsidepoint and geom_ysidepoint to display individual data points in side panels. Useful for showing metadata or additional variables aligned with the main panel's axis. Ensure ggplot2 and ggside libraries are loaded.

```r
library(ggplot2)
library(ggside)

# Side points showing additional variables
ggplot(diamonds, aes(depth, table, alpha = .2)) +
  geom_point() +
  geom_ysidepoint(aes(x = price)) +
  geom_xsidepoint(aes(y = price)) +
  theme(ggside.panel.scale = .3)
```

```r
# Binned scale with side points
ggplot(iris, aes(Sepal.Width, Sepal.Length)) +
  geom_point() +
  geom_xsidepoint(aes(y = Petal.Width, xcolour = Petal.Length)) +
  scale_xsidey_binned(n.breaks = 4) +
  scale_colour_steps(aesthetics = "xcolour",
                     guide = guide_colorbar(available_aes = "xcolour")) +
  theme(ggside.panel.scale.x = .3)
```

--------------------------------

### ggside Theme Elements

Source: https://context7.com/jtlandis/ggside/llms.txt

Theme elements specific to ggside for customizing the appearance of side panels including panel scale, spacing, background, grid lines, and axis elements.

```APIDOC
## ggside Theme Elements

### Description
Theme elements specific to ggside for customizing the appearance of side panels including panel scale, spacing, background, grid lines, and axis elements.

### Parameters
- **ggside.panel.scale** (numeric) - Panel size ratio
- **ggside.panel.border** (element) - Border styling
- **ggside.panel.grid** (element) - Grid line styling
- **ggside.panel.spacing.x** (unit) - Spacing between main and yside
- **ggside.panel.spacing.y** (unit) - Spacing between main and xside
```

--------------------------------

### Remedy positional scale issues with explicit declaration

Source: https://github.com/jtlandis/ggside/blob/main/README.md

Use this approach to resolve missing data or warnings by explicitly declaring the main panel scale.

```r
ggplot(iris, aes(Sepal.Width)) + 
  geom_density() + 
  geom_xsidepoint(aes(y = Species)) +
  scale_y_continuous() 
```

--------------------------------

### Side Boxplots with Continuous Data

Source: https://context7.com/jtlandis/ggside/llms.txt

Illustrates side boxplots for continuous data summaries using `geom_xsideboxplot` and `geom_ysideboxplot`. Custom scales are applied to both side axes.

```r
library(ggplot2)
library(ggside)

df <- expand.grid(UpperCase = LETTERS, LowerCase = letters)
df$Combo_Index <- as.integer(df$UpperCase) * as.integer(df$LowerCase)

ggplot(df, aes(UpperCase, LowerCase)) +
  geom_tile(aes(fill = Combo_Index)) +
  geom_xsideboxplot(aes(y = Combo_Index)) +
  geom_ysideboxplot(aes(x = Combo_Index)) +
  scale_xsidey_continuous() +
  scale_ysidex_continuous()
```

--------------------------------

### Side Boxplots with Mixed Axes

Source: https://context7.com/jtlandis/ggside/llms.txt

Creates side boxplots using `geom_xsideboxplot` with a discrete y-axis and a continuous y-axis for the main plot. Includes custom scaling for the side x-axis.

```r
library(ggplot2)
library(ggside)

# Boxplot with mixed discrete and continuous axes
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point(size = 2) +
  geom_xsideboxplot(aes(y = class), orientation = "y") +
  geom_ysidedensity(aes(x = after_stat(density)), position = "stack") +
  scale_ysidex_continuous(guide = guide_axis(angle = 90), minor_breaks = NULL) +
  theme(ggside.panel.scale = .3)
```

--------------------------------

### Side Boxplots with Swapped Orientation

Source: https://context7.com/jtlandis/ggside/llms.txt

Shows side boxplots with a swapped orientation using `geom_xsideboxplot` where the y-axis is discrete and the x-axis is continuous. `scale_xsidey_discrete()` is used.

```r
library(ggplot2)
library(ggside)

ggplot(iris, aes(Sepal.Width, Sepal.Length, color = Species)) +
  geom_xsideboxplot(aes(y = Species), orientation = "y") +
  geom_point() +
  scale_y_continuous() +
  scale_xsidey_discrete()
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.