Create a collection of separate forest plots split by categorical variable values, with interactive sidebar navigation.
| Argument | Description |
|---|---|
x |
A WebSpec object or data frame |
by |
Column name(s) for splitting. Single string or character vector for hierarchical splits |
shared_axis |
If TRUE, use the same axis range across all plots (default: FALSE) |
... |
Additional arguments passed to web_spec() if x is a data frame |
A SplitForest object containing multiple WebSpec objects, one per unique combination of split values.
Creates one plot per unique value in the region column.
Creates plots for each combination (e.g., Male/Young, Male/Old, Female/Young, Female/Old) with nested navigation.
Forces all sub-plots to use the same axis range, enabling visual comparison across subgroups.
set.seed(42)
data <- data.frame(
study = paste0("Study ", 1:30),
region = sample(c("Americas", "Europe", "Asia"), 30, replace = TRUE),
or = exp(rnorm(30, log(0.8), 0.3)),
lower = NA, upper = NA
)
data$lower <- data$or * exp(-1.96 * 0.25)
data$upper <- data$or * exp(1.96 * 0.25)
forest_plot(data,
point = "or", lower = "lower", upper = "upper",
label = "study",
split_by = "region",
scale = "log", null_value = 1,
theme = web_theme_modern()
)Use a vector of column names for nested navigation:
forest_plot() - Render a forest plot (accepts split_by parameter)save_split_table() - Export all sub-plots to a directoryweb_spec() - Create a plot specification---
title: "split_table()"
---
```{r}
#| include: false
library(tabviz)
```
Create a collection of separate forest plots split by categorical variable values, with interactive sidebar navigation.
## Usage
```r
split_table(x, by, shared_axis = FALSE, ...)
```
## Arguments
| Argument | Description |
|----------|-------------|
| `x` | A `WebSpec` object or data frame |
| `by` | Column name(s) for splitting. Single string or character vector for hierarchical splits |
| `shared_axis` | If `TRUE`, use the same axis range across all plots (default: `FALSE`) |
| `...` | Additional arguments passed to `web_spec()` if `x` is a data frame |
## Value
A `SplitForest` object containing multiple `WebSpec` objects, one per unique combination of split values.
## Details
### Single Variable Split
```r
split_table(spec, by = "region")
```
Creates one plot per unique value in the `region` column.
### Hierarchical Split
```r
split_table(spec, by = c("sex", "age_group"))
```
Creates plots for each combination (e.g., Male/Young, Male/Old, Female/Young, Female/Old) with nested navigation.
### Shared Axis
```r
split_table(spec, by = "region", shared_axis = TRUE
)
```
Forces all sub-plots to use the same axis range, enabling visual comparison across subgroups.
## Examples
### Basic Split
```{r}
set.seed(42)
data <- data.frame(
study = paste0("Study ", 1:30),
region = sample(c("Americas", "Europe", "Asia"), 30, replace = TRUE),
or = exp(rnorm(30, log(0.8), 0.3)),
lower = NA, upper = NA
)
data$lower <- data$or * exp(-1.96 * 0.25)
data$upper <- data$or * exp(1.96 * 0.25)
forest_plot(data,
point = "or", lower = "lower", upper = "upper",
label = "study",
split_by = "region",
scale = "log", null_value = 1,
theme = web_theme_modern()
)
```
### Hierarchical Split
Use a vector of column names for nested navigation:
```r
forest_plot(data,
point = "or", lower = "lower", upper = "upper",
label = "study",
split_by = c("sex", "age_group"), # Creates nested tree navigation
scale = "log", null_value = 1
)
```
## Related Functions
- `forest_plot()` - Render a forest plot (accepts `split_by` parameter)
- `save_split_table()` - Export all sub-plots to a directory
- `web_spec()` - Create a plot specification
## See Also
- [Split Plots Guide](../guide/split-plots.qmd) for detailed usage
- [Gallery - Advanced Examples](../gallery-advanced.qmd) for visual examples