The main way to create tables and figures for your asar
report is by using functions within the stockplotr package.
However, if stockplotr doesn’t contain the functions to
make tables or figures you need, you may wish to add custom tables or
figures to your report. Here, we provide multiple workflow options for
doing so.
| Workflow Options for Custom Tables and Figures | ||||
| Workflow | Summary | Appropriate if... | Pros | Cons |
|---|---|---|---|---|
| 1: Direct image insertion workflow | Take minimal steps to add an external file to your report in this format:
|
|
|
|
| 2: rda-based workflow | Make an rda containing your table/figure, caption, and alternative text, then add each into your report in the same way that non-custom tables/figures are added. |
|
|
|
| 3: Direct coding-in-qmd workflow | Code, and plot, your table or figure directly in a Quarto document. |
|
|
|
Once you know what your tables and figures look like, write your own captions and alternative text. Custom tables will require captions only.
Check out the stockplotr ‘captions_alt_text_template.csv’
file, which contains the templates for each table or figure’s
caption/alternative text, to get a sense of how each description is
structured. Then, refer to the
accessibility vignette’s guide to learn how to write clear and
comprehensive alternative text.
We recommend adding in key quantities, like maximum and minimum values, to ensure your captions and alternative text clearly describe your plots. For example, if you’re showing how biomass changed over time, we recommend providing the maximum and minimum values of biomass and years shown, instead of simply stating that a figure shows biomass changing over time. Check out the “How captions and alternative text are generated” vignette to see how we extract certain key quantities from the model results files. You are welcome to use and adapt that code to your own results to calculate key quantities, or calculate the quantities with your own code.
Do you have an existing captions_alt_text.csv file? If you’ve already
generated a figure or table rda, this file should exist, most likely in
your working directory. If you don’t have one, run a
stockplotr plotting function (e.g.,
plot_biomass(make_rda = TRUE),
table_bnc(make_rda = TRUE)) to generate the file.
Open captions_alt_text.csv file, then add your text. The file is set up like this:
| label | type | caption | alt_text |
|---|---|---|---|
| example_fig | figure | Example caption for figure. | Example alternative text for figure. |
| example_tab | table | Example caption for table. |
NOTE: Only the alternative text will be used in your final report- not the caption. This happens because of the workaround workflow that allows us to add alt text into PDFs. The caption will be taken from your directly-coded image’s markdown code, so you can leave it empty or put the same caption here; it doesn’t matter.
In your ‘report’ folder, open your figures and tables docs (probably named something like ‘08_tables.qmd’ and ‘09_figures.qmd’). Add the following code there.
IMPORTANT: The label in your captions/alt text csv must match the label in your plot’s chunk options, MINUS the “fig-” or “tab-”. For example, the label “your_image_label_name” in the csv would match up properly with the “tbl-your_image_label_name” label in this code:
{width=4in #fig-your_image_label_name}The same rule applies for tables: “custom_table2” in the csv would match up with “tbl-custom_table2” in the markdown’s label.
If you’re using this workflow, your table/figure should be at most 8” wide or can be shrunken to 8” wide and still be legible. Find the width of your image file. Would you prefer to show it on a page with a portrait orientation (can fit 5” width) or landscape orientation (can fit 8” width)?
Identify the preferred width of your image. Keep it in mind for when you add your image in the next section.
Next, add your image in this format (see this Quarto documentation for more information):
NOTE: Captions and alternative text in this markdown format will appear in your final report file. However, we strongly encourage adding the caption and alt text in the captions_alt_text.csv file as well, where your other figures and tables’ captions and alt text are stored, for reproducibility and clarity when reusing report templates.
NOTE: It can be a headache to specify the correct image path. We recommend placing your files in either of these places:
Here are some examples, using the following example folder structure setup:
If you’d like to place your image on a landscape-oriented page, you’ll add landscape braces before and after your table/figure to ensure it will be displayed properly, like this:
{width=___in #fig-your_image_label_name}Then, add three colons to close the braces:
NOTE: Landscape braces only work in Quarto v1.6+. Please read this Discussion to learn how to check your Quarto version and update it if necessary.
First, write the code to produce (but not export; that’s a future
step!) your custom tables and figures. Save each table and figure as an
object (e.g., in the examples below, your_table and
your_figure). Save the script somewhere safe.
# Example dataframe
your_df <- data.frame(
"x" = c(1, 2, 3),
"y" = c(4, 5, 6)
)
# Example table
your_table <- gt::gt(your_df)
# Example figure
your_figure <- ggplot2::ggplot(
your_df,
aes(
x = x,
y = y
)
) +
ggplot2::geom_point()Once you know what your tables and figures look like, write your own captions and alternative text. Custom tables will require captions only.
Check out the stockplotr ‘captions_alt_text_template.csv’
file, which contains the templates for each table or figure’s
caption/alternative text, to get a sense of how each description is
structured. Then, refer to the
accessibility vignette’s guide to learn how to write clear and
comprehensive alternative text.
We recommend adding in key quantities, like maximum and minimum values, to ensure your captions and alternative text clearly describe your plots. For example, if you’re showing how biomass changed over time, we recommend providing the maximum and minimum values of biomass and years shown, instead of simply stating that a figure shows biomass changing over time. Check out the “How captions and alternative text are generated” vignette to see how we extract certain key quantities from the model results files. You are welcome to use and adapt that code to your own results to calculate key quantities, or calculate the quantities with your own code.
Do you have an existing captions_alt_text.csv file? If you’ve already
generated a figure or table rda, this file should exist, most likely in
your working directory. If you don’t have one, run a
stockplotr plotting function (e.g.,
plot_biomass(make_rda = TRUE),
table_bnc(make_rda = TRUE)) to generate the file.
Open captions_alt_text.csv file, then add your text. The file is set up like this:
| label | type | caption | alt_text |
|---|---|---|---|
| example_fig | figure | Example caption for figure. | Example alternative text for figure. |
| example_tab | table | Example caption for table. |
Next, export your tables and figures to rda files. This code was
adapted from functions like stockplotr::plot_biomass.
Import your csv containing your captions and alternative text and save it as an object. Then, save the captions and alternative text as separate objects. For example:
# Import captions and alternative text
my_text <- read.csv(file = "captions_alt_text.csv")
# Extract table caption
my_table_cap <- my_text |>
dplyr::filter(
label == "example_table",
type == "table"
) |>
dplyr::select(caption) |>
as.character()
# Extract figure caption
my_figure_cap <- my_text |>
dplyr::filter(
label == "example_fig",
type == "figure"
) |>
dplyr::select(caption) |>
as.character()
# Extract figure alternative text
my_figure_alt_text <- my_text |>
dplyr::filter(
label == "example_fig",
type == "figure"
) |>
dplyr::select(alt_text) |>
as.character()NOTE: Your label must match the label associated with your table or figure in your csv containing the captions and alternative text. If it does not match, the label will not be extracted properly and added to your rdas.
Your rdas will contain your table or figure, caption, and alternative text (if it’s a figure).
rda <- list(
"table" = your_table, # your table object
"caption" = my_table_cap # your table caption
)
rda <- list(
"figure" = your_figure, # your figure object
"caption" = my_figure_cap, # your figure caption
"alt_text" = my_figure_alt_text # your figure alternative text
)Do you already have ‘figures’ and ‘tables’ folders? Hint: both should be in your working directory. If yes: Great! You can skip this step. If not, simply enter the code below to make the folders.
dir.create(fs::path(getwd(), "figures"))
dir.create(fs::path(getwd(), "tables"))This will produce an rda called “example_table.rda” and save it in your ‘tables’ folder.
IMPORTANT: Your table must have “_table” before the .rda file extension. For example, “custom_table1.rda” wouldn’t work, but “custom1_table.rda” would work.
Skip this section if you are not including custom tables.
Your next step is to get a sense of your table dimensions. You’ll ask:
This section contains the steps to answer these questions.
NOTE: This workflow is reflected in the create_tables_doc.R file and its associated functions (such as
render_lg_table(),ID_tbl_length_class(),ID_tbl_width_class(), andexport_split_tbls()).
Run this code:
my_plot_name <- "example_table.rda" # replace this with the filename of your table rda
tables_dir <- getwd() # replace this with the location of your tables folder
# Identify table width class
tbl_orient <- ID_tbl_width_class(
plot_name = gsub("_table.rda", "", my_plot_name),
tables_dir = tables_dir,
portrait_pg_width = 5 # 5 inches = the threshold for maximum table width before it needs to be resized, rotated, and/or split
)
# Identify table length class
tbl_length <- ID_tbl_length_class(
plot_name = gsub("_table.rda", "", my_plot_name),
tables_dir = tables_dir
)
table_specs <- list(tbl_orient, tbl_length)
# Identify table dimension class (length x width)
tbl_class <- dplyr::case_when(
table_specs[[1]] == "regular" & table_specs[[2]] == "regular" ~ "reg_reg",
table_specs[[1]] == "regular" & table_specs[[2]] == "long" ~ "reg_long",
table_specs[[1]] == "wide" & table_specs[[2]] == "regular" ~ "wide_reg",
table_specs[[1]] == "wide" & table_specs[[2]] == "long" ~ "wide_long",
table_specs[[1]] == "extra-wide" & table_specs[[2]] == "regular" ~ "ewide_reg",
table_specs[[1]] == "extra-wide" & table_specs[[2]] == "long" ~ "ewide_long",
TRUE ~ "unknown"
)
max_rows <- ifelse(tbl_orient == "regular", 38, 28)
print(paste0("Your table dimension is ", tbl_class, ". The maximum number of table rows per page is ", max_rows, "."))
tables_path <- fs::path(
tables_dir,
"tables",
my_plot_name
)
load(tables_path)
# Get table length in rows
split_table_rows <- length(rda[[1]]$`_data`[[1]])
split_tables_rowwise <- ceiling(split_table_rows / max_rows)
if (tbl_length == "long") {
print(paste0("Your table must be split row-wise. Each table can have, at most, ", max_rows, "rows."))
}
if (tbl_orient == "extra-wide") {
print(paste0("Your table must be split column-wise. Proceed to the section 'Table splitting' (regarding extra-wide tables) to identify the number of smaller tables your original table must be split into."))
}You should see one of six outputs: reg_reg, reg_long, wide_reg, wide_long, ewide_reg, or ewide_long.
| Classification | reg_reg | reg_long | wide_reg | wide_long | ewide_reg | ewide_long |
| Dimensions | Regular width & length | Regular width, long | Wide, regular length | Wide, long | Extra-wide, regular length | Extra-wide, long |
| Table width | < 5” wide | < 5” wide | at least 5” and up to 12” wide | at least 5” and up to 12” wide | >12” wide | >12” wide |
| Table length1 | <= 38 rows | > 38 rows | <= 28 rows | > 28 rows | <= 28 rows | > 28 rows |
Regular-length tables
If your output is reg_reg, you can display your table in a .qmd chunk without any additional steps. Jump to section Add custom tables and figures and proceed.
If your output is wide_reg, you will place your table’s .qmd chunk in special braces that change the page orientation to landscape. Jump to section Add custom tables and figures and proceed.
If your output is ewide_reg, you will place your table’s .qmd chunk in special braces that change the page orientation to landscape and split it into narrower tables, each of which are displayed on separate pages. Proceed to the section Table splitting.
Long tables
If your output is reg_long, you will split your table into shorter tables, each of which are displayed on separate pages. Proceed to the section Table splitting.
If your output is wide_long, you will place your table’s .qmd chunk in special braces that change the page orientation to landscape and split your table into shorter tables, each of which are displayed on separate pages. Proceed to the section Table splitting.
If your output is ewide_long, you will place your table’s .qmd chunk in special braces that change the page orientation to landscape; split it into narrower tables, each of which are displayed on separate pages; and split your table into shorter tables, each of which are displayed on separate pages. Proceed to the section Table splitting.
Extra-wide tables will need to be split among multiple pages. Run this code to learn the number of tables into which your original table will be split (by column) and export the split tables (as a list) into a new rda:
my_plot_name <- "example_table.rda" # replace this with the filename of your table rda
tables_dir <- getwd() # replace this with the location of your tables folder
essential_cols <- 1:2 # replace this with the columns that will be retained between the split tables, formatted as a sequence (e.g., 1:2 for columns 1-2, or 1 for a single column)
export_split_tbls(
tables_dir = tables_dir,
plot_name = my_plot_name,
essential_columns = essential_cols
)If the number returned was, say, 5, then since each split table must be in its own chunk, you will need 5 chunks to show your split tables by column (if your table is ewide-long, then you must also split tables by row). You will also need an additional chunk to load in the data. Each table needs its own chunk, and therefore label, so that it can be cross-referenced in text.
You can check out your split tables in the new rda saved in your tables_dir folder. It will have the same filename as your original rda except that it will contain “_split” in the filename. For instance, split tables created from “example_table.rda” will be saved in “example_table_table_split.rda”.
Long tables will need to be split among multiple pages. Refer to the code chunk above to learn the number of tables into which your original table will be split by row.
If the number returned was, say, 3, then since each split table must be in its own chunk, you will need 3 chunks to show your split tables by row. You will also need an additional chunk to load in the data. Each table needs its own chunk, and therefore label, so that it can be cross-referenced in text.
This step will alter your figures and tables docs (probably named something like ‘08_tables.qmd’ and ‘09_figures.qmd’), located in your ‘report’ folder.
As a reminder, this workflow assumes that you have tables and/or figures stored in rda files. If you don’t have those rda files, please see the Export your custom tables and figures section to create them.
IMPORTANT: The label in your captions/alt text csv must match the label in your plot’s chunk options, MINUS the “fig-” or “tab-”. For example, the label “custom_table3” in the csv would match up properly with the “tbl-custom_table3” label in a code chunk. The same rule applies for figures: “custom_figure1” in the csv would match up with “fig-custom_figure1” in the chunk options’ label.
To add figures, first ensure that your folder containing the figures is called “figures”.
Then, there are only two arguments to fill out:
subdir: The location where the new figures doc
should be saved (we recommend your ‘report’ folder, so it overwrites the
old, empty version)figures_dir: The location of your “figures” folder
create_figures_doc(
subdir = fs::path(getwd(), "report"), # indicates the new figures doc will be saved in your "report" folder, located in the working directory
figures_dir = getwd() # indicates your "figures" folder is located in the working directory
)In your figures doc, you’ll notice the following structure:
Chunk 1 will always create an object saving the
location of your figures_dir.
Then, there will be at least two chunks for each figure. For each figure,
Chunk 2 will:
Chunk 3 will:
Adding tables entails nearly the same process as described for figures. The only differences are:
create_tables_doc()
and why some tables are split into several code chunks.To add tables to the {asar} tables doc:
create_tables_doc(
subdir = fs::path(getwd(), "report"),
tables_dir = getwd()
)First, write the code to produce (but not export; that’s a future
step!) your custom tables and figures. Save each table and figure as an
object (e.g., in the examples below, your_table and
your_figure). Save the script somewhere safe.
# Example dataframe
your_df <- data.frame(
"x" = c(1, 2, 3),
"y" = c(4, 5, 6)
)
# Example table
your_table <- gt::gt(your_df)
# Example figure
your_figure <- ggplot2::ggplot(
your_df,
aes(
x = x,
y = y
)
) +
ggplot2::geom_point()Once you know what your tables and figures look like, write your own captions and alternative text. Custom tables will require captions only.
Check out the stockplotr ‘captions_alt_text_template.csv’
file, which contains the templates for each table or figure’s
caption/alternative text, to get a sense of how each description is
structured. Then, refer to the
accessibility vignette’s guide to learn how to write clear and
comprehensive alternative text.
We recommend adding in key quantities, like maximum and minimum values, to ensure your captions and alternative text clearly describe your plots. For example, if you’re showing how biomass changed over time, we recommend providing the maximum and minimum values of biomass and years shown, instead of simply stating that a figure shows biomass changing over time. Check out the “How captions and alternative text are generated” vignette to see how we extract certain key quantities from the model results files. You are welcome to use and adapt that code to your own results to calculate key quantities, or calculate the quantities with your own code.
Skip this section if you are not including custom tables.
Your next step is to get a sense of your table dimensions. You’ll ask:
This section contains the steps to answer these questions.
NOTE: This workflow is reflected in the create_tables_doc.R file and its associated functions (such as
render_lg_table(),ID_tbl_length_class(),ID_tbl_width_class(), andexport_split_tbls()).
Run this code:
my_plot_name <- "example_table.rda" # replace this with the filename of your table rda
tables_dir <- getwd() # replace this with the location of your tables folder
# Identify table width class
tbl_orient <- ID_tbl_width_class(
plot_name = gsub("_table.rda", "", my_plot_name),
tables_dir = tables_dir,
portrait_pg_width = 5 # 5 inches = the threshold for maximum table width before it needs to be resized, rotated, and/or split
)
# Identify table length class
tbl_length <- ID_tbl_length_class(
plot_name = gsub("_table.rda", "", my_plot_name),
tables_dir = tables_dir
)
table_specs <- list(tbl_orient, tbl_length)
# Identify table dimension class (length x width)
tbl_class <- dplyr::case_when(
table_specs[[1]] == "regular" & table_specs[[2]] == "regular" ~ "reg_reg",
table_specs[[1]] == "regular" & table_specs[[2]] == "long" ~ "reg_long",
table_specs[[1]] == "wide" & table_specs[[2]] == "regular" ~ "wide_reg",
table_specs[[1]] == "wide" & table_specs[[2]] == "long" ~ "wide_long",
table_specs[[1]] == "extra-wide" & table_specs[[2]] == "regular" ~ "ewide_reg",
table_specs[[1]] == "extra-wide" & table_specs[[2]] == "long" ~ "ewide_long",
TRUE ~ "unknown"
)
max_rows <- ifelse(tbl_orient == "regular", 38, 28)
print(paste0("Your table dimension is ", tbl_class, ". The maximum number of table rows per page is ", max_rows, "."))
tables_path <- fs::path(
tables_dir,
"tables",
my_plot_name
)
load(tables_path)
# Get table length in rows
split_table_rows <- length(rda[[1]]$`_data`[[1]])
split_tables_rowwise <- ceiling(split_table_rows / max_rows)
if (tbl_length == "long") {
print(paste0("Your table must be split row-wise. Each table can have, at most, ", max_rows, "rows."))
}
if (tbl_orient == "extra-wide") {
print(paste0("Your table must be split column-wise. Proceed to the section 'Table splitting' (regarding extra-wide tables) to identify the number of smaller tables your original table must be split into."))
}You should see one of six outputs: reg_reg, reg_long, wide_reg, wide_long, ewide_reg, or ewide_long.
| Classification | reg_reg | reg_long | wide_reg | wide_long | ewide_reg | ewide_long |
| Dimensions | Regular width & length | Regular width, long | Wide, regular length | Wide, long | Extra-wide, regular length | Extra-wide, long |
| Table width | < 5” wide | < 5” wide | at least 5” and up to 12” wide | at least 5” and up to 12” wide | >12” wide | >12” wide |
| Table length2 | <= 38 rows | > 38 rows | <= 28 rows | > 28 rows | <= 28 rows | > 28 rows |
Regular-length tables
If your output is reg_reg, you can display your table in a .qmd chunk without any additional steps. Jump to section Add custom tables and figures and proceed.
If your output is wide_reg, you will place your table’s .qmd chunk in special braces that change the page orientation to landscape. Jump to section Add custom tables and figures and proceed.
If your output is ewide_reg, you will place your table’s .qmd chunk in special braces that change the page orientation to landscape and split it into narrower tables, each of which are displayed on separate pages. Proceed to the section Table splitting.
Long tables
If your output is reg_long, you will split your table into shorter tables, each of which are displayed on separate pages. Proceed to the section Table splitting.
If your output is wide_long, you will place your table’s .qmd chunk in special braces that change the page orientation to landscape and split your table into shorter tables, each of which are displayed on separate pages. Proceed to the section Table splitting.
If your output is ewide_long, you will place your table’s .qmd chunk in special braces that change the page orientation to landscape; split it into narrower tables, each of which are displayed on separate pages; and split your table into shorter tables, each of which are displayed on separate pages. Proceed to the section Table splitting.
Extra-wide tables will need to be split among multiple pages. Run this code to learn the number of tables into which your original table will be split (by column) and export the split tables (as a list) into a new rda:
my_plot_name <- "example_table.rda" # replace this with the filename of your table rda
tables_dir <- getwd() # replace this with the location of your tables folder
essential_cols <- 1:2 # replace this with the columns that will be retained between the split tables, formatted as a sequence (e.g., 1:2 for columns 1-2, or 1 for a single column)
export_split_tbls(
tables_dir = tables_dir,
plot_name = my_plot_name,
essential_columns = essential_cols
)If the number returned was, say, 5, then since each split table must be in its own chunk, you will need 5 chunks to show your split tables by column (if your table is ewide-long, then you must also split tables by row). You will also need an additional chunk to load in the data. Each table needs its own chunk, and therefore label, so that it can be cross-referenced in text.
You can check out your split tables in the new rda saved in your tables_dir folder. It will have the same filename as your original rda except that it will contain “_split” in the filename. For instance, split tables created from “example_table.rda” will be saved in “example_table_table_split.rda”.
Long tables will need to be split among multiple pages. Refer to the code chunk above to learn the number of tables into which your original table will be split by row.
If the number returned was, say, 3, then since each split table must be in its own chunk, you will need 3 chunks to show your split tables by row. You will also need an additional chunk to load in the data. Each table needs its own chunk, and therefore label, so that it can be cross-referenced in text.
In your ‘report’ folder, open your figures and tables docs (probably named something like ‘08_tables.qmd’ and ‘09_figures.qmd’). Add the following code there.
IMPORTANT: The label in your captions/alt text csv must match the label in your plot’s chunk options, MINUS the “fig-” or “tab-”. For example, the label “custom_table1” in the csv would match up properly with the “tbl-custom_table1” label in a code chunk. The same rule applies for figures: “custom_figure1” in the csv would match up with “fig-custom_figure1” in the chunk options’ label.
Follow the instructions in the appropriate section below based on your table classification: reg_reg, reg_long, wide_reg, wide_long, ewide_reg, or ewide_long.
For all table types, add a setup chunk to define your table and its caption:
```{r}
#| label: 'tab-setup-custom'
#| include: false
# Example dataframe
your_df <- data.frame(
"x" = c(1, 2, 3),
"y" = c(4, 5, 6)
)
# Example table
your_table <- gt::gt(your_df)
# Define your caption
your_cap <- "This is the caption for my custom table."
```reg_reg)
Portrait orientation, fits on one page.
Add this chunk to display the table:
reg_long or wide_long)
Splits by row across multiple pages. wide_long uses
landscape; reg_long uses portrait.
You will need a separate chunk for each page of the split. For
example, if your table requires 2 pages, repeat this chunk twice,
changing the index in grp_pull(1) to
grp_pull(2).
Also, notice how gt_split() extracts subsets of rows
from the table to ensure it fits on one page. This function is from the
excellent gt package. There is a bug preventing the
gt function from working as expected, so we filed an issue
and submitted a pull
request that fixes the issue. Until it’s resolved, we’ve added the
fixed function to {asar} so users can access it via
asar::gt_split().
```{r}
#| label: 'tbl-custom-long-p1'
#| echo: false
#| tbl-cap: !expr paste0(your_cap, ' (Page 1 of 2)')
your_table |>
gt::tab_options(table.width = pct(100), table.layout = "auto") |>
gt::cols_width(everything() ~ pct(20)) |>
asar::gt_split(row_every_n = 38) |> # Use 28 for wide_long
gt::grp_pull(1) # Change this to 2 for the next page
```NOTE: For
wide_long, wrap the chunk in::: {.landscape}braces. For example:
ewide_reg)
Landscape orientation, split by column across multiple pages.
Because extra-wide tables are split by column, you must have already
run export_split_tbls()
to create the _split.rda file. Load that split file to
access the list of tables:
```{r}
#| label: 'tbl-setup-ewide-split'
#| include: false
# Load the list of split tables generated by export_split_tbls()
load(file.path(tables_dir, "example_tab_table_split.rda"))
table_list_split <- table_list
```Then, for each split table in the list, create a landscape chunk:
ewide_long)
Landscape orientation, split by both column AND row.
This requires a nested approach using the
table_list_split loaded above. You must create chunks for
every combination of column-split and row-split.
::: {.landscape}
```{r}
#| label: 'tbl-custom-ewide-long-c1-r1'
#| echo: false
#| tbl-cap: !expr paste0(your_cap, ' (Column split 1 of 2, Row split 1 of 3)')
table_list_split[[1]] |>
gt::tab_options(table.width = pct(100), table.layout = "auto") |>
gt::cols_width(everything() ~ pct(20)) |>
asar::gt_split(row_every_n = 28) |>
gt::grp_pull(1)
```
:::The next chunk would be identical except for a different label,
caption, and would have gt::grp_pull(2) instead of
gt::grp_pull(1), for instance. When adding the second split
table, add table_list_split[[2]] instead of
table_list_split[[1]], then change the label, caption, and
gt::grp_pull() as needed.
The workflow for figures is very similar to the workflow for regular tables: 1) add a chunk to define your figure, its caption, and its alternative text, and then 2) add a chunk to display the figure.
In your figures doc, add the following chunk to display the figure in your .qmd when it’s rendered:
```{r}
#| label: 'fig-custom1' # choose a label
#| echo: false
#| warning: false
#| fig-cap: !expr This is your figure caption.
#| fig-alt: !expr This is your figure alternative text.
# Import your data
your_df <- data.frame(
"x" = c(1, 2, 3),
"y" = c(4, 5, 6)
)
# Make your figure
your_figure <- ggplot2::ggplot(
your_df,
aes(
x = x,
y = y
)
) +
ggplot2::geom_point()
# Show your figure
your_figure
``` If you are adding another figure, add a page break first:
The maximum number of rows drops from 38 (for regular-width tables) to 28 (for wide or extra-wide tables) because the latter two tables are rotated on a landscape page, which offers less space for table rows.↩︎
The maximum number of rows drops from 38 (for regular-width tables) to 28 (for wide or extra-wide tables) because the latter two tables are rotated on a landscape page, which offers less space for table rows.↩︎