# Frequently asked questions

```
knitr::opts_chunk$set(
dpi = 300,
out.width = "100%",
collapse = TRUE,
comment = "#>"
)
```

# FAQ

Here are some of the common questions that have been asked in GitHub issues and on social media platforms.

## I just want the plot, not the statistical details. How can I turn them off?

All functions in `ggstatsplot`

that display results from statistical analysis in
a subtitle have argument `results.subtitle`

. Setting it to `FALSE`

will return
only the plot.

## What statistical test was carried out?

In case you are not sure what was the statistical test that produced the results
shown in the subtitle of the plot, the best way to get that information is to
either look at the documentation for the function used or check out the
associated vignette. For example, if you used the function `ggbetweenstats`

, the
details of the tests can be seen at the summary table.
Such summary tables are available for each function.

## Does `ggstatsplot`

work with `plotly`

?

The `plotly`

R graphing library makes it easy to produce interactive web
graphics via 'plotly.js'. `ggstatsplot`

functions are compatible with `plotly`

.

```
set.seed(123)
library(ggstatsplot)
library(plotly)
# will work
p <- ggstatsplot::ggbetweenstats(
data = mtcars,
x = cyl,
y = mpg,
messages = FALSE
)
# converting to plotly object
plotly::ggplotly(p)
```

## How can I use `grouped_`

functions with more than one group?

Currently, the `grouped_`

variants of functions only support repeating the
analysis across a *single* grouping variable. Often, you have to run the same
analysis across a combination of more than two grouping variables. This can be
easily achieved using `purrr`

package.

Here is an example-

```
# setup
set.seed(123)
library(tidyverse, warn.conflicts = FALSE)
library(ggstatsplot)
# creating a list by splitting dataframe by combination of two different
# grouping variables
df_list <- mpg %>%
dplyr::filter(drv %in% c("4", "f"), fl %in% c("p", "r")) %>%
split(x = ., f = list(.$drv, .$fl), drop = TRUE)
# checking if the length of the list is 4
length(df_list)
# running correlation analyses between
# this will return a *list* of plots
plot_list <- purrr::pmap(
.l = list(
data = df_list,
x = "displ",
y = "hwy",
results.subtitle = FALSE,
marginal.type = "densigram",
messages = FALSE
),
.f = ggstatsplot::ggscatterstats
)
# arragen the list in a single plot
ggstatsplot::combine_plots(
plotlist = plot_list,
nrow = 2,
labels = c("(i)", "(ii)", "(iii)", "(iv)")
)
```

# Suggestions

If you find any bugs or have any suggestions/remarks, please file an issue on GitHub: https://github.com/IndrajeetPatil/ggstatsplot/issues

# Session Information

For details, see- https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/session_info.html