descriptive_numbers.qmd

# Offerings {#sec-offerings}

```{r setup, include=FALSE}
# FUNCTIONS AND LIBRARIES
# have to load all data over again each document https://forum.posit.co/t/quarto-cant-find-r-objects/156848
knitr::opts_chunk$set(echo = FALSE)
library(ggplot2)    #for plots
library(tidyverse)  #for data munging including dates
library(viridis)    #color scheme


attendance_named <- read.csv("raw_data/processed_attendance_named.csv")

```

## Workshop topics offered

The number of distinct topics has declined since 2022, likely due to loss of digital scholarship specialist expertise.
```{r workshop_descriptive_stats_topics_unique, echo=FALSE, message = FALSE, warning = FALSE}
topics_desc <- attendance_named %>%
  group_by(year,
           Semester,
           Is.Course,
           Requested.
      ) %>%
  summarize(topics_count = n_distinct(WorkshopCode))


ggplot(data = topics_desc,
       mapping = aes(x = year,
                     y = topics_count))+
  geom_bar(stat = "identity")+
  labs(x = "Calendar year",
       y = "Number of unique topics offered")

```


While we offer many scheduled workshops each semester (upper left panel, "Not requested/Regularly scheduled"), we continue to increase our course-based "workshops on request" visits (lower right panel) as well as a low but steady number of out-of-class requested workshops (upper right panel).

```{r joined_post, echo=FALSE, message = FALSE, warning = FALSE}

to_string <- as_labeller(c(`No` = "Regularly Scheduled", `Yes` = "Requested",
                           `Unknown` = "Request vs schedule unknown"))

ggplot(data = attendance_named,
       mapping = aes(x = year,
                     fill = Is.Course))+
  geom_bar()+
  facet_wrap(. ~ Requested.,
             labeller = to_string)+
  labs(x = "Calendar year",
       y = "Number of workshops conducted",
       fill = "Within a course")
```



We have increased the number of topics we've brought "on request" to groups and courses.

```{r workshop_descriptive_stats_topics, echo=FALSE, message = FALSE, warning = FALSE}

topics_desc <- attendance_named %>%
  group_by(year,
           Is.Course,
           Requested.
      ) %>%
  summarize(topics_count = n_distinct(WorkshopCode))


ggplot(data = topics_desc,
       mapping = aes(x = year,
                     y = topics_count,
                     fill = Is.Course))+
  geom_bar(stat = "identity")+
  facet_grid(~Requested., labeller = to_string)+
  labs(x = "Calendar year",
       y = "Number of unique topics offered",
       fill = "Within a course")



```

## Workshop staffing needs

```{r workshop_descriptive_stats_staff, echo=FALSE, message = FALSE, warning = FALSE}

ggplot(data = attendance_named,
       mapping = aes(x = Total.Attendees,
                     y = Number.of.Helpers))+
  geom_point()+
  labs(x = "Total attendees at each workshop",
       y = "Number of helpers per workshop")


## how many helpers analysis for common workshops
topics_common <- attendance_named %>%
  group_by(WorkshopCode) %>%
  summarize(times_offered = n()) %>%
  dplyr::filter(times_offered > 10,
                !is.na(WorkshopCode))
  
ggplot(data = attendance_named[attendance_named$WorkshopCode %in% topics_common$WorkshopCode,],
       mapping = aes(x = Number.of.Helpers,
                     y = Format))+
  geom_boxplot()+
  facet_wrap(.~WorkshopCode)+
  labs(x = "Workshop topic (offered >10 times)",
       y = "Number of helpers per workshop")


```