Summer 2022 All Workshops Survey Responses

Number of responses

Code

library(tidyverse)
library(bslib)
library(shiny)
library(bsicons)
source("scripts/helper_functions.R")

# list of workshop IDs to filter results
workshops <- c("2022-08-16-ucsb-machlearn-r", "2022-08-09-ucsb-r-geospatial", "2022-07-26-ucsb-R", "2022-07-19-ucsb-git", "2022-07-12-ucsb-bash")

results <- read_csv("data-joined/all_workshops.csv") %>% 
  filter(workshop %in% workshops)
  
# Fix comma separator
results <- results %>% 
  mutate(findout_select.pre = str_replace_all(
  findout_select.pre, 
  "Twitter, Facebook, etc.", 
  "Twitter; Facebook; etc."))

pre_survey <- results %>%
  select(ends_with(".pre"))

post_survey <- results %>%
  select(ends_with(".post"))

n_pre <- sum(apply(post_survey, 1, function(row) all(is.na(row))))
n_post <- sum(apply(pre_survey, 1, function(row) all(is.na(row))))
n_total <- nrow(results)
n_both <- nrow(results) - n_pre - n_post

layout_columns(
  value_box(
    title = "Total responses", value = n_total, ,
    theme = NULL, showcase = bs_icon("people-fill"), showcase_layout = "left center",
    full_screen = FALSE, fill = TRUE, height = NULL
  ),
  value_box(
    title = "Both pre- and post-", value = n_both, , theme = NULL,
    showcase = bs_icon("arrows-expand-vertical"), showcase_layout = "left center",
    full_screen = FALSE, fill = TRUE, height = NULL
  ),
  value_box(
    title = "Only pre-workshop", value = n_pre, ,
    theme = NULL, showcase = bs_icon("arrow-left-short"), showcase_layout = "left center",
    full_screen = FALSE, fill = TRUE, height = NULL
  ),
  value_box(
    title = "Only post-workshop", value = n_post, , theme = NULL,
    showcase = bs_icon("arrow-right-short"), showcase_layout = "left center",
    full_screen = FALSE, fill = TRUE, height = NULL
  )
)

Total responses

94

Both pre- and post-

22

Only pre-workshop

64

Only post-workshop

8

Departments

Code

depts <- results %>% select(dept_select.pre) %>% 
  separate_rows(dept_select.pre, sep=",") %>%
  mutate(dept_select.pre = str_trim(dept_select.pre)) %>%
  count(dept_select.pre, name = "count") %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(depts, aes(y=reorder(dept_select.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) +  
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(depts$count)*1.1))

“Other” Departments

Code

other_depts <- results %>% 
  count(dept_other.pre, name = "count") %>% 
  drop_na() %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(other_depts, aes(y=reorder(dept_other.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) + 
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(other_depts$count)*1.1))

Current occupation / Career stage

Code

ocup <- results %>% select(occupation.pre) %>% 
  separate_rows(occupation.pre, sep=",") %>%
  mutate(occupation.pre = str_trim(occupation.pre)) %>%
  count(occupation.pre, name = "count") %>% 
  drop_na() %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(ocup, aes(y=reorder(occupation.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) + 
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(ocup$count)*1.2))

Motivation - Why are you participating in this workshop?

Code

motiv <- results %>% select(motivation_select.pre) %>% 
  separate_rows(motivation_select.pre, sep=",")  %>% 
  mutate(motivation_select.pre = str_trim(motivation_select.pre)) %>%
  count(motivation_select.pre, name = "count") %>% 
  drop_na() %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(motiv, aes(y=reorder(motivation_select.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) + 
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(motiv$count)*1.2))

How did you find out about this workshop?

Code

findw <- results %>% select(findout_select.pre) %>% 
  separate_rows(findout_select.pre, sep=",")  %>% 
  mutate(findout_select.pre = str_trim(findout_select.pre)) %>%
  count(findout_select.pre, name = "count") %>% 
  drop_na() %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(findw, aes(y=reorder(findout_select.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) + 
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(findw$count)*1.2))

What you most hope to learn?

Code

results %>% group_by(workshop) %>% 
  select(workshop, hopes.pre) %>% 
  drop_na()

workshop	hopes.pre
2022-07-12-ucsb-bash	To learn how to use Python/R to manage data
2022-07-12-ucsb-bash	Foundation and basic knowledge of Shell and Bash
2022-07-12-ucsb-bash	shell code for folder organization
2022-07-12-ucsb-bash	Basics of R that I can use for statistical data analysis projects
2022-07-12-ucsb-bash	A new skill to automate workflow
2022-07-12-ucsb-bash	I hope to learn new skills that will serve me well in the workplace and in school
2022-07-12-ucsb-bash	new skills
2022-07-12-ucsb-bash	Basic shell commands
2022-07-12-ucsb-bash	continued programming practice and exposure
2022-07-12-ucsb-bash	I suck at bash! I want to get better.
2022-07-12-ucsb-bash	I want to diversify my use of R in my research and even utilize it in my literature database and other database management. I would also like to improve my use of for loops in data manipulation and accessing. Additionally, I would like to be comfortable and versatile with the use of the terminal in programming.
2022-07-12-ucsb-bash	A more thorough understanding of the bash/shell interface and a more formal training in using the command line interface
2022-07-12-ucsb-bash	Handling Shell scripting
2022-07-12-ucsb-bash	Frequently used commands and also frequently used options
2022-07-12-ucsb-bash	Im hoping to become more familiar with shell scripting and command line so that I can work more efficiently on my research.
2022-07-12-ucsb-bash	Basic but essential knowledge and skills for beginners
2022-07-12-ucsb-bash	To get comfortable with using and navigating in the command line to improve the reproducibility of my workflow. More comfortable to use command line tools so I can start learning about remote & scalable computing.
2022-07-12-ucsb-bash	data analysis
2022-07-12-ucsb-bash	Gain crucial skills for industry careers
2022-07-19-ucsb-git	Version control best practices and strategies
2022-07-19-ucsb-git	Skills necessary for a position as a data analyst or data scientist.
2022-07-19-ucsb-git	good practices
2022-07-19-ucsb-git	how to use git
2022-07-19-ucsb-git	How to collaborate with others in git
2022-07-19-ucsb-git	better and more diverse use of github and version control
2022-07-19-ucsb-git	Learn how to use git to start my own project;
2022-07-19-ucsb-git	have an overall idea of Git, know some common uses of Git, and know how to search answers online when i get stuck in the future
2022-07-26-ucsb-R	’-learn new skills to apply to schoolwork or jobs or internships; -gain experience and knowledge
2022-07-26-ucsb-R	How to efficiently analyze data
2022-07-26-ucsb-R	how to use R for future research data analysis
2022-07-26-ucsb-R	I hope to grasp a better understanding of coding with R and how I can apply it in my career or research (be more comopetitive).
2022-07-26-ucsb-R	The basics of R and how to use it for research
2022-07-26-ucsb-R	New skills for data analysis in R
2022-07-26-ucsb-R	Technical skills and problem solving
2022-07-26-ucsb-R	I want to gain new skills for a potential career in data analysis or data science
2022-07-26-ucsb-R	I hope to learn how to use R more efficiently so that I can organize and analyze my research data better/quicker.
2022-07-26-ucsb-R	Be more comfortable using R.
2022-07-26-ucsb-R	I am hoping to learn background on how to use r studio so that I can analyze my own data
2022-07-26-ucsb-R	Leanr the basics
2022-07-26-ucsb-R	I hope to improve my data management and analysis skillset by learning beginner code in R. I already know and use Stata but would love to learn another data manipulation tool for my research and career.
2022-07-26-ucsb-R	Gain some skills with R and data analysis that I can apply to a job in the future hopefully in some field of biology. If not maybe this workshop will inspire me to look in other directions.
2022-07-26-ucsb-R	I’d like to learn if investing time into learning R is better than continuing to use MS Access, excel, jmp, and other programs for data management and analysis
2022-07-26-ucsb-R	Anything
2022-08-09-ucsb-r-geospatial	I have a good amount of programming experience in R, but it has mostly been for data cleaning/manipulation, and not with geospatial data. I am planning to incorporate geospatial analyses into my research, so I wanted to start learning how to work with these data now.
2022-08-09-ucsb-r-geospatial	The basics of geospatial data in R and being able to apply what I learned in future career/graduate studies
2022-08-09-ucsb-r-geospatial	variety of R functions for research;
2022-08-16-ucsb-machlearn-r	R in Machine Learning
2022-08-16-ucsb-machlearn-r	I want to learn more about machine learning in particular.
2022-08-16-ucsb-machlearn-r	An understanding of random forests that I can apply to my data
2022-08-16-ucsb-machlearn-r	More detail of Machine Learning and how to apply it to the projects I am working on now/in the future
2022-08-16-ucsb-machlearn-r	Enhance skills;
2022-08-16-ucsb-machlearn-r	Ways to automate my work and skills I can pass on to people I consult with.
2022-08-16-ucsb-machlearn-r	A better understanding of ML techniques. I had one course during my grad program on ML but I struggled to retain the material.

Learning environment in the workshop

Code

orderedq <- c("Strongly Disagree", "Somewhat Disagree", "Neither Agree or Disagree","Somewhat Agree", "Strongly Agree")
addNA(orderedq)

Code

agree_questions <- results %>% 
  select(join_key, agree_apply.post,    agree_comfortable.post, agree_clearanswers.post,
         agree_instr_enthusiasm.post, agree_instr_interaction.post, agree_instr_knowledge.post
) %>% 
  filter(!if_all(-join_key, is.na))

n_agree_questions <- nrow(agree_questions)
  
agree_questions <- agree_questions %>%
  pivot_longer(cols = -join_key, names_to = "Question", values_to = "Response") %>% 
  mutate(Response = factor(Response, levels = orderedq),
         Question = recode(Question,
                     "agree_apply.post" = "Can immediatly apply 
 what they learned",
                     "agree_comfortable.post" = "Comfortable learning in 
 the workshop environment",
                     "agree_clearanswers.post" = "Got clear answers 
 from instructors",
                     "agree_instr_enthusiasm.post" = "Instructors were enthusiastic",
                     "agree_instr_interaction.post" = "Comfortable interacting 
 with instructors",
                     "agree_instr_knowledge.post" = "Instructors were knowledgeable 
 about the material"
      ))

summary_data <- agree_questions %>%
  count(Question, Response, name = "count") %>% 
  mutate(percent = (count / n_agree_questions) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(summary_data, aes(x = Question, y = count, fill = Response)) +
  geom_col(position = "fill", color = "black", show.legend = TRUE) +
  scale_y_continuous(labels = scales::percent_format()) + 
  scale_fill_manual(values = c("Strongly Disagree" = "#d01c8b", 
                               "Somewhat Disagree" = "#f1b6da", 
                               "Neither Agree or Disagree" = "#f7f7f7", 
                               "Somewhat Agree" = "#b8e186", 
                               "Strongly Agree" = "#4dac26"), 
                    na.translate = TRUE, na.value = "#cccccc", 
                    breaks = orderedq, drop = FALSE) +
  geom_text(aes(label = text), size = 3,
             position = position_fill(vjust = 0.5)) +
  labs(y = "# respondents (Percentage)", x = element_blank(), fill = "Responses",
       subtitle = paste0("Number of responses: ", n_agree_questions)) +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1),
        plot.subtitle = element_text(hjust = 0.5, size = 12))

How an instructor or helper affected your learning experience

Code

results %>% 
  group_by(workshop) %>% 
  select(workshop, instructor_example.post) %>%
  drop_na()

workshop	instructor_example.post
2022-07-12-ucsb-bash	Helpers are always able to resolve our difficulties very quickly. Thats quite important cuz we were moving very fast, and instructors wouldn’t stop the whole lecture for an individual. Luckily I didn’t fall behind every time I ask for personal help.
2022-07-12-ucsb-bash	the instructors coming over when we held up a red sticky to help us individually
2022-07-12-ucsb-bash	Nice clear explanations of the basic commands
2022-07-12-ucsb-bash	I think the workshop did a good job in the online accommodation (probably the best experience I have)! It provides a lot of benefit to the people who cannot attend in person (I am having a baby due next week!)
2022-07-12-ucsb-bash	The instructors went through step by step how to solve some of the more difficult challenges, which I found pretty helpful.
2022-07-12-ucsb-bash	following live code example is helpful.
2022-07-12-ucsb-bash	great answers
2022-07-12-ucsb-bash	Pulled into a breakout room to solve a problem. We worked through chat which was a bit difficult verses audio
2022-07-19-ucsb-git	Hands on examples
2022-07-26-ucsb-R	Chris was particularly helpful in answering my nuanced questions and kindly provided additional resources upon request.
2022-07-26-ucsb-R	I attended the workshop via zoom and the instructors and helpers online made sure that we were able to access any of the material presented in the physical classroom.
2022-07-26-ucsb-R	How the workshop was led and managed was very organized and prepared. The instructors/helpers dealt with students’ questions immediately in various ways during the session (i.e., chat room, workshop room. I appreciate the prepared commends and codes bc I was able to revisit what I missed later and will do so later again. I greatly appreciate them all.
2022-07-26-ucsb-R	I had a question about a violin graph and one of the instructors gave an explanation how it was similar to a histogram and it made sense.
2022-07-26-ucsb-R	they answered my question thoroughly and with examples
2022-08-09-ucsb-r-geospatial	The lessons were slowly paced, which allowed us to get a good grasp on the materials taught, but this pace also prevented us from going into depth in several of the lessons.
2022-08-09-ucsb-r-geospatial	With the clearly structured layout of each episode, I had an idea of where I was although I’m still unfamiliar with the specific area (advanced R level). I greatly appreciate all. just I need to improve my knowledge by myself first.
2022-08-09-ucsb-r-geospatial	Open to questions, gave great explanations for answers, made sure everyone was caught up and not left behind
2022-08-09-ucsb-r-geospatial	All questions that I or others asked were answered completely.
2022-08-09-ucsb-r-geospatial	instructors and helpers were quick to troubleshoot my issues
2022-08-16-ucsb-machlearn-r	very friendly - felt comfortable asking questions

Skills and perception comparison

Code

# Calculate mean scores and make graph for all respondents (only_matched=FALSE)
tryCatch(
  {
mean_nresp <- get_mean_scores_nresp(results, only_matched=FALSE)
graph_pre_post(mean_nresp$mean_scores, mean_nresp$n_resp_pre, mean_nresp$n_resp_post, mean_nresp$n_resp_pre_post, only_matched=FALSE)
},
error = function(cond) {
message("Could not do the plots as there are no pre or post results to show")
}
)

Code

# Calculate mean scores and make graph for only matched respondents in pre and post (only_matched=TRUE)
tryCatch(
  {
mean_nresp <- get_mean_scores_nresp(results, only_matched=TRUE)
graph_pre_post(mean_nresp$mean_scores, mean_nresp$n_resp_pre, mean_nresp$n_resp_post, mean_nresp$n_resp_pre_post, only_matched=TRUE)
},
error = function(cond) {
message("Could not do the plots as there are no pre or post results to show")
}
)

Workshop Strengths

Code

results %>% 
  group_by(workshop) %>% 
  select(workshop, workshop_strengths.post) %>% 
  drop_na()

workshop	workshop_strengths.post
2022-07-12-ucsb-bash	.
2022-07-12-ucsb-bash	many instructors available to answer questions in the zoom chat and in person
2022-07-12-ucsb-bash	Easy to implement, good example data sets
2022-07-12-ucsb-bash	The content of the material covered
2022-07-12-ucsb-bash	The collaborative notebook was very helpful for keeping track of what was going on.
2022-07-12-ucsb-bash	Logic and clear.
2022-07-12-ucsb-bash	Basic Navigation through shell, and some common command line uses
2022-07-12-ucsb-bash	webpage is helpful.
2022-07-12-ucsb-bash	examples and exercises
2022-07-12-ucsb-bash	almost immediate responses from the staff
2022-07-19-ucsb-git	The curriculum notes and constant request for feedback from students.
2022-07-26-ucsb-R	It was super helpful to have so many different instructors/helpers, because I was able to find individuals with whom I felt comfortable asking for assistance from and who had different knowledge/expertise to share.
2022-07-26-ucsb-R	’- Workshop covered a wide range of topics; - Provided detailed answers to questions and instructors were honest when they were unsure of the answer; - Workshop material was very digestible and seems applicable to many fields
2022-07-26-ucsb-R	‘-provided the core and essential contents with an actual data. ; -dealt with the survey feedback and students’ questions ; -various teachers helped to share more information with students;
2022-07-26-ucsb-R	Having remote instruction as an option was perfect for me. I think everyone did a good job balancing between the remote and in-person attendees.
2022-07-26-ucsb-R	The pacing was just right
2022-07-26-ucsb-R	Having a day in between workshop days
2022-07-26-ucsb-R	I like that the copy of the code was supplied with lesson. Instructors were very helpful.
2022-07-26-ucsb-R	interactive, friendly learning place
2022-08-09-ucsb-r-geospatial	Accessibility, good introduction to the contents, pleasant and positive staff
2022-08-09-ucsb-r-geospatial	organized preparation and kind patience for slower learners or beginners
2022-08-09-ucsb-r-geospatial	Learned basics of geospatial data in R which I didn’t know anything about before; provided a basic understanding of all of this so if I need to use it in the future I can figure out what to google/apply it much easier than teaching myself
2022-08-09-ucsb-r-geospatial	Knowledgeable instructors, learning material provided afterward (step by step lessons), R script(s) provided afterward, able to attend and interact remotely.
2022-08-09-ucsb-r-geospatial	instructors/helpers with different areas/levels of expertise
2022-08-16-ucsb-machlearn-r	the challenges on the first day aligned well with what was taught

Ways to improve the workshop

Code

results %>% 
  group_by(workshop) %>% 
  select(workshop, workshop_improved.post) %>% 
  drop_na()

workshop	workshop_improved.post
2022-07-12-ucsb-bash	Ventilation? It’s kinda hot and stuffy inside the room.
2022-07-12-ucsb-bash	making sure that they are familiar with the lesson and exactly what they are going to show and that there aren’t any issues before they lead the lesson. When the instructors got confused or made mistakes and had to try to fix them, it made learning already confusing things even more confusing because I was lost on what was a mistake and what was correct. In general, I believe it went a little too fast for me
2022-07-12-ucsb-bash	Not jumping around directories quickly
2022-07-12-ucsb-bash	Better coordination between instructors if other instructors need to interrupt the instructor currently teaching to better explain a point or answer a question
2022-07-12-ucsb-bash	Clearer syllabus and more exercises
2022-07-12-ucsb-bash	Break time can come a little soon.
2022-07-12-ucsb-bash	grep gets a little complicated with escape characters, I think those could be added to the workshop
2022-07-12-ucsb-bash	none
2022-07-12-ucsb-bash	sharing instructors use for bash-shell and participants briefly sharing relevance to their own work (I mostly work in rstudio on datasets, or morphing datasets into better datasets, I rarely work with tons of files…)
2022-07-12-ucsb-bash	I found it particularly difficult to follow along in this hybrid course. Perhaps the workbook and course flow should be reorganized. Or having a cheatsheet available of commands we have learned so far so participants don’t have to scroll through the workbook endlessly when trying to solve a challenge. I think a fully online course would work much better (since I can’t attend in person, but grateful to have access to these courses working remotely, so I’ll take whatever you can swing!). One of the instructors shell was color coded, which was sooo much easier to follow along even though its not what my own shell looks like. Maybe multiple shell windows up at the same time so when working in nano the previous commands are still available for those who are a step or two behind. I think it would be great to emphasize somewhere in the course why command line is still important when working on modern computers. Looking forward to the next course, thanks!
2022-07-19-ucsb-git	Great workshop but it might help if the instructors do not go too fast sometimes since we need to execute commands. Thank you!
2022-07-26-ucsb-R	It would be super helpful if there was an additional day allotted to this workshop as we were unable to cover everything as planned.
2022-07-26-ucsb-R	’- There were a few uncertainties in the material taught on the 2nd day; - Some parts of the workshop were a bit fast paced; - There were a few technical difficulties on zoom in the beginning (but they were resolved in the end);
2022-07-26-ucsb-R	Everything was good. thank you.
2022-07-26-ucsb-R	Perhaps providing the scripts ahead or time or afterward so that we can re-do the lessons at our leisure after the workshop.
2022-07-26-ucsb-R	would have liked to learn how to import data (e.g., from csv files, etc) to work with.
2022-07-26-ucsb-R	I think some of the instructors that are not teaching at the moment should be monitoring the room a bit more. I was stuck and put up my pink sticky note, but didn’t get help until the break.
2022-07-26-ucsb-R	n/a;
2022-08-09-ucsb-r-geospatial	Not all instructors had a strong grasp on R, which caused some slow-downs and also caused some confusing presentation of the material. ; ; It would also be useful if the instructors presented clear and self-constrained scripts in these lessons (i.e. how one would actually organize scripts in their own work). This was done inconsistently across trainers, and there were some errors in how the scripts were managed. For example, it would be useful to tell the learners that it is important to clear your environment between scripts and to make sure that objects referenced only in previous scripts are not used in your current script.
2022-08-09-ucsb-r-geospatial	N/A
2022-08-09-ucsb-r-geospatial	better timing - although instructor commented that they rarely get through the whole thing; or plan more realistic timing goals
2022-08-09-ucsb-r-geospatial	As someone fairly new to R, perhaps a longer class (more days) to go through the lessons slower, step by step. I can do this on my own now, but it would have been nice to have more time to learn the steps. Sometimes I would have an error in my typing that took me awhile to catch and fix and by then the workshop had moved on. I was usually able to catch up or fix it later by redoing the lesson in my own timeframe.
2022-08-09-ucsb-r-geospatial	including a quick tutorial video on the set-up page for how to get the data up n running before may help alleviate some of the issues that required troubleshooting at the beginning of the workshop
2022-08-16-ucsb-machlearn-r	it’s always a struggle, especially in piloted workshops, to have a good balance between getting through the planned material and allowing enough time in the workshops to provide necessary background/context info and answer questions. The first day was paced a bit fast, but we made it through the material; the second day accommodated more time for explanations, but we did not make it through the material.

How likely are you to recommend this workshop? Scale 0 - 10

Code

orderedq <- c("Detractor", "Passive", "Promoter")

nps <- results %>% 
  count(recommend_group.post, recommende_score.post, name = "count") %>% 
  drop_na() %>% 
  mutate(recommend_group.post = factor(recommend_group.post, levels = orderedq),
         percent = (count/sum(count)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

nps %>% 
ggplot(aes(x=recommende_score.post, y=count, fill=recommend_group.post)) +
  geom_col(color="black", show.legend = TRUE) +
  scale_fill_manual(values = c("Detractor" = "#af8dc3", "Passive" = "#f7f7f7", "Promoter" = "#7fbf7b"), breaks = c("Detractor", "Passive", "Promoter"), drop = FALSE) +
  geom_label(aes(label = text, vjust = -0.5), fill = "white", size= 3) +
  scale_x_continuous(breaks = 1:10) +
  labs(x = "NPS Score", y = "# respondents", subtitle = paste0("Number of responses: ", sum(nps$count), "
 Mean score: ", format(weighted.mean(nps$recommende_score.post, nps$count), digits = 3))) +
  theme_minimal() +
  theme(
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_blank(),
    plot.subtitle = element_text(hjust = 0.5, size = 12)
  ) +
  expand_limits(x = c(1,10),
                y = c(0, max(nps$count)*1.1))

Topic Suggestions

Code

results %>% 
  group_by(workshop) %>% 
  select(workshop, suggest_topics.post) %>% 
  drop_na()

workshop	suggest_topics.post
2022-07-12-ucsb-bash	.
2022-07-12-ucsb-bash	C++
2022-07-12-ucsb-bash	chatter from instructors helping other in-person participants during the workshop can sound quite loud to online participants, affecting concentration of online participants on the instructor teaching
2022-07-12-ucsb-bash	Possibly some more advanced topics on constructing shell scripts that allow for user input. I am also hoping to see a QGIS workshop in the future.
2022-07-12-ucsb-bash	python basics
2022-07-12-ucsb-bash	continuation of bash things
2022-07-12-ucsb-bash	using the command line to write scripts that run & incorporate multiple scripts and languages (python, R, SQL). Intro to Cloud computing?
2022-07-19-ucsb-git	Bash shell integration in Jupyter Notebook
2022-07-26-ucsb-R	More R workshops please and thank you! :D
2022-07-26-ucsb-R	Data cleaning and how to process raw data into a form where we could apply the analysis and visualization techniques from this workshop to
2022-07-26-ucsb-R	Perhaps additional workshops for practicing with R, especially using examples from environmental science. Working through more examples would help strengthen the techniques I learned.
2022-07-26-ucsb-R	Multivariate analysis in R!!! (e.g., regression, two-way tables with t-tests/chi2, etc); Importing data (from csv, etc) and cleaning it. For example, if we conduct a survey and the responses are all in a file and we want to analyze them in R
2022-07-26-ucsb-R	Data Cleaning and Analysis in R or Python
2022-08-09-ucsb-r-geospatial	I think a more advanced offering that practices doing a longer problem set or something more applied.
2022-08-09-ucsb-r-geospatial	A whole ggplot lesson! The syntax gets kind of confusing and would be great to learn how to manipulate/display categorical and continuous data better since it is so widely used
2022-08-09-ucsb-r-geospatial	More classes aimed for beginners or people who haven’t used R in a long time. Just going through more examples of how to summarize and visualize data, but at a slower pace.
2022-08-09-ucsb-r-geospatial	analyzing stats
2022-08-16-ucsb-machlearn-r	R to analyze stats