--- title: "Kahoot Report" author: "Scary Scarecrow" date: "5/4/2022" output: html_document: theme: lumen highlight: tango self_contained: true toc: true toc_depth: 4 toc_float: true css: style.css --- ```{r setup, include=FALSE} knitr::opts_chunk$set( echo = FALSE, message = FALSE, warning = FALSE ) culture<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answer"), Votes=c(0,7,0,0,1)) training<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answer"), Votes=c(0,3,3,2,0)) mentor<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answer"), Votes=c(0,4,1,2,1)) documentation<-data.frame(Answer=c("Fully","Somewhat","Not Much","Not Clue","No Answer"), Votes=c(0,3,3,1,0)) controls<-data.frame(Answer=c("Legislation","Business","Rules","Risk","No Answer"), Votes=c(5,6,3,5,0)) simulations<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answer"), Votes=c(0,1,1,3,2)) automation<-data.frame(Answer=c("Yes","No"), Votes=c(7,0)) tech_use<-c("AI","AI","excel","BI","Lucy","Recipe predict","Tableau","Cloud") tech_challenges<-c("Time","Time","Time","Resistance","Time","People","Knowledge", "People","People", "Excel", "Speed", "Data Availability", "Self Exp","Frequency") strunstr<-data.frame(Answer=c("Definitely","Somewhat","Nope","No Clue","No Answer"), Votes=c(3,2,2,0,0)) quality<-data.frame(Answer=c("Definitely","Somewhat","Nope","No Clue","No Answer"), Votes=c(0,2,4,1,0)) sources<-data.frame(Answer=c("Definitely","Somewhat","Nope","No Clue","No Answer"), Votes=c(2,4,1,0,0)) library(dplyr) library(wordcloud) library(highcharter) library(tidyr) library(d3wordcloud) ``` ## Technology ### Tech Use ```{r} tech_use<-as.data.frame(table(tech_use)) d3wordcloud(tech_use$tech_use, tech_use$Freq, colors = c("#000000", "#0000FF", "#FF0000"), rangesizefont = c(30, 50),color.scale="sqrt",rotate.min=0, rotate.max=0,spiral="rectangular") ``` ### Challenges in Tech Adoption ```{r} tech_challenges<-as.data.frame(table(tech_challenges)) d3wordcloud(tech_challenges$tech_challenges, tech_challenges$Freq, colors = c("#000000", "#0000FF", "#FF0000"), rangesizefont = c(20, 50),color.scale="sqrt",rotate.min=0, rotate.max=0,spiral="rectangular") ``` ## People ```{r} culture |> rename(Culture=Votes) |> bind_cols(training) |> select(1,2,4) |> rename(Answer=Answer...1, Training=Votes) |> bind_cols(mentor) |> select(-4) |> rename(Answer=Answer...1, Mentor=Votes) |> pivot_longer(!Answer,names_to = "Type",values_to = "values") |> #pivot_wider(names_from = Answer, values_from = values) mutate(point=case_when( Answer=="Definitely" ~ 4, Answer=="Somewhat" ~ 3, Answer=="No Way" ~ 2, Answer=="Not Sure" ~ 1, Answer=="No Answer" ~ 0, )) |> mutate(score=values*point) |> group_by(Type) |> summarise(score=sum(score)/sum(values)) |> mutate(Max=4) |> mutate(score=round(score*100/Max,2)) |> ungroup() |> arrange(score) |> hchart("column", hcaes(x=Type, y=score), name="People", tooltip = list(pointFormat = "Avg. Score {point.Type}: {point.score}%"), dataLabels = list(enabled = TRUE, format= "{point.score}%")) |> hc_yAxis(title = list(text = "Average Score (%)"), labels = list(format = "{value}%"), max = 100) |> hc_title(text = "Mentorship and Training needs a boost") |> hc_subtitle(text = "Average score from culture promotion and training and mentorship opportunities") |> hc_credits(enabled = TRUE, text = "LaNubia Data Science", href = "https://www.lanubia.com/") |> hc_tooltip() |> hc_add_theme(hc_theme_economist()) |> hc_exporting(enabled = TRUE, # always enabled filename = "People") ``` ## Data ```{r} strunstr |> rename(Data.Type=Votes) |> bind_cols(quality) |> select(1,2,4) |> rename(Answer=Answer...1, Quality=Votes) |> bind_cols(sources) |> select(-4) |> rename(Answer=Answer...1, Sources=Votes) |> pivot_longer(!Answer,names_to = "Type",values_to = "values") |> #pivot_wider(names_from = Answer, values_from = values) mutate(point=case_when( Answer=="Definitely" ~ 4, Answer=="Somewhat" ~ 3, Answer=="Nope" ~ 2, Answer=="No Clue" ~ 1, Answer=="No Answer" ~ 0, )) |> mutate(score=values*point) |> group_by(Type) |> summarise(score=sum(score)/sum(values)) |> mutate(Max=4) |> mutate(score=round(score*100/Max,2)) |> ungroup() |> arrange(score) |> hchart("column", hcaes(x=Type, y=score), name="Data", tooltip = list(pointFormat = "Avg. Score {point.Type}: {point.score}%"), dataLabels = list(enabled = TRUE, format= "{point.score}%")) |> hc_yAxis(title = list(text = "Average Score (%)"), labels = list(format = "{value}%"), max = 100) |> hc_title(text = "Data quality is a major issue") |> hc_subtitle(text = "Average score from types of data used, its quality and sources") |> hc_credits(enabled = TRUE, text = "LaNubia Data Science", href = "https://www.lanubia.com/") |> hc_tooltip() |> hc_add_theme(hc_theme_economist()) |> hc_exporting(enabled = TRUE, # always enabled filename = "Data") ``` ## Process ```{r} documentation |> rename(Documentation=Votes) |> bind_cols(simulations) |> select(-3) |> rename(Answer=Answer...1, Simulations=Votes) |> pivot_longer(!Answer,names_to = "Type",values_to = "values") |> #pivot_wider(names_from = Answer, values_from = values) mutate(point=case_when( Answer=="Fully" ~ 4, Answer=="Somewhat" ~ 3, Answer=="Not Much" ~ 2, Answer=="Not Clue" ~ 1, Answer=="No Answer" ~ 0, )) |> mutate(score=values*point) |> group_by(Type) |> summarise(score=sum(score)/sum(values)) |> mutate(Max=4) |> mutate(score=round(score*100/Max,2)) |> ungroup() |> arrange(score) |> hchart("column", hcaes(x=Type, y=score), name="Process", tooltip = list(pointFormat = "Avg. Score {point.Type}: {point.score}%"), dataLabels = list(enabled = TRUE, format= "{point.score}%")) |> hc_yAxis(title = list(text = "Average Score (%)"), labels = list(format = "{value}%"), max = 100) |> hc_title(text = "Opportunity exists in Process Simulation and Documentation") |> hc_subtitle(text = "Average score from process documentation and simulations") |> hc_credits(enabled = TRUE, text = "LaNubia Data Science", href = "https://www.lanubia.com/") |> hc_tooltip() |> hc_add_theme(hc_theme_economist()) |> hc_exporting(enabled = TRUE, # always enabled filename = "Process") ``` ### Automation Opportunity ```{r} automation |> arrange(Votes) |> hchart("column", hcaes(x=Answer, y=Votes), name="ProcessAutomation", tooltip = list(pointFormat = "Votes {point.Answer}: {point.Votes}"), dataLabels = list(enabled = TRUE, format= "{point.Votes}")) |> hc_yAxis(title = list(text = "Count"), labels = list(format = "{value}")) |> hc_title(text = "Substantial Automation Opportunities Exist") |> hc_subtitle(text = "Count of votes (Whether or not process automation opportunities exist)") |> hc_credits(enabled = TRUE, text = "LaNubia Data Science", href = "https://www.lanubia.com/") |> hc_tooltip() |> hc_add_theme(hc_theme_economist()) |> hc_exporting(enabled = TRUE, # always enabled filename = "ProcessAuto") ``` ### Process Controls ```{r} controls |> arrange(Votes) |> hchart("column", hcaes(x=Answer, y=Votes), name="ProcessControl", tooltip = list(pointFormat = "Votes {point.Answer}: {point.Votes}"), dataLabels = list(enabled = TRUE, format= "{point.Votes}")) |> hc_yAxis(title = list(text = "Count"), labels = list(format = "{value}")) |> hc_title(text = "Process rules need boost") |> hc_subtitle(text = "Count of votes (Which controls exist)") |> hc_credits(enabled = TRUE, text = "LaNubia Data Science", href = "https://www.lanubia.com/") |> hc_tooltip() |> hc_add_theme(hc_theme_economist()) |> hc_exporting(enabled = TRUE, # always enabled filename = "ProcessControl") ```