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---
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")
```