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109 lines
3.7 KiB
109 lines
3.7 KiB
4 years ago
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---
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title: "Kahoot Report"
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author: "Scary Scarecrow"
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date: "5/4/2022"
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output: html_document
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---
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```{r setup, include=FALSE}
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knitr::opts_chunk$set(echo = TRUE)
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culture<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answer"),
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Votes=c(0,7,0,0,1))
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training<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answer"),
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Votes=c(0,3,3,2,0))
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mentor<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answer"),
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Votes=c(0,4,1,2,1))
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documentation<-data.frame(Answer=c("Fully","Somewhat","Not Much","Not Clue","No Answer"),
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Votes=c(0,3,3,1,0))
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controls<-data.frame(Answer=c("Legislation","Business","Process","Risk","No Answer"),
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Votes=c(5,6,3,5,0))
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simulations<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answer"),
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Votes=c(0,1,1,3,2))
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automation<-data.frame(Answer=c("Yes","No"),
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Votes=c(7,0))
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tech_use<-c("AI","AI","excel","BI","Lucy","Recipe predict","Tableau","Cloud")
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tech_challenges<-c("Time","Time","Time","Resistance","Time","People","Knowledge",
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"People","People", "Excel", "Speed", "Data Availability", "Self Exp","Frequency")
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strunstr<-data.frame(Answer=c("Definitely","Somewhat","Nope","No Clue","No Answer"),
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Votes=c(3,2,2,0,0))
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quality<-data.frame(Answer=c("Definitely","Somewhat","Nope","No Clue","No Answer"),
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Votes=c(0,2,4,1,0))
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sources<-data.frame(Answer=c("Definitely","Somewhat","Nope","No Clue","No Answer"),
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Votes=c(2,4,1,0,0))
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library(dplyr)
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library(wordcloud)
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library(highcharter)
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library(tidyr)
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```
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## Technology
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```{r}
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tech_use<-as.data.frame(table(tech_use))
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wordcloud(tech_use$tech_use, tech_use$Freq, min.freq = 1, random.color = T, colors = c("red","green","purple","blue","cyan","magenta","grey2"), scale = c(2,0.5), rot.per = 0, fixed.asp = F)
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```
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```{r}
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tech_challenges<-as.data.frame(table(tech_challenges))
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wordcloud(tech_challenges$tech_challenges, tech_challenges$Freq, min.freq = 1, random.color = T, colors = c("red","green","purple","blue","cyan","magenta","grey2"), scale = c(2,0.5), rot.per = 0, fixed.asp = F)
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```
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## People
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```{r}
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culture
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training
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mentor
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culture |>
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rename(Culture=Votes) |>
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bind_cols(training) |>
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select(1,2,4) |>
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rename(Answer=Answer...1, Training=Votes) |>
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bind_cols(mentor) |>
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select(-4) |>
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rename(Answer=Answer...1, Mentor=Votes) |>
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pivot_longer(!Answer,names_to = "Type",values_to = "values") |>
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#pivot_wider(names_from = Answer, values_from = values)
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mutate(point=case_when(
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Answer=="Definitely" ~ 4,
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Answer=="Somewhat" ~ 3,
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Answer=="No Way" ~ 2,
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Answer=="Not Sure" ~ 1,
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Answer=="No Answer" ~ 0,
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)) |>
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mutate(score=values*point) |>
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group_by(Type) |>
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summarise(score=sum(score)/sum(values)) |>
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mutate(Max=4) |>
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mutate(score=round(score*100/Max,2)) |>
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ungroup() |>
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arrange(score) |>
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hchart("column", hcaes(x=Type, y=score), name="People",
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tooltip = list(pointFormat = "Avg. Score {point.Type}: {point.score}%"),
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dataLabels = list(enabled = TRUE, format= "{point.score}%")) |>
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hc_yAxis(title = list(text = "Average Score (%)"),
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labels = list(format = "{value}%"), max = 100) |>
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hc_title(text = "Score: People") |>
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hc_subtitle(text = "Average score from culture promotion and training and mentorship opportunities") |>
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hc_credits(enabled = TRUE,
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text = "LaNubia Data Science",
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href = "https://www.lanubia.com/") |>
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hc_tooltip() |>
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hc_add_theme(hc_theme_economist()) |>
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hc_exporting(enabled = TRUE, # always enabled
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filename = "People")
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```
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