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@ -2,12 +2,23 @@ |
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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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output: |
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html_document: |
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theme: lumen |
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highlight: tango |
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self_contained: true |
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toc: true |
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toc_depth: 4 |
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toc_float: true |
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css: style.css |
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--- |
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```{r setup, include=FALSE} |
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knitr::opts_chunk$set(echo = TRUE) |
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knitr::opts_chunk$set( |
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echo = FALSE, |
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message = FALSE, |
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warning = FALSE |
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) |
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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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@ -16,7 +27,7 @@ mentor<-data.frame(Answer=c("Definitely","Somewhat","No Way","Not Sure","No Answ |
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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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controls<-data.frame(Answer=c("Legislation","Business","Rules","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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@ -39,31 +50,34 @@ library(dplyr) |
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library(wordcloud) |
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library(highcharter) |
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library(tidyr) |
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library(d3wordcloud) |
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``` |
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## Technology |
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### Tech Use |
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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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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") |
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``` |
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### Challenges in Tech Adoption |
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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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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") |
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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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```{r} |
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culture |> |
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rename(Culture=Votes) |> |
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bind_cols(training) |> |
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@ -93,7 +107,7 @@ culture |> |
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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_title(text = "Mentorship and Training needs a boost") |> |
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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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@ -106,3 +120,149 @@ culture |> |
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## Data |
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```{r} |
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strunstr |> |
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rename(Data.Type=Votes) |> |
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bind_cols(quality) |> |
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select(1,2,4) |> |
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rename(Answer=Answer...1, Quality=Votes) |> |
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bind_cols(sources) |> |
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select(-4) |> |
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rename(Answer=Answer...1, Sources=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=="Nope" ~ 2, |
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Answer=="No Clue" ~ 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="Data", |
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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 = "Data quality is a major issue") |> |
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hc_subtitle(text = "Average score from types of data used, its quality and sources") |> |
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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 = "Data") |
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``` |
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## Process |
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```{r} |
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documentation |> |
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rename(Documentation=Votes) |> |
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bind_cols(simulations) |> |
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select(-3) |> |
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rename(Answer=Answer...1, Simulations=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=="Fully" ~ 4, |
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Answer=="Somewhat" ~ 3, |
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Answer=="Not Much" ~ 2, |
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Answer=="Not Clue" ~ 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="Process", |
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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 = "Opportunity exists in Process Simulation and Documentation") |> |
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hc_subtitle(text = "Average score from process documentation and simulations") |> |
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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 = "Process") |
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``` |
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### Automation Opportunity |
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```{r} |
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automation |> |
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arrange(Votes) |> |
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hchart("column", hcaes(x=Answer, y=Votes), name="ProcessAutomation", |
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tooltip = list(pointFormat = "Votes {point.Answer}: {point.Votes}"), |
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dataLabels = list(enabled = TRUE, format= "{point.Votes}")) |> |
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hc_yAxis(title = list(text = "Count"), |
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labels = list(format = "{value}")) |> |
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hc_title(text = "Substantial Automation Opportunities Exist") |> |
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hc_subtitle(text = "Count of votes (Whether or not process automation opportunities exist)") |> |
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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 = "ProcessAuto") |
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``` |
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### Process Controls |
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```{r} |
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controls |> |
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arrange(Votes) |> |
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hchart("column", hcaes(x=Answer, y=Votes), name="ProcessControl", |
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tooltip = list(pointFormat = "Votes {point.Answer}: {point.Votes}"), |
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dataLabels = list(enabled = TRUE, format= "{point.Votes}")) |> |
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hc_yAxis(title = list(text = "Count"), |
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labels = list(format = "{value}")) |> |
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hc_title(text = "Process rules need boost") |> |
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hc_subtitle(text = "Count of votes (Which controls exist)") |> |
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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 = "ProcessControl") |
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``` |
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