Team Performance Dashboard, February’21

Team Performance

Engineering & Analytics

Engineering & Analytics Team Major Activities

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Report Importance & Qualitative Marks

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Engineering And Analytics Team

Engineering

Engineering Team Major Activities

Report Importance & Qualitative Marks

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Engineering And Analytics Team

Analytics

Analytics Team Key Activities

Report Importance & Qualitative Marks

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Engineering And Analytics Team

Team Rankings

5 Subteams Ranking by Theodor

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Subteams & Members

Infrastructure	IT	Senior Data Scientist	Data Scientist	Data Analyst
Tucker	Benedict	Hunter	Margaret	Eric
Jamie	Jenson	Francis	Blake	Geoffrey
Marshman	Elliot		Roy	Alan
Ross	Nancy
Scarlette
Chris

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Subteam Wise Top Performers

Name	Subteam	Marks
Roy	Data Scientist	70.7
Nancy	IT	70.7
Geoffrey	Data Analyst	70.1
Francis	Senior Data Scientist	69.5
Chris	Infrastructure	68.5

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Engineering And Analytics Team

Individual Rankings

Engineering & Analytics Team Rankings

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Engineering Team Ranking

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Analytics Team Ranking

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Marks are on scale of 100 Points

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Engineering And Analytics Team

Individual performance

Engineering Individuals Performance

Tucker

Tucker

Key Activities

Report Importance & Qualitative Marks

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Mr. Tucker’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task7	Subtask41	76
Task6	Subtask28	75
Task4	Subtask26	74
Task9	Subtask31	74
Task10	Subtask32	72
Task8	Subtask30	71
Task3	Subtask37	71
Task6	Subtask40	70
Task8	Subtask42	70
Task2	Subtask24	68
Task1	Subtask35	68
Task4	Subtask38	67
Task1	Subtask23	66
Task12	Subtask22	65
Task3	Subtask25	65
Task12	Subtask34	63
Task11	Subtask33	62
Task7	Subtask29	60
Task5	Subtask27	58
Task2	Subtask36	56
Task5	Subtask39	49

Benedict

Benedict

Key Activities

Report Importance & Qualitative Marks

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Mr. Benedict’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task3	Subtask9	74
Task9	Subtask3	73
Task1	Subtask19	73
Task7	Subtask13	73
Task10	Subtask4	72
Task7	Subtask1	71
Task8	Subtask2	70
Task12	Subtask6	69
Task1	Subtask7	69
Task5	Subtask49	68
Task8	Subtask14	68
Task5	Subtask11	68
Task6	Subtask12	68
Task2	Subtask8	67
Task10	Subtask16	66
Task6	Subtask50	66
Task4	Subtask10	66
Task9	Subtask15	66
Task11	Subtask17	62
Task2	Subtask20	61
Task11	Subtask5	60
Task12	Subtask18	60

Jenson

Jenson

Key Activities

Report Importance & Qualitative Marks

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Mr. Jenson’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task3	Subtask41	71
Task9	Subtask35	69
Task7	Subtask45	68
Task12	Subtask38	68
Task8	Subtask34	67
Task1	Subtask39	67
Task9	Subtask47	66
Task7	Subtask33	66
Task10	Subtask36	66
Task4	Subtask42	66
Task10	Subtask48	66
Task2	Subtask40	64
Task8	Subtask46	64
Task6	Subtask44	64
Task11	Subtask37	64
Task5	Subtask43	63

Jamie

Jamie

Key Activities

Report Importance & Qualitative Marks

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Mr. Jamie’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task4	Subtask22	76
Task8	Subtask26	76
Task6	Subtask36	76
Task9	Subtask39	76
Task11	Subtask29	75
Task7	Subtask25	74
Task7	Subtask37	74
Task10	Subtask28	71
Task5	Subtask35	68
Task3	Subtask21	67
Task8	Subtask38	67
Task6	Subtask24	66
Task12	Subtask30	66
Task1	Subtask31	66
Task2	Subtask32	66
Task3	Subtask33	66
Task5	Subtask23	65
Task9	Subtask27	65
Task11	Subtask41	63
Task12	Subtask42	62
Task4	Subtask34	60
Task10	Subtask40	56

Chris

Chris

Key Activities

Report Importance & Qualitative Marks

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Mr. Chris’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task4	Subtask22	76
Task8	Subtask26	76
Task6	Subtask36	76
Task9	Subtask39	76
Task11	Subtask29	75
Task7	Subtask25	74
Task7	Subtask37	74
Task10	Subtask28	71
Task5	Subtask35	68
Task3	Subtask21	67
Task8	Subtask38	67
Task6	Subtask24	66
Task12	Subtask30	66
Task1	Subtask31	66
Task2	Subtask32	66
Task3	Subtask33	66
Task5	Subtask23	65
Task9	Subtask27	65
Task11	Subtask41	63
Task12	Subtask42	62
Task4	Subtask34	60
Task10	Subtask40	56

Elliot

Elliot

Key Activities

Report Importance & Qualitative Marks

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Mr. Elliot’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task4	Subtask18	70
Task6	Subtask20	70
Task9	Subtask23	70
Task10	Subtask24	70
Task8	Subtask22	70
Task7	Subtask21	69
Task1	Subtask27	69
Task3	Subtask29	69
Task5	Subtask19	68
Task11	Subtask25	68
Task2	Subtask28	67
Task4	Subtask30	66
Task5	Subtask31	66
Task12	Subtask26	65
Task6	Subtask32	64

Nancy

Nancy

Key Activities

Report Importance & Qualitative Marks

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Ms. Nancy’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task3	Subtask49	74
Task11	Subtask49	72
Task12	Subtask50	72
Task2	Subtask48	70
Task1	Subtask47	67

Ross

Ross

Key Activities

Report Importance & Qualitative Marks

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Mr. Ross’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task3	Subtask39	72
Task1	Subtask37	66
Task12	Subtask36	65
Task2	Subtask38	65
Task4	Subtask40	59
Task5	Subtask41	49

Scarlette

Scarlette

Key Activities

Report Importance & Qualitative Marks

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Ms. Scarlette’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task10	Subtask20	73
Task5	Subtask15	72
Task7	Subtask5	68
Task8	Subtask6	68
Task12	Subtask10	68
Task7	Subtask17	68
Task6	Subtask16	68
Task8	Subtask18	68
Task11	Subtask9	67
Task9	Subtask7	66
Task3	Subtask13	66
Task2	Subtask12	65
Task1	Subtask11	65
Task9	Subtask19	62
Task11	Subtask21	62
Task4	Subtask14	60
Task10	Subtask8	59

Marshman

Marshman

Key Activities

Report Importance & Qualitative Marks

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Mr. Marshman’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task9	Subtask9	72
Task1	Subtask1	68
Task8	Subtask8	68
Task5	Subtask5	65
Task2	Subtask2	65
Task6	Subtask6	65
Task3	Subtask3	63
Task11	Subtask11	63
Task12	Subtask12	62
Task7	Subtask7	60
Task4	Subtask4	56
Task10	Subtask10	56

Analytics Individuals Performance

Hunter

Hunter

Key Activities

Report Importance & Qualitative Marks

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Mr. Hunter’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task2	Subtask10	73
Task11	Subtask19	72
Task2	Subtask22	72
Task3	Subtask35	72
Task4	Subtask12	72
Task5	Subtask13	72
Task6	Subtask14	72
Task7	Subtask15	72
Task8	Subtask16	72
Task9	Subtask17	72
Task10	Subtask18	72
Task12	Subtask20	72
Task1	Subtask21	72
Task3	Subtask23	72
Task4	Subtask24	72
Task5	Subtask25	72
Task9	Subtask29	72
Task10	Subtask30	72
Task11	Subtask31	72
Task12	Subtask32	72
Task1	Subtask33	72
Task4	Subtask36	72
Task5	Subtask37	72
Task6	Subtask38	72
Task8	Subtask28	70
Task7	Subtask27	68
Task1	Subtask9	66
Task2	Subtask34	64
Task3	Subtask11	62
Task6	Subtask26	59

Margaret

Margaret

Key Activities

Report Importance & Qualitative Marks

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Ms. Margaret’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task12	Subtask2	75
Task1	Subtask41	72
Task10	Subtask38	72
Task11	Subtask39	72
Task2	Subtask42	72
Task3	Subtask43	72
Task5	Subtask45	72
Task7	Subtask47	72
Task8	Subtask48	72
Task9	Subtask49	72
Task10	Subtask50	72
Task11	Subtask1	72
Task7	Subtask35	71
Task9	Subtask37	71
Task6	Subtask34	71
Task4	Subtask44	70
Task8	Subtask36	68
Task6	Subtask46	68
Task12	Subtask40	62

Eric

Eric

Key Activities

Report Importance & Qualitative Marks

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Mr. Eric’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task5	Subtask3	73
Task3	Subtask1	73
Task8	Subtask44	72
Task6	Subtask4	72
Task10	Subtask46	72
Task11	Subtask47	72
Task12	Subtask48	72
Task2	Subtask50	72
Task4	Subtask2	72
Task6	Subtask42	71
Task9	Subtask45	71
Task1	Subtask49	70
Task7	Subtask43	62

Alan

Alan

Key Activities

Report Importance & Qualitative Marks

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Mr. Alan’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task7	Subtask39	72
Task1	Subtask45	72
Task2	Subtask46	72
Task11	Subtask43	71
Task3	Subtask47	71
Task8	Subtask40	70
Task10	Subtask42	70
Task4	Subtask48	70
Task12	Subtask44	68
Task9	Subtask41	60

Francis

Francis

Key Activities

Report Importance & Qualitative Marks

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Mr. Francis’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task3	Subtask45	72
Task4	Subtask46	72
Task5	Subtask47	72
Task6	Subtask48	72
Task7	Subtask49	72
Task6	Subtask10	72
Task8	Subtask12	72
Task11	Subtask15	72
Task12	Subtask16	72
Task1	Subtask17	72
Task9	Subtask25	72
Task10	Subtask26	72
Task1	Subtask29	72
Task3	Subtask31	72
Task4	Subtask8	71
Task5	Subtask9	71
Task11	Subtask27	71
Task2	Subtask6	70
Task9	Subtask1	70
Task10	Subtask2	70
Task9	Subtask13	70
Task2	Subtask30	69
Task4	Subtask32	69
Task11	Subtask3	68
Task12	Subtask4	68
Task1	Subtask5	68
Task10	Subtask14	68
Task2	Subtask18	68
Task3	Subtask19	68
Task4	Subtask20	68
Task5	Subtask21	68
Task6	Subtask22	68
Task7	Subtask23	68
Task8	Subtask24	68
Task12	Subtask28	68
Task8	Subtask50	68
Task5	Subtask33	66
Task3	Subtask7	66
Task1	Subtask43	64
Task2	Subtask44	64
Task7	Subtask11	62

Geoffrey

Geoffrey

Key Activities

Report Importance & Qualitative Marks

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Mr. Geoffrey’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task5	Subtask17	72
Task12	Subtask24	72
Task6	Subtask18	71
Task4	Subtask16	70
Task11	Subtask23	70
Task9	Subtask21	70
Task7	Subtask19	70
Task2	Subtask14	70
Task1	Subtask13	69
Task3	Subtask15	69
Task8	Subtask20	69
Task1	Subtask25	69
Task10	Subtask22	69

Roy

Roy

Key Activities

Report Importance & Qualitative Marks

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Mr. Roy’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task11	Subtask35	74
Task2	Subtask26	72
Task5	Subtask29	72
Task8	Subtask32	72
Task9	Subtask33	72
Task10	Subtask34	72
Task3	Subtask27	71
Task6	Subtask30	70
Task7	Subtask31	69
Task4	Subtask28	62

Blake

Blake

Key Activities

Report Importance & Qualitative Marks

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Mr. Blake’s Reports

Key Activity	Extended Responsibility	Qualitative Marks
Task3	Subtask49	72
Task9	Subtask43	72
Task6	Subtask2	72
Task7	Subtask3	72
Task12	Subtask8	72
Task10	Subtask44	71
Task1	Subtask47	71
Task11	Subtask7	70
Task2	Subtask48	70
Task5	Subtask1	70
Task9	Subtask5	70
Task8	Subtask4	68
Task10	Subtask6	66
Task11	Subtask45	62
Task12	Subtask46	62
Task4	Subtask50	60

Reports Summary

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Engineering & Analytics Team Reports Summary

Team	# Key Activity	# Extended Responsibility
Engineering	12	50
Analytics	12	50
Total	12	50

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Weekly Reports

Week	# Key Activity	# Extended Responsibility
Week - 1	12	45
Week - 2	12	49
Week - 3	12	40
Week - 4	5	6

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Not Submitted Reports

Sl.	Name of Report	Status	Remarks	Responsible
1	Task 420	Submitted Late	Due to late data receiving	Tucker, Chris
2	SQL Report	Submitted Late	Due to late data receiving	Tucker, Chris

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Unique number of Key Activity & Extended Responsibility are considered

Data

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Engineering & Analytics Team Individual Marks Data

Code

## ----setup, include=FALSE--------------------------
knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE)


## --------------------------------------------------
library(readxl)
require(dplyr)
require(shiny)
require(ggplot2)
require(plotly)
require(knitr)
library(kableExtra)
require(janitor)
require(tidyr)
require(DT)

####################################################
####################################################
####################################################


# Steps

# Read Current Month Data
# Read Not Submitted Excel Files for Table
# Read Previous Rank Table Excel File
# Write csv File


##### Current Month With All Reports

dat <- read_excel("February Data 2 All Activity.xlsx", col_names = TRUE)


###### Read data of previous Month ######

PreviousMonth <- read.csv("CalculatedNovember.csv", header = T)
datprevmonth <- PreviousMonth
# View(dat)


###### Not Submitted Reports Excel File ######

datmissing <- read_xlsx("Not Submitted Reports.xlsx")


###### Previous Month Marks for ranks ######

datprevrank <- read_excel("prevrank.xlsx")

####################################################
####################################################
####################################################



## ---- eval=TRUE, results='hide'--------------------
# Check Data
head(dat)
# Check variables
glimpse(dat)
# CHeck Names for duplicates, Edit if necessary
unique(dat$Name)
# Check Key Activity
unique(dat$`Key Activity`)
# Check Importance
table(dat$Importance)
# Check Deadline
table(dat$Deadline)
# Check Marks Range for outliers #### Marks is given by Leads ####
range(dat$Marks)
# Check Weeks for any duplicates
table(dat$Week)
# Check MOnths
table(dat$Month)
# Check Team
table(dat$Team)
#Check SUbteam
table(dat$Subteam)

# Check Name and Team
dat %>% group_by(Name, Team, Subteam) %>% summarise(n()) %>% arrange(Team, Name)


# Calculate Quantitative Mark
PriMark <- NULL
for(i in 1:length(dat$Name)){
    if(dat$Importance[i] == "High"){
        PriMark[i] <- 5
    }
    if(dat$Importance[i] == "Medium"){
        PriMark[i] <- 3
    }
    if(dat$Importance[i] == "Moderate"){
        PriMark[i] <- 2
    }
}
dat$PriMark <- PriMark
# PriMark is marks based on priority
table(dat$PriMark)
table(dat$Importance)


DeadMark <- NULL
for(i in 1:length(dat$Name)){
    if(dat$Deadline[i] == "Ceiling"){
        DeadMark[i] <- 1
    }
    if(dat$Deadline[i] == "Target"){
        DeadMark[i] <- 0.90
    }
    if(dat$Deadline[i] == "Floor"){
        DeadMark[i] <- 0
    }
}
dat$DeadMark <- DeadMark
# DeadMark is marks based on Deadline Time
table(dat$DeadMark)

table(dat$Deadline)


dat <- dat %>% group_by(Name) %>% mutate(Target = PriMark / sum(PriMark)) 


# Check if target is 100% for each at each month
dat %>% group_by(Name, Month) %>% summarise(sum(Target), n())
# This Target is Marks based on Frequency and numbers based on priotity
# Target is Target Marks For each individual in each individual task


# QuanTitative Marks
# dat$QuanMark <- dat$DeadMark * dat$Target * 0.50

dat$QualMark <- dat$Marks * dat$Target

dat$FinalMark <- dat$QualMark


# Check Rankings Based in Final MArks
dat %>% 
  group_by(Name) %>% 
  summarise(sorttc = sum(QualMark)) %>% 
  arrange(desc(sorttc))

# View(dat)

dat$tgt <- dat$Target / sum(dat$Target)
dat$ach <- dat$QualMark / sum(dat$Target) 

# tgt and ach by Team for Individual team slide

dat <- dat %>% 
  group_by(Team) %>% 
  mutate(tgtteam = tgt / sum(tgt),
         achteam = ach / sum(tgt))

sum(dat$tgtteam)
sum(dat$achteam)




## ---- eval=FALSE-----------------------------------
## ## **Welcome**
## ### Welcome to Engineering and Analytics Team Activity Dashboard
## #### July, 2020


## --------------------------------------------------

pbakey <- dat %>% 
  group_by(`Key Activity`) %>% 
  summarise(TGT = round(100*sum(tgt),1), Ach = round(100*sum(ach),2) ) %>% 
  mutate(ACH = ifelse(Ach>TGT, TGT, Ach)) %>% 
  arrange(desc(TGT)) %>% 
  mutate(`ACH%` = round(100*ACH/TGT,1)) %>% 
  select(`Key Activity`, TGT, ACH, `ACH%`) 

pbakey <- pbakey[1:10,] # TOp 10 activities of p&ba

# Add others row in pbakey

ot <- 100 - sum(pbakey$TGT)
ot <- as.double(ot)                
oth <- data.frame("Others", as.double(ot), 0,0)

pbakey[11,] <- oth


#Previous Month
pbaprev <- datprevmonth %>% 
  group_by(Key.Activity) %>% 
  summarise(TGT = round(100*sum(tgt),1), Ach = round(100*sum(ach),2) ) %>% 
  mutate(ACH = ifelse(Ach>TGT, TGT, Ach)) %>% 
  arrange(desc(TGT)) %>% 
  mutate(`ACH%` = round(100*ACH/TGT,1)) %>% 
  select(Key.Activity, TGT, ACH, `ACH%`) 

pbaprev <- pbaprev[1:7,] # TOp 5 key activities of p&ba of previous month

# Add others row in pbaprev

ot <- 100 - sum(pbaprev$TGT)
ot <- as.double(ot)                
oth <- data.frame("Others", as.double(ot), 0,0)

pbaprev[8,] <- oth





## --------------------------------------------------

colors <- c('rgba(249, 146, 108, 1)',
            'rgba(114, 195, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)'
            )

                          

# Add Title
pltttl <- 100* round( sum(dat$ach), 3)

pltttl12 <- paste("Team Achievement", pltttl,"%")

plot_ly(data = pbakey, labels = ~`Key Activity`, values = ~TGT, type = 'pie', 
                         sort=T, direction="anticlockwise", marker = list(colors = colors, line = list(color = '#FFFFFF', width = 1.2)),
        
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent', hoverinfo = 'label+percent', textfont = list(size = 13), textposition = 'outside', 
                          showlegend = F, height = 350, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 85, t = 55,  pad = 1 ),
                     title=pltttl12,
         font=list(  size = 12)) 


## ---- eval=FALSE-----------------------------------
## #### Previous Month Key Activities
## 
## colors <- c('rgba(249, 146, 108, 1)',
##             'rgba(114, 195, 218, 1)',
##             'rgba(108, 224, 189, 1)',
##             'rgba(239, 118, 118, 1)',
##             'rgba( 18, 167, 226, 1)',
##             'rgba(244, 113, 222, 1)',
##             'rgba(114, 218, 136, 1)',
##             'rgba(255, 148, 184, 1)',
##             'rgba(218, 114, 159, 1)',
##             'rgba(114, 161, 218, 1)'
##             )
## 
## # Add Title
## pltttl2 <- 100* round( sum(datprevmonth$ach), 3)
## 
## pltttl22 <- paste("Team Achievement", pltttl2,"%")
## 
## plot_ly(data = pbaprev, labels = ~Key.Activity, values = ~TGT, type = 'pie',
##                          sort=T, direction="anticlockwise", marker = list(colors = colors, line = list(color = '#FFFFFF', width = 1.2)),
##                           #title= pltttl22,
##            #title='<b>Key Activities</b>' ,
##                          textinfo='label+percent', hoverinfo = 'label+percent', textfont = list(size = 13), textposition = 'outside',
##                           showlegend = F, height = 350, width = 950
##         ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 85, t = 55,  pad = 1 ),
##                      title=pltttl22,
##          font=list(  size = 12))


## --------------------------------------------------

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  #filter(Team == "Engineering") %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
  #filter(Team == "Engineering") %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  #filter(Team == "Engineering") %>% 
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`, na.rm = T),
            Formmean = mean(`Formatting (20%)`, na.rm = T))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################


fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = "Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`,  
  textfont = list(size = 14), 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,   
  textfont = list(size = 14),
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )







## --------------------------------------------------

#### Engineering & Analytics Team Top 10 Key Activities Table

#kable(pbakey)



## --------------------------------------------------

#### Engineering & Analytics Team Top 10 Extended Responsibility Table

# kable(pbaext)



## --------------------------------------------------

pkey <- dat %>% 
  filter(Team == "Engineering") %>% 
  group_by(`Key Activity`) %>% 
  summarise(TGT = round(100*sum(tgtteam),1), Ach = round(100*sum(achteam),2) ) %>% 
  mutate(ACH = ifelse(Ach>TGT, TGT, Ach)) %>% 
  arrange(desc(TGT)) %>% 
  mutate(`ACH%` = round(100*ACH/TGT,1)) %>% 
  select(`Key Activity`, TGT, ACH, `ACH%`) 

pkey <- pkey[1:10,]  ###### Select Top 2 Key Activities ########



# Add others row in pkey

ot <- 100 - sum(pkey$TGT)
ot <- as.double(ot)                
oth <- data.frame("Others", as.double(ot), 0,0)

pkey[11,] <- oth


pext <- dat %>% 
  filter(Team == "Engineering") %>% 
  group_by(`Extended Responsibility`) %>% 
  summarise(TGT = round(100*sum(tgt),2), Ach = round(100*sum(ach),2) ) %>% 
  mutate(ACH = ifelse(Ach>TGT, TGT, Ach)) %>% 
  arrange(desc(ACH)) %>% 
  mutate(`ACH%` = round(100*ACH/TGT,1)) %>% 
  select(`Extended Responsibility`, TGT, ACH, `ACH%`)

pext <- pext[1:10,] # Select Top 10 Extended Responsibilities



#Previous Month
pkeyprev <- datprevmonth %>% 
  filter(Team == "Engineering") %>% 
  group_by(Key.Activity) %>% 
  summarise(TGT = round(100*sum(tgtteam),1), Ach = round(100*sum(achteam),2) ) %>% 
  mutate(ACH = ifelse(Ach>TGT, TGT, Ach)) %>% 
  arrange(desc(TGT)) %>% 
  mutate(`ACH%` = round(100*ACH/TGT,1)) %>% 
  select(Key.Activity, TGT, ACH, `ACH%`) 

pkeyprev <- pkeyprev[1:7,] # TOp 2 key activities of p&ba of previous month

# Add others row in pbaprev

ot <- 100 - sum(pkeyprev$TGT)
ot <- as.double(ot)                
oth <- data.frame("Others", as.double(ot), 0,0)

pkeyprev[8,] <- oth





## --------------------------------------------------

colors <- c('rgba(249, 146, 108, 1)',
            'rgba(114, 195, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)'
            )

# Add Title
pltttl <- 100* round( sum(dat$achteam[dat$Team=="Engineering"]), 3)

pltttl12 <- paste("Team Achievement", pltttl,"%")

plot_ly(data = pkey, labels = ~`Key Activity`, values = ~TGT, type = 'pie', 
                         sort=T, direction="anticlockwise", marker = list(colors = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent', hoverinfo = 'label+percent', textfont = list(size = 13), textposition = 'outside', 
                          showlegend = F, height = 350, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 85, t = 55,  pad = 1 ),
                     title=pltttl12,
         font=list(  size = 12))  


## ---- eval=FALSE-----------------------------------
## 
## 
## #### Engineering Team Previous Month Key Activities
## 
## colors <- c('rgba(249, 146, 108, 1)',
##             'rgba(114, 195, 218, 1)',
##             'rgba(108, 224, 189, 1)',
##             'rgba(239, 118, 118, 1)',
##             'rgba( 18, 167, 226, 1)',
##             'rgba(244, 113, 222, 1)',
##             'rgba(114, 218, 136, 1)',
##             'rgba(255, 148, 184, 1)',
##             'rgba(218, 114, 159, 1)',
##             'rgba(114, 161, 218, 1)'
##             )
## 
## # Add Title
## pltttl2 <- 100* round( sum(datprevmonth$achteam[datprevmonth$Team=="Engineering"]), 3)
## 
## pltttl22 <- paste("Team Achievement", pltttl2,"%")
## 
## plot_ly(data = pkeyprev, labels = ~Key.Activity, values = ~TGT, type = 'pie',
##                          sort=T, direction="anticlockwise", marker = list(colors = colors, line = list(color = '#FFFFFF', width = 1.2)),
##                           #title= pltttl22,
##            #title='<b>Key Activities</b>' ,
##                          textinfo='label+percent', hoverinfo = 'label+percent', textfont = list(size = 13), textposition = 'outside',
##                           showlegend = F, height = 350, width = 950
##         ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 85, t = 55,  pad = 1 ),
##                      title=pltttl22,
##          font=list(  size = 12))


## --------------------------------------------------
ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Team == "Engineering") %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
  filter(Team == "Engineering") %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Team == "Engineering") %>% 
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`, na.rm = T),
            Formmean = mean(`Formatting (20%)`, na.rm = T))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`,  
  textfont = list(size = 14), 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = "Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`,   
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,   
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1,  fig3, shareY = T, nrows = 1, titleX = TRUE )



## --------------------------------------------------

#### Engineering Team Top 10 Key Activities Table
#kable(pkey)



## --------------------------------------------------
#### Engineering Team Top 10 Extended Responsibility Table
#kable(pext)



## --------------------------------------------------



bakey <- dat %>% 
  filter(Team == "Analytics") %>% 
  group_by(`Key Activity`) %>% 
  summarise(TGT = round(100*sum(tgtteam),1), Ach = round(100*sum(achteam),2) ) %>% 
  mutate(ACH = ifelse(Ach>TGT, TGT, Ach)) %>% 
  arrange(desc(ACH)) %>% 
  mutate(`ACH%` = round(100*ACH/TGT,1)) %>% 
  select(`Key Activity`, TGT, ACH, `ACH%`) 

bakey <- bakey[1:10,]



# Add others row in bakey

ot <- 100 - sum(bakey$TGT)
ot <- as.double(ot)                
oth <- data.frame("Others", as.double(ot), 0,0)

bakey[11,] <- oth

baext <- dat %>% 
  filter(Team == "Analytics") %>% 
  group_by(`Extended Responsibility`) %>% 
  summarise(TGT = round(100*sum(tgt),2), Ach = round(100*sum(ach),2) ) %>% 
  mutate(ACH = ifelse(Ach>TGT, TGT, Ach)) %>% 
  arrange(desc(ACH)) %>% 
  mutate(`ACH%` = round(100*ACH/TGT,1)) %>% 
  select(`Extended Responsibility`, TGT, ACH, `ACH%`)

baext <- baext[1:10,]


#Previous Month
bakeyprev <- datprevmonth %>% 
  filter(Team == "Analytics") %>% 
  group_by(Key.Activity) %>% 
  summarise(TGT = round(100*sum(tgtteam),1), Ach = round(100*sum(achteam),2) ) %>% 
  mutate(ACH = ifelse(Ach>TGT, TGT, Ach)) %>% 
  arrange(desc(TGT)) %>% 
  mutate(`ACH%` = round(100*ACH/TGT,1)) %>% 
  select(Key.Activity, TGT, ACH, `ACH%`) 

bakeyprev <- bakeyprev[1:7,] # TOp 2 key activities of p&ba of previous month

# Add others row in bakeyprev

ot <- 100 - sum(bakeyprev$TGT)
ot <- as.double(ot)                
oth <- data.frame("Others", as.double(ot), 0,0)

bakeyprev[8,] <- oth



## --------------------------------------------------
colors <- c('rgba(249, 146, 108, 1)',
            'rgba(114, 195, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)'
            )

# Add Title
pltttl <- 100* round( sum(dat$achteam[dat$Team=="Analytics"]), 3)

pltttl12 <- paste("Team Achievement", pltttl,"%")

plot_ly(data = bakey, labels = ~`Key Activity`, values = ~TGT, type = 'pie', 
                         sort=T, direction="anticlockwise", marker = list(colors = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent', hoverinfo = 'label+percent', textfont = list(size = 13), textposition = 'outside', 
                          showlegend = F, height = 350, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 85, t = 55,  pad = 1 ),
                     title=pltttl12,
         font=list(  size = 12))  


## ---- eval=FALSE-----------------------------------
## 
## #### Analytics Team Previous Month Key Activities
## 
## colors <- c('rgba(249, 146, 108, 1)',
##             'rgba(114, 195, 218, 1)',
##             'rgba(108, 224, 189, 1)',
##             'rgba(239, 118, 118, 1)',
##             'rgba( 18, 167, 226, 1)',
##             'rgba(244, 113, 222, 1)',
##             'rgba(114, 218, 136, 1)',
##             'rgba(255, 148, 184, 1)',
##             'rgba(218, 114, 159, 1)',
##             'rgba(114, 161, 218, 1)'
##             )
## # Add Title
## pltttl2 <- 100* round( sum(datprevmonth$achteam[datprevmonth$Team=="Analytics"]), 3)
## 
## pltttl22 <- paste("Team Achievement", pltttl2,"%")
## 
## plot_ly(data = bakeyprev, labels = ~Key.Activity, values = ~TGT, type = 'pie',
##                          sort=T, direction="anticlockwise", marker = list(colors = colors, line = list(color = '#FFFFFF', width = 1.2)),
##                           #title= pltttl22,
##            #title='<b>Key Activities</b>' ,
##                          textinfo='label+percent', hoverinfo = 'label+percent', textfont = list(size = 13), textposition = 'outside',
##                           showlegend = F, height = 350, width = 950
##         ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 85, t = 55,  pad = 1 ),
##                      title=pltttl22,
##          font=list(  size = 12))


## --------------------------------------------------
ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Team == "Analytics") %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
  filter(Team == "Analytics") %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Team == "Analytics") %>% 
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################


fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`,   
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = "Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`,   
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,   
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1,  fig3, shareY = T, nrows = 1, titleX = TRUE )




## --------------------------------------------------

#### Analytics Team Top 10 Key Activities Table
#kable(bakey)



## --------------------------------------------------
#### Analytics Team Top 10 Extended Responsibility Table
#kable(baext)



## ---- fig.height=4, fig.width=6--------------------

# Filter only TOfazzol Sir marks, and take average of Manager him

rankcom <- dat %>% 
  filter(`Manager` == "Theodor") %>% 
  group_by(Subteam) %>% 
  summarise( Ach = 100*mean(Marks)) %>% 
  arrange(desc(Ach)) %>% 
  mutate(R=seq(1:length(Ach))) %>% 
  select(R, Subteam, Ach)

rankcom$Ach <- round(rankcom$Ach,1)

plot_ly(rankcom, x = ~Ach, y = ~reorder(Subteam,Ach), 
        color = ~Subteam,

        type = 'bar',
        
        text = ~Ach,
        textposition = 'auto',
        textfont = list(color = '#000000', size = 12),

        orientation = 'h', 
        hoverinfo='y+text') %>% 
        
        #marker = list(color = 'rgba(99,21,133, 0.8)', 
        #  line = list(color = 'rgba(99,21,133,1)', width = 1)) ) %>%
  
  layout( showlegend = FALSE,
          xaxis = list(title = "", ticks="",zeroline = FALSE,  
                       showline = FALSE, showticklabels = FALSE, 
                       showgrid = FALSE),
          yaxis = list(title = "",
                       tickfont=list(size=15)),
          autosize = F, width = 800, height = 400
          #xaxis = list(tickfont = list(size = 8))
  )  
    


## --------------------------------------------------


teammembers <- readxl::read_xlsx("Team Members.xlsx")

require(knitr)
opts <- options(knitr.kable.NA = "")

teammembers %>% kable() %>% kable_styling(bootstrap_options = "striped", 
                                          font_size = 13, 
                                          fixed_thead = list(enabled = T/F, background = "skyblue")) 



## --------------------------------------------------

# Keep only one member in all 5 teams
# This way it will always be automatic


rankcom <- dat %>% 
        filter(`Manager` != "Theodor") 

rankcom <- bind_rows(rankcom, dat %>% filter(Name == "Francis"))
  
  
rankcom <- rankcom %>% 
        group_by(Name, Subteam) %>% 
        summarise(sum(FinalMark)) 


rankcom <- rankcom %>% 
        group_by(Subteam) %>% slice_max(order_by = `sum(FinalMark)`, n = 1)

names(rankcom) <- c("Name", "Subteam", "Marks")


rankcom$Marks <- 100*rankcom$Marks
rankcom$Marks <- round(rankcom$Marks, 1)

rankcom <- rankcom %>% arrange(desc(Marks))

rankcom %>% kable() %>% kable_styling(bootstrap_options = "striped", 
                                      font_size = 13, 
                                      fixed_thead = list(enabled = T/F, background = "skyblue")) 






## ---- fig.height=4, fig.width=6, fig.align='right'----

rankcom <- rankcom %>% mutate(nam = paste(Name, "(", Subteam, ")"))

plot_ly(rankcom, x = ~Marks, y = ~reorder(Name, Marks),
                       color = ~Subteam,
        
        
        text = ~Marks,
        textposition = 'auto',
        textfont = list(color = '#000000', size = 12),
        
                       type = 'bar', width = 1, orientation = 'h', 
                       hoverinfo='y+text') %>%  
                      #marker = list(color = 'rgba(29,41,133, 0.8)', 
                      #line = list(color = 'rgba(29,41,133,1)', width = 1)) ) %>%
            layout( showlegend = FALSE,
              
                    xaxis = list(title = "", ticks="",zeroline = FALSE,  
                                 showline = FALSE, showticklabels = FALSE, 
                                 showgrid = FALSE),
                    yaxis = list(title = "",
                                 tickfont=list(size=15)),
                                 autosize = F, width = 800, height = 400,
                    margin =list(l = 0, r = 0, b = 0, t = 0,  pad = 1 )
                    #xaxis = list(tickfont = list(size = 8))
                    )  




## ---- fig.height=7.3-------------------------------
rankcom <- dat %>% 
        group_by(Name) %>% 
        summarise( Ach = 100*sum(FinalMark)) %>% 
        arrange(desc(Ach)) %>% 
        mutate(R=seq(1:length(Ach))) %>% 
        select(R, Name, Ach)

rankcom$Ach <- round(rankcom$Ach,1)

plot_ly(rankcom, x = ~Ach, y = ~reorder(Name,Ach), 
                       type = 'bar', width = 1, orientation = 'h', text = ~Ach, textposition = 'auto', hoverinfo='y+text'
        
        ) %>%
            layout( xaxis = list(title = "", ticks="",zeroline = FALSE,  
                                 showline = FALSE, showticklabels = FALSE, 
                                 showgrid = FALSE),
                    yaxis = list(title = "",
                                 tickfont=list(size=15)),
                                 autosize = F, width = 700, height = 700
                    #xaxis = list(tickfont = list(size = 8))
                    )     


## ---- eval=FALSE-----------------------------------
## 
## ### Current & Previous Month Rankings
## 
## rankcom <- dat %>%
##   group_by(Name) %>%
##   summarise( Ach = 100*sum(FinalMark)) %>%
##   arrange(desc(Ach)) %>%
##   mutate(R=seq(1:length(Ach))) %>%
##   select(R, Name, Ach)
## 
## rankcom$Ach <- round(rankcom$Ach,2)
## 
## mergerank <- merge(rankcom, datprevrank, by = "Name")
## names(mergerank)[4] <- "Previous Ach"
## 
## mergerankkable <- mergerank %>%
##   arrange( desc(`Previous Ach` )) %>%
##   mutate(Previous = 1:length(unique(dat$Name)))%>%
##   mutate(Current = R)%>%
##   select(Name, Current, Previous, Ach, `Previous Ach`) %>%
##   arrange(desc(Ach))
## 
## require(knitr)
## mergerankkable %>% kable() %>% kable_styling(bootstrap_options = "striped", font_size = 17)
## 
## 
## 


## --------------------------------------------------
rankplan <- dat %>% filter(Team == "Engineering") %>% 
        group_by(Name) %>% 
        summarise( Ach = 100*sum(FinalMark)) %>% 
        arrange(desc(Ach)) %>% 
        mutate(R=seq(1:length(Ach))) %>% 
        select(R, Name, Ach)

rankplan$Ach <- round(rankplan$Ach,1)

plot_ly(rankplan, x = ~Ach, y = ~reorder(Name,Ach), width = 2,
                       type = 'bar', orientation = 'h',  text = ~Ach,
        hoverinfo='y+text', textposition = 'auto', marker = list(color = 'rgba(199,21,133, 0.8)',
                            line = list(color = 'rgba(199,21,133,1)', width = 1))) %>%
            layout( xaxis = list(title = "", ticks="",zeroline = FALSE,  
                                 showline = FALSE, showticklabels = FALSE, 
                                 showgrid = FALSE),
                    yaxis = list(title = "",
                                 tickfont=list(size=15))
                    #xaxis = list(tickfont = list(size = 8))
                    )     


## --------------------------------------------------
rankan <- dat %>% filter(Team == "Analytics") %>% 
        group_by(Name) %>% 
        summarise( Ach = 100*sum(FinalMark)) %>% 
        arrange(desc(Ach)) %>% 
        mutate(R=seq(1:length(Ach))) %>% 
        select(R, Name, Ach)

rankan$Ach <- round(rankan$Ach,1)

plot_ly(rankan, x = ~Ach, y = ~reorder(Name,Ach), 
                       type = 'bar', width = 0.8, orientation = 'h',  text = ~Ach,
        textposition = 'auto', 
        hoverinfo='y+text', 
        marker = list(color = 'rgba(    25,25,112, 0.8)',
                line = list(color = 'rgba(  25,25,112,1)', width = 1))) %>%
            layout( xaxis = list(title = "", ticks="",zeroline = FALSE,  
                                 showline = FALSE, showticklabels = FALSE, 
                                 showgrid = FALSE),
                    yaxis = list(title = "",
                                 tickfont=list(size=15))
                    #xaxis = list(tickfont = list(size = 8))
                    )     


## ---- fig.height = 10.5, fig.width = 8, eval=FALSE----
## 
## ### Consistency Ranking September to November
## 
## require(readxl)
## require(plotly)
## require(dplyr)
## 
## datconsis <- readxl::read_xlsx("Jul-Nov.xlsx")
## 
## 
## datconsis <- data.frame(datconsis)
## 
## datconsis$Average <- round(rowMeans(datconsis[, -1], na.rm = T),2)
## 
## datconsis <- datconsis %>% arrange(Average)
## 
## #dat
## 
## datconsis$rank <- seq(1:length(datconsis$Name))
## 
## #dat
## 
## #class(dat)
## 
## November <- datconsis$November
## October <- datconsis$October
## September <- datconsis$September
## #August <- datconsis$August
## #July <- datconsis$July
## Average <- datconsis$Average
## 
## fig <- plot_ly(datconsis) %>% add_trace(x = ~September, y = ~Name, type = 'bar',
##                          text = September, textposition = 'auto',
##                          name = 'September',
##                          hoverinfo = 'Name+September',
##                          marker = list(color = 'rgb((255,127,80))',
##                                        line = list(color = 'rgb(8,98,107)', width = 1.5))) %>%
##   layout(yaxis = list(categoryorder = "array", categoryarray = rank))    %>%
## 
## 
##  add_trace(x = ~October, y = ~Name, type = 'bar',
##                          text = October, textposition = 'auto',
##                          name = 'October',
##                          hoverinfo = 'Name+October',
##                          marker = list(color = 'rgb(158, 221, 124)',
##                                        line = list(color = 'rgb(8,98,107)', width = 1.5))) %>%
##   layout(yaxis = list(categoryorder = "array", categoryarray = rank)) %>%
## 
## 
## 
## 
##  add_trace(x = ~November, y = ~Name, type = 'bar',
##                          text = November, textposition = 'auto',
##                          name = 'November',
##                          hoverinfo = 'Name+November',
##                          marker = list(color = 'rgb(158, 221, 124)',
##                                        line = list(color = 'rgb(8,98,107)', width = 1.5))) %>%
##   layout(yaxis = list(categoryorder = "array", categoryarray = rank)) %>%
## 
## 
## 
## 
##   add_trace(x = ~Average, y = ~Name, type = 'bar',
##                          text = Average, textposition = 'auto',
##                          name = 'Average',
##                          hoverinfo = 'Name+Average',
##                          marker = list(color = 'rgb(198,202,225)',
##                                        line = list(color = 'rgb(8,48,107)', width = 1.5))) %>%
##   layout(yaxis = list(categoryorder = "array", categoryarray = rank),
##          xaxis= list(showticklabels = FALSE, title=" "))
## 
## 
## fig %>%
## layout(yaxis = list(categoryorder = "array", categoryarray = rank, showticklabels = TRUE, title="", tickfont=list(size=15)),
##        xaxis= list(title=""))
## 


## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Tucker") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Tucker") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 





## --------------------------------------------------

colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 55, t = 40,  pad = 1 )) 


## ---- fig.width=5----------------------------------
Nam <- "Tucker"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )






## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------


#ne <- as.character(length(dind2$`Extended Responsibility`))
#as <- sum(dind2$Ach)
#as2 <- mean(dind2$`Ach%`)
#ot <- data.frame("Total", ne, 100, as, as2)
#dind2[length(dind2$Name) + 1,  ] <- ot 
#x <- dind2 %>% kable(digits = 1) %>% kable_styling(bootstrap_options = "striped")
#row_spec(x, dim(dind2)[1], bold = TRUE)


## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Benedict") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Benedict") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 





## --------------------------------------------------

colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 65, t = 40,  pad = 1 )) 


## ---- fig.width=5----------------------------------
Nam <- "Benedict"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )






## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------


#ne <- as.character(length(dind2$`Extended Responsibility`))
#as <- sum(dind2$Ach)
#as2 <- mean(dind2$`Ach%`)
#ot <- data.frame("Total", ne, 100, as, as2)
#dind2[length(dind2$Name) + 1,  ] <- ot 
#x <- dind2 %>% kable(digits = 1) %>% kable_styling(bootstrap_options = "striped")
#row_spec(x, dim(dind2)[1], bold = TRUE)


## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Jenson") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Jenson") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 



## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent', hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Jenson"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`, na.rm = T), 
            Impmean = mean(`Improvement Initiatives (30%)`, na.rm = T),
            Formmean = mean(`Formatting (20%)`, na.rm = T))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )





## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Jamie") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Jamie") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Chris"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Chris") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Chris") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Chris"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Elliot") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Elliot") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 30,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Elliot"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Nancy") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Nancy") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Nancy"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Ross") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Ross") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Ross"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Scarlette") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Scarlette") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 





## --------------------------------------------------

colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 55, t = 40,  pad = 1 )) 


## ---- fig.width=5----------------------------------
Nam <- "Scarlette"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )






## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "10em") %>% column_spec( 2, width = "15em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------


#ne <- as.character(length(dind2$`Extended Responsibility`))
#as <- sum(dind2$Ach)
#as2 <- mean(dind2$`Ach%`)
#ot <- data.frame("Total", ne, 100, as, as2)
#dind2[length(dind2$Name) + 1,  ] <- ot 
#x <- dind2 %>% kable(digits = 1) %>% kable_styling(bootstrap_options = "striped")
#row_spec(x, dim(dind2)[1], bold = TRUE)


## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Marshman") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Marshman") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Marshman"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Hunter") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Hunter") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 65, t = 30,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Hunter"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Margaret") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Margaret") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 75, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Margaret"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Eric") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Eric") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 80, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Eric"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Alan") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Alan") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)



## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Alan"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Francis") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 

dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Francis") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 70, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Francis"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Geoffrey") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 


dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Geoffrey") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 90, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Geoffrey"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Roy") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 


dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Roy") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Roy"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------
dind <- dat %>%
  filter(Name=="Blake") %>%  
  select(Name, `Key Activity`, Target, FinalMark ) %>% 
  group_by(Name, `Key Activity`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt) 


dind2 <- dat %>%
  ungroup() %>% 
  filter(Name=="Blake") %>%  
  select(Name, `Extended Responsibility` , Target, FinalMark ) %>% 
  group_by(Name, `Extended Responsibility`) %>% 
  summarise(Tgt = 100*sum(Target), Ach = 100*sum(FinalMark)) %>% 
  mutate(`Ach%` = 100*Ach/Tgt)


## --------------------------------------------------
colors <- c('rgba(114, 195, 218, 1)', 
            'rgba(114, 218, 136, 1)', 
            'rgba(255, 148, 184, 1)', 
            'rgba(218, 114, 159, 1)', 
            'rgba(114, 161, 218, 1)',
            'rgba(108, 224, 189, 1)',
            'rgba(239, 118, 118, 1)',
            'rgba(249, 146, 108, 1)',
            'rgba( 18, 167, 226, 1)',
            'rgba(244, 113, 222, 1)')

plot_ly(data = dind, labels = ~`Key Activity`, values = ~Tgt, type = 'pie', 
                         sort=T, direction="anticlockwise",marker = list(colors  = colors, line = list(color = '#FFFFFF', width = 1.2)),
                          #title='<b>Key Activities</b>' ,
                         textinfo='label+percent',hoverinfo = 'label+percent', textfont = list(size = 15), textposition = 'outside', 
                          showlegend = F, height = 320, width = 950
        ) %>% layout(autosize = F, margin =list(l = 0, r = 0, b = 50, t = 40,  pad = 1 )) 


## --------------------------------------------------
Nam <- "Blake"

ar1 <- c("High", "Medium", "Moderate")
dpi1 <- dat %>% 
  filter(Name == Nam) %>% 
  group_by(Importance) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi1
if(length(unique(dpi1$Importance))!=3){
  x <- data.frame(ar1[ar1 %in% dpi1$Importance==FALSE], 0,0, "0")
  colnames(x) <- names(dpi1)
  dpi1 <- dpi1 %>% rbind(x)
}
########################################
ar2 <- c("Ceiling", "Target", "Floor")
dpi2 <- dat %>% 
   filter(Name == Nam) %>% 
  group_by(Deadline) %>% 
  summarise(Imp = n()) %>% 
  mutate(`Impn` = round(100*Imp /sum(Imp),1)) %>%           
  mutate(`Imp%` = paste(`Impn`, "%"))
#dpi2

if(length(unique(dpi2$Deadline))!=3){
  x <- data.frame(ar2[ar2 %in% dpi2$Deadline==FALSE], 0,0, "0")
  colnames(x) <- names(dpi2)
  dpi2 <- dpi2 %>% rbind(x)
}

dpi2 <- dpi2[order(match(ar2, dpi2$Deadline)),]
######################################
dpi3 <- dat %>% 
  ungroup() %>% 
  filter(Name == Nam) %>%  
  select(`Factual Accuracy (50%)`, `Improvement Initiatives (30%)`, `Formatting (20%)`) %>% 
  summarise(Factmean = mean(`Factual Accuracy (50%)`), 
            Impmean = mean(`Improvement Initiatives (30%)`),
            Formmean = mean(`Formatting (20%)`))

dpi3  <- data.frame(c(names(dpi3)), c(dpi3$Factmean, dpi3$Impmean, dpi3$Formmean))
names(dpi3) <- c("Category", "Marks")
dpi3$Category <- c("Factual", "Improvement", "Formatting") 
dpi3$Marks <- round( dpi3$Marks * 100 , 1)
dpi3$Marks2 <- paste(dpi3$Marks, "%")
#dpi3

################################

fig1 <- plot_ly(
  data = dpi1,
  x = ~Importance,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(248, 180, 135, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,   orientation = 'v'
)%>% layout(yaxis = list(title = ""),
            xaxis = list(title = " Report Importance",
                         categoryorder="array",
                         categoryarray = c("High", "Medium", "Moderate"))
)
#fig1

fig2 <- plot_ly(
  data = dpi2,
  x = ~Deadline,
  y = ~`Impn`,
  text = ~`Imp%`, 
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(25, 159, 174, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  
  hoverinfo = "x+text",
  type = "bar", width = 850, orientation = 'v'
)%>% layout(barmode="overlay",
            yaxis = list(title = ""),
            xaxis = list(
              categoryorder="array",
              categoryarray = as.character("Ceiling", "Target", "Floor"),
              title = "Deadline")
)
#fig2

fig3 <- plot_ly(
  data = dpi3,
  x = ~Category,
  y = ~Marks,
  text = ~Marks2,  
  textfont = list(size = 14),
  textposition = 'auto',
  showlegend = FALSE,
  marker = list(color = 'rgba(34, 201, 126, 1)', 
                line = list(color = 'rgb(8,48,107)', width = 1.5)),
  hoverinfo = "x+text",
  type = "bar", width = 850,  orientation = 'v'
)%>% layout(barmode = "overlay",
            yaxis = list(title = ""),
            xaxis = list(title = "Qualitative Marks",
                         categoryorder="array",
                         categoryarray = c("Factual", "Formatting", "Improvement"))
)
#fig3
subplot(fig1, fig2, fig3, shareY = T, nrows = 1, titleX = TRUE )




## ---- echo=FALSE-----------------------------------

dind3 <-  dat %>% 
  filter(Name == Nam) %>% 
  select(Name, `Key Activity`, `Extended Responsibility`,  Marks) %>% arrange(desc(Marks))

dind3 <- dind3[, -c(1,2)]

dind3$Marks <- round(100*dind3$Marks, 0)

names(dind3)[3] <- "Qualitative Marks"

x <- dind3 %>% kable(digits = 1, align = "llc") %>% kable_styling(bootstrap_options = "striped")

x  %>% column_spec( 1, width = "12em") %>% column_spec( 2, width = "18em") %>% column_spec( c(3), width = "6em")




## --------------------------------------------------

tm <- c("Engineering", "Analytics")
tk <- c(length(unique(dat$`Key Activity`[dat$Team=="Engineering"])),
        length(unique(dat$`Key Activity`[dat$Team=="Analytics"])))

te <- c(length(unique(dat$`Extended Responsibility`[dat$Team=="Engineering"])),
        length(unique(dat$`Extended Responsibility`[dat$Team=="Analytics"])))

tr <- data.frame(tm, tk, te)

tt <- data.frame(tm = "Total", tk = length(unique(dat$`Key Activity`)), te=length(unique(dat$`Extended Responsibility`)))

t <- rbind(tr, tt)

x <- t %>% kable(col.names = c("Team", "# Key Activity", "# Extended Responsibility")) %>% kable_styling(bootstrap_options = "striped", font_size = 17)
row_spec(x, 3, bold = TRUE, font_size = 19)




## --------------------------------------------------
comsum <- dat %>% 
            #ungroup() %>% 
            #filter(Team == "Analytics") %>% 
            select(Month, Week, `Key Activity`, `Extended Responsibility`) %>% 
            group_by(Week) %>% 
            summarise( ############ Unique Nisi ###############
                       `# Key Activity` = length(unique(`Key Activity`)),
                       `# Extended Responsibility` = length(unique(`Extended Responsibility`))
            ) 

comsum %>% kable() %>% kable_styling(bootstrap_options = "striped", font_size = 17)



## ---- echo=F---------------------------------------

# Missing Reports 

require(knitr)

datmissing %>% kable() %>%  kable_styling(bootstrap_options = "striped", font_size = 14) %>% column_spec( 1, width = "2em") %>% column_spec( 2, width = "15em") %>% column_spec( 3, width = "10em") %>% column_spec( 4, width = "14em")





## ---- eval=FALSE-----------------------------------
## 
## 
## ### Engineering Team Reports Summary
## 
## plsum <- dat %>%
##             #ungroup() %>%
##             filter(Team == "Engineering") %>%
##             select(Month, Week, `Key Activity`, `Extended Responsibility`) %>%
##             group_by(Week ) %>%
##             summarise( ############ Unique Nisi ###############
##                        `# Key Activity` = length(unique(`Key Activity`)),
##                        `# Extended Responsibility` = length(unique(`Extended Responsibility`))
##             ) %>%
##             adorn_totals("row")
## 
## plsum %>% kable() %>% kable_styling((bootstrap_options = "striped", font_size = 17)
## 


## ---- eval=FALSE-----------------------------------
## 
## ### Analytics Team Reports Summary
## ansum <- dat %>%
##             #ungroup() %>%
##             filter(Team == "Analytics") %>%
##             select(Month, Week, `Key Activity`, `Extended Responsibility`) %>%
##             group_by(Week ) %>%
##             summarise( ############ Unique Nisi ###############
##                        `# Key Activity` = length(unique(`Key Activity`)),
##                        `# Extended Responsibility` = length(unique(`Extended Responsibility`))
##             ) %>%
##             adorn_totals("row")
## 
## ansum %>% kable() %>% kable_styling((bootstrap_options = "striped", font_size = 18)
## 


## --------------------------------------------------

require(DT)

markstable <- dat[, c(1:10) ]

# Change Name
names(markstable)[6] <- "Manager Mr/Ms"
names(markstable)[10] <- "Qualitative Marks"


# Multiply by 100
markstable[, 7:10] <- 100*markstable[, 7:10]
markstable[, 7:10] <- round(markstable[7:10], 1)

markstable %>%  DT::datatable(class = 'cell-border stripe', width = "1600px",
              extensions = c('KeyTable', 'FixedHeader', 'Scroller', "FixedColumns"),
              options = list(
                             paging = T,
                             autoWidth = FALSE,
                             #dom = 't',
                             scrollX=TRUE, 
                             scrollY = 500,
                             columnDefs = list(list(width = '350px', 
                                                    targets = list(1,2,3))),
                             pageLength = 50, 
                             fixedHeader = TRUE,
                             #deferRender = TRUE,
                             #scroller = TRUE,
                             keys = TRUE
                             #fixedColumns = list(leftColumns = 4)
                             )
              ) %>% DT::formatStyle(columns = 7:10, 
                                    fontSize = '120%')



## ---- eval=FALSE, message=FALSE, warning=false-----
## 
## 
## 
##