Toi Maori Data Visualization

Completion By Reporting Year

Code
line_chart <- tribble(~'Completion_Year',        ~'n'
             ,1995                ,9
             ,1996                ,18
             ,1997                ,39
             ,1998                ,51
             ,1999                ,48
             ,2000                ,45
             ,2001                ,213
             ,2002                ,123
             ,2003                ,501
             ,2004                ,471
             ,2005                ,492
             ,2006                ,207
             ,2007                ,441
             ,2008                ,507
             ,2009                ,768
             ,2010                ,600
             ,2011                ,1047
             ,2012                ,1041
             ,2013                ,1599
             ,2014                ,1818
             ,2015                ,1422
             ,2016                ,1692
             ,2017                ,1794
             ,2018                ,1968
             ,2019                ,1590
             ,2020                ,1035
             ,2021                ,1233
             ,2022                ,828
) %>% 
    ggplot(aes(Completion_Year,n,group=1))+
    geom_line(color="#207977",linetype="dashed")+
    geom_point(color="#207977",size=2)+
    scale_fill_brewer(type = "qual", palette = "Set2")+
    scale_color_brewer(type = "qual", palette = "Set1")+
    theme_minimal(base_size = 12, base_family = 'Source Sans Pro')+
    labs(
    x = element_blank(),
    y = element_blank(),
    title = 'In 2018, the completion of Nga Toi programmes reached its peak',
    subtitle = 'Completion By Reporting Year',
    caption = 'Datasource: Statistic New Zealand Integrated Data Infrastructure'
    )

ggplotly(line_chart)
Figure 1: Completion By Reporting Year

Completion By Gender and Reporting Year

Code
By_Gender <- tribble(~'Completion_Year',    ~'Gender_label',    ~'n'
               ,1996           ,"Female"        ,12
               ,1997           ,"Female"        ,27
               ,1998           ,"Female"        ,33
               ,1999           ,"Female"        ,33
               ,2000           ,"Female"        ,30
               ,2001           ,"Female"        ,123
               ,2002           ,"Female"        ,63
               ,2003           ,"Female"        ,384
               ,2004           ,"Female"        ,369
               ,2005           ,"Female"        ,348
               ,2006           ,"Female"        ,165
               ,2007           ,"Female"        ,324
               ,2008           ,"Female"        ,384
               ,2009           ,"Female"        ,603
               ,2010           ,"Female"        ,450
               ,2011           ,"Female"        ,639
               ,2012           ,"Female"        ,696
               ,2013           ,"Female"        ,1107
               ,2014           ,"Female"        ,1281
               ,2015           ,"Female"        ,1002
               ,2016           ,"Female"        ,1071
               ,2017           ,"Female"        ,1197
               ,2018           ,"Female"        ,1380
               ,2019           ,"Female"        ,1140
               ,2020           ,"Female"        ,765
               ,2021           ,"Female"        ,879
               ,2022           ,"Female"        ,612
               ,1996           ,"Male"          ,0
               ,1997           ,"Male"          ,9
               ,1998           ,"Male"          ,9
               ,1999           ,"Male"          ,15
               ,2000           ,"Male"          ,12
               ,2001           ,"Male"          ,84
               ,2002           ,"Male"          ,57
               ,2003           ,"Male"          ,105
               ,2004           ,"Male"          ,96
               ,2005           ,"Male"          ,126
               ,2006           ,"Male"          ,42
               ,2007           ,"Male"          ,96
               ,2008           ,"Male"          ,117
               ,2009           ,"Male"          ,156
               ,2010           ,"Male"          ,138
               ,2011           ,"Male"          ,393
               ,2012           ,"Male"          ,336
               ,2013           ,"Male"          ,474
               ,2014           ,"Male"          ,516
               ,2015           ,"Male"          ,402
               ,2016           ,"Male"          ,594
               ,2017           ,"Male"          ,576
               ,2018           ,"Male"          ,552
               ,2019           ,"Male"          ,429
               ,2020           ,"Male"          ,258
               ,2021           ,"Male"          ,324
               ,2022           ,"Male"          ,195
) 

By_Gender_Wrangled <- By_Gender%>% 
    group_by(Completion_Year) %>% 
    mutate(Total_Completion = sum(n)) %>% 
    mutate(Percentage = n / Total_Completion) 

By_Gender_Wrangled %>% 
    ggplot(aes(x=Completion_Year))+
    geom_col(aes(y=n,fill=Gender_label))+
    geom_line(data=subset(By_Gender_Wrangled, Gender_label=="Female"),
              aes(y=Percentage*2000,group=Gender_label,color=Gender_label))+
    geom_point(data=subset(By_Gender_Wrangled, Gender_label=="Female"),
              aes(y=Percentage*2000,group=Gender_label,color=Gender_label))+
    scale_fill_brewer(type = "qual", palette = "Set2")+
    scale_color_brewer(type = "qual", palette = "Set1")+
    scale_y_continuous(name = "Total Completion", sec.axis = sec_axis(trans = ~./20, name = "Female (%)", labels = scales::percent_format(scale = 1))) +
    theme_minimal(base_size = 12, base_family = 'Source Sans Pro')+
    theme(legend.position = "top")+
    labs(x=element_blank(),
         y=element_blank(),
         title="Relevant programmes produced a greater number \nof female graduates than male graduates.",
         subtitle = "1995 - 2022",
         fill = "Legend",
         caption = "Datasource: Statistic New Zealand Integrated Data Infrastructure ")+
    labs(color = "Line Legend", fill = "Column Legend")
Figure 2: Completion By Gender and Reporting Year

Completion By Ethnicity and Reporting Year

Code
By_Ethnicity <- tribble(~"Completion_Year", ~"Ethnicity_label",  ~"n"
               ,2001             ,"Asian"         ,0
               ,2002             ,"Asian"         ,9
               ,2004             ,"Asian"         ,0
               ,2006             ,"Asian"         ,0
               ,2007             ,"Asian"         ,15
               ,2008             ,"Asian"         ,0
               ,2009             ,"Asian"         ,0
               ,2010             ,"Asian"         ,0
               ,2012             ,"Asian"         ,0
               ,2013             ,"Asian"         ,0
               ,2014             ,"Asian"         ,27
               ,2015             ,"Asian"         ,9
               ,2016             ,"Asian"         ,0
               ,2017             ,"Asian"         ,27
               ,2018             ,"Asian"         ,36
               ,2019             ,"Asian"         ,27
               ,2020             ,"Asian"         ,9
               ,2021             ,"Asian"         ,45
               ,2022             ,"Asian"         ,21
               ,1997             ,"European"      ,0
               ,1998             ,"European"      ,0
               ,1999             ,"European"      ,0
               ,2000             ,"European"      ,0
               ,2001             ,"European"      ,0
               ,2002             ,"European"      ,15
               ,2003             ,"European"      ,51
               ,2004             ,"European"      ,42
               ,2005             ,"European"      ,30
               ,2006             ,"European"      ,15
               ,2007             ,"European"      ,24
               ,2008             ,"European"      ,57
               ,2009             ,"European"      ,69
               ,2010             ,"European"      ,78
               ,2011             ,"European"      ,72
               ,2012             ,"European"      ,111
               ,2013             ,"European"      ,150
               ,2014             ,"European"      ,204
               ,2015             ,"European"      ,189
               ,2016             ,"European"      ,210
               ,2017             ,"European"      ,234
               ,2018             ,"European"      ,357
               ,2019             ,"European"      ,342
               ,2020             ,"European"      ,240
               ,2021             ,"European"      ,279
               ,2022             ,"European"      ,189
               ,1996             ,"Maori"         ,15
               ,1997             ,"Maori"         ,30
               ,1998             ,"Maori"         ,39
               ,1999             ,"Maori"         ,45
               ,2000             ,"Maori"         ,39
               ,2001             ,"Maori"         ,186
               ,2002             ,"Maori"         ,93
               ,2003             ,"Maori"         ,375
               ,2004             ,"Maori"         ,375
               ,2005             ,"Maori"         ,420
               ,2006             ,"Maori"         ,186
               ,2007             ,"Maori"         ,357
               ,2008             ,"Maori"         ,414
               ,2009             ,"Maori"         ,648
               ,2010             ,"Maori"         ,498
               ,2011             ,"Maori"         ,873
               ,2012             ,"Maori"         ,852
               ,2013             ,"Maori"         ,1368
               ,2014             ,"Maori"         ,1482
               ,2015             ,"Maori"         ,1131
               ,2016             ,"Maori"         ,1335
               ,2017             ,"Maori"         ,1422
               ,2018             ,"Maori"         ,1455
               ,2019             ,"Maori"         ,1119
               ,2020             ,"Maori"         ,702
               ,2021             ,"Maori"         ,825
               ,2022             ,"Maori"         ,570
               ,2009             ,"MELAA"         ,0
               ,2010             ,"MELAA"         ,0
               ,2012             ,"MELAA"         ,0
               ,2013             ,"MELAA"         ,0
               ,2014             ,"MELAA"         ,0
               ,2015             ,"MELAA"         ,0
               ,2016             ,"MELAA"         ,0
               ,2017             ,"MELAA"         ,0
               ,2018             ,"MELAA"         ,6
               ,2019             ,"MELAA"         ,15
               ,2020             ,"MELAA"         ,12
               ,2021             ,"MELAA"         ,12
               ,2022             ,"MELAA"         ,0
               ,1997             ,"Other"         ,0
               ,2001             ,"Other"         ,0
               ,2003             ,"Other"         ,0
               ,2004             ,"Other"         ,0
               ,2006             ,"Other"         ,0
               ,2008             ,"Other"         ,0
               ,2009             ,"Other"         ,0
               ,2011             ,"Other"         ,0
               ,2012             ,"Other"         ,0
               ,2013             ,"Other"         ,0
               ,2014             ,"Other"         ,0
               ,2015             ,"Other"         ,6
               ,2016             ,"Other"         ,0
               ,2017             ,"Other"         ,9
               ,2018             ,"Other"         ,0
               ,2019             ,"Other"         ,12
               ,2020             ,"Other"         ,9
               ,2021             ,"Other"         ,9
               ,2022             ,"Other"         ,12
               ,1998             ,"Pacifica"      ,0
               ,2001             ,"Pacifica"      ,0
               ,2002             ,"Pacifica"      ,0
               ,2003             ,"Pacifica"      ,63
               ,2004             ,"Pacifica"      ,45
               ,2005             ,"Pacifica"      ,27
               ,2006             ,"Pacifica"      ,0
               ,2007             ,"Pacifica"      ,27
               ,2008             ,"Pacifica"      ,24
               ,2009             ,"Pacifica"      ,33
               ,2010             ,"Pacifica"      ,6
               ,2011             ,"Pacifica"      ,84
               ,2012             ,"Pacifica"      ,57
               ,2013             ,"Pacifica"      ,51
               ,2014             ,"Pacifica"      ,69
               ,2015             ,"Pacifica"      ,66
               ,2016             ,"Pacifica"      ,96
               ,2017             ,"Pacifica"      ,72
               ,2018             ,"Pacifica"      ,78
               ,2019             ,"Pacifica"      ,54
               ,2020             ,"Pacifica"      ,48
               ,2021             ,"Pacifica"      ,39
               ,2022             ,"Pacifica"      ,9
)

By_Ethnicity_Wrangled <- By_Ethnicity%>% 
    group_by(Completion_Year) %>% 
    mutate(Total_Completion = sum(n)) %>% 
    mutate(Percentage = n / Total_Completion) 


By_Ethnicity_Wrangled %>% 
    ggplot(aes(x=Completion_Year))+
    geom_col(aes(y=n,fill=Ethnicity_label))+
    geom_line(data=subset(By_Ethnicity_Wrangled, Ethnicity_label=="Maori"),
              aes(y=Percentage*2000,group=Ethnicity_label,color=Ethnicity_label))+
    geom_point(data=subset(By_Ethnicity_Wrangled, Ethnicity_label=="Maori"),
              aes(y=Percentage*2000,group=Ethnicity_label,color=Ethnicity_label))+
    scale_fill_brewer(type = "qual", palette = "Set2")+
    scale_color_brewer(type = "qual", palette = "Set1")+
    scale_y_continuous(name = "Total Completion", sec.axis = sec_axis(trans = ~./20, name = "Maori (%)", labels = scales::percent_format(scale = 1))) +
    theme_minimal(base_size = 12, base_family = 'Source Sans Pro')+
    theme(legend.position = "top")+
    labs(x=element_blank(),
         y=element_blank(),
         title="Relevant programmes produced a greater number \nof Maori graduates than graduates from ethnicity group.",
         subtitle = "1995 - 2022",
         fill = "Legend",
         caption = "Datasource: Statistic New Zealand Integrated Data Infrastructure ")+
    labs(color = "Line Legend", fill = "Column Legend")
Figure 3: Completion By Ethnicity and Reporting Year

Completion By Age Group and Reporting Year

Code
By_Age <- tribble(~'Completion_Year',   ~'Age Group',   ~'n'
               ,1996              ,"15 to 24"        ,0
               ,1997              ,"15 to 24"        ,12
               ,1998              ,"15 to 24"        ,9
               ,1999              ,"15 to 24"        ,12
               ,2000              ,"15 to 24"        ,12
               ,2001              ,"15 to 24"        ,45
               ,2002              ,"15 to 24"        ,39
               ,2003              ,"15 to 24"        ,96
               ,2004              ,"15 to 24"        ,96
               ,2005              ,"15 to 24"        ,138
               ,2006              ,"15 to 24"        ,48
               ,2007              ,"15 to 24"        ,102
               ,2008              ,"15 to 24"        ,141
               ,2009              ,"15 to 24"        ,216
               ,2010              ,"15 to 24"        ,243
               ,2011              ,"15 to 24"        ,480
               ,2012              ,"15 to 24"        ,492
               ,2013              ,"15 to 24"        ,750
               ,2014              ,"15 to 24"        ,828
               ,2015              ,"15 to 24"        ,564
               ,2016              ,"15 to 24"        ,762
               ,2017              ,"15 to 24"        ,834
               ,2018              ,"15 to 24"        ,948
               ,2019              ,"15 to 24"        ,702
               ,2020              ,"15 to 24"        ,495
               ,2021              ,"15 to 24"        ,627
               ,2022              ,"15 to 24"        ,441
               ,1996              ,"25 to 34"        ,9
               ,1997              ,"25 to 34"        ,18
               ,1998              ,"25 to 34"        ,21
               ,1999              ,"25 to 34"        ,30
               ,2000              ,"25 to 34"        ,15
               ,2001              ,"25 to 34"        ,111
               ,2002              ,"25 to 34"        ,57
               ,2003              ,"25 to 34"        ,183
               ,2004              ,"25 to 34"        ,192
               ,2005              ,"25 to 34"        ,210
               ,2006              ,"25 to 34"        ,75
               ,2007              ,"25 to 34"        ,168
               ,2008              ,"25 to 34"        ,213
               ,2009              ,"25 to 34"        ,333
               ,2010              ,"25 to 34"        ,318
               ,2011              ,"25 to 34"        ,594
               ,2012              ,"25 to 34"        ,549
               ,2013              ,"25 to 34"        ,813
               ,2014              ,"25 to 34"        ,1008
               ,2015              ,"25 to 34"        ,750
               ,2016              ,"25 to 34"        ,864
               ,2017              ,"25 to 34"        ,990
               ,2018              ,"25 to 34"        ,987
               ,2019              ,"25 to 34"        ,792
               ,2020              ,"25 to 34"        ,576
               ,2021              ,"25 to 34"        ,645
               ,2022              ,"25 to 34"        ,477
               ,1996              ,"35 to 44"        ,12
               ,1997              ,"35 to 44"        ,30
               ,1998              ,"35 to 44"        ,27
               ,1999              ,"35 to 44"        ,33
               ,2000              ,"35 to 44"        ,24
               ,2001              ,"35 to 44"        ,126
               ,2002              ,"35 to 44"        ,69
               ,2003              ,"35 to 44"        ,255
               ,2004              ,"35 to 44"        ,246
               ,2005              ,"35 to 44"        ,270
               ,2006              ,"35 to 44"        ,108
               ,2007              ,"35 to 44"        ,210
               ,2008              ,"35 to 44"        ,255
               ,2009              ,"35 to 44"        ,390
               ,2010              ,"35 to 44"        ,318
               ,2011              ,"35 to 44"        ,519
               ,2012              ,"35 to 44"        ,468
               ,2013              ,"35 to 44"        ,735
               ,2014              ,"35 to 44"        ,942
               ,2015              ,"35 to 44"        ,777
               ,2016              ,"35 to 44"        ,825
               ,2017              ,"35 to 44"        ,951
               ,2018              ,"35 to 44"        ,987
               ,2019              ,"35 to 44"        ,834
               ,2020              ,"35 to 44"        ,576
               ,2021              ,"35 to 44"        ,603
               ,2022              ,"35 to 44"        ,450
               ,1996              ,"45 to 54"        ,9
               ,1997              ,"45 to 54"        ,24
               ,1998              ,"45 to 54"        ,30
               ,1999              ,"45 to 54"        ,24
               ,2000              ,"45 to 54"        ,21
               ,2001              ,"45 to 54"        ,108
               ,2002              ,"45 to 54"        ,48
               ,2003              ,"45 to 54"        ,225
               ,2004              ,"45 to 54"        ,225
               ,2005              ,"45 to 54"        ,222
               ,2006              ,"45 to 54"        ,108
               ,2007              ,"45 to 54"        ,186
               ,2008              ,"45 to 54"        ,246
               ,2009              ,"45 to 54"        ,384
               ,2010              ,"45 to 54"        ,240
               ,2011              ,"45 to 54"        ,393
               ,2012              ,"45 to 54"        ,372
               ,2013              ,"45 to 54"        ,600
               ,2014              ,"45 to 54"        ,747
               ,2015              ,"45 to 54"        ,669
               ,2016              ,"45 to 54"        ,693
               ,2017              ,"45 to 54"        ,711
               ,2018              ,"45 to 54"        ,777
               ,2019              ,"45 to 54"        ,708
               ,2020              ,"45 to 54"        ,474
               ,2021              ,"45 to 54"        ,480
               ,2022              ,"45 to 54"        ,351
               ,1996              ,"55 to 64"        ,0
               ,1997              ,"55 to 64"        ,12
               ,1998              ,"55 to 64"        ,18
               ,1999              ,"55 to 64"        ,12
               ,2000              ,"55 to 64"        ,18
               ,2001              ,"55 to 64"        ,39
               ,2002              ,"55 to 64"        ,36
               ,2003              ,"55 to 64"        ,171
               ,2004              ,"55 to 64"        ,162
               ,2005              ,"55 to 64"        ,144
               ,2006              ,"55 to 64"        ,90
               ,2007              ,"55 to 64"        ,141
               ,2008              ,"55 to 64"        ,177
               ,2009              ,"55 to 64"        ,270
               ,2010              ,"55 to 64"        ,162
               ,2011              ,"55 to 64"        ,210
               ,2012              ,"55 to 64"        ,246
               ,2013              ,"55 to 64"        ,387
               ,2014              ,"55 to 64"        ,438
               ,2015              ,"55 to 64"        ,408
               ,2016              ,"55 to 64"        ,411
               ,2017              ,"55 to 64"        ,423
               ,2018              ,"55 to 64"        ,492
               ,2019              ,"55 to 64"        ,447
               ,2020              ,"55 to 64"        ,282
               ,2021              ,"55 to 64"        ,273
               ,2022              ,"55 to 64"        ,183
               ,1997              ,"65+"             ,0
               ,1998              ,"65+"             ,9
               ,1999              ,"65+"             ,0
               ,2000              ,"65+"             ,12
               ,2001              ,"65+"             ,0
               ,2002              ,"65+"             ,12
               ,2003              ,"65+"             ,90
               ,2004              ,"65+"             ,81
               ,2005              ,"65+"             ,63
               ,2006              ,"65+"             ,48
               ,2007              ,"65+"             ,81
               ,2008              ,"65+"             ,87
               ,2009              ,"65+"             ,135
               ,2010              ,"65+"             ,78
               ,2011              ,"65+"             ,105
               ,2012              ,"65+"             ,105
               ,2013              ,"65+"             ,156
               ,2014              ,"65+"             ,162
               ,2015              ,"65+"             ,159
               ,2016              ,"65+"             ,147
               ,2017              ,"65+"             ,159
               ,2018              ,"65+"             ,180
               ,2019              ,"65+"             ,195
               ,2020              ,"65+"             ,99
               ,2021              ,"65+"             ,99
               ,2022              ,"65+"             ,57
)

By_Age_Wrangled <- By_Age %>% 
    group_by(Completion_Year) %>% 
    mutate(Total_Completion = sum(n)) %>% 
    mutate(Percentage = n / Total_Completion) 

By_Age_Wrangled %>% 
    group_by(`Age Group`) %>% 
    summarise(Average_Percentage=mean(Percentage))
# A tibble: 6 × 2
  `Age Group` Average_Percentage
  <chr>                    <dbl>
1 15 to 24                0.153 
2 25 to 34                0.220 
3 35 to 44                0.246 
4 45 to 54                0.206 
5 55 to 64                0.124 
6 65+                     0.0531
Code
By_Age_Wrangled %>% 
    ggplot(aes(x=Completion_Year))+
    geom_col(aes(y=n,fill=`Age Group`))+
    geom_line(data=subset(By_Age_Wrangled, `Age Group` %in% c('25 to 34',
                                                              '35 to 44')),
              aes(y=Percentage*10000,group=`Age Group`,color=`Age Group`))+
    geom_point(data=subset(By_Age_Wrangled,`Age Group` %in% c('25 to 34',
                                                              '35 to 44')),
              aes(y=Percentage*10000,group=`Age Group`,color=`Age Group`))+
    scale_fill_brewer(type = "qual", palette = "Set2")+
    scale_color_brewer(type = "qual", palette = "Set1")+
    scale_y_continuous(name = "Total Completion", sec.axis = sec_axis(trans = ~./100, name = "(%)", labels = scales::percent_format(scale = 1))) +
    theme_minimal(base_size = 12, base_family = 'Source Sans Pro')+
    theme(legend.position = "top")+
    labs(x=element_blank(),
         y=element_blank(),
         title="35 to 44 used to be the predominent age group for taking relevant \nprogrammes.However, 25 to 34 surpassed other groups to become \nmain age groups to study relevant programmes",
         subtitle = "1995 - 2022",
         fill = "Legend",
         caption = "Datasource: Statistic New Zealand Integrated Data Infrastructure")+
    labs(color = "Line Legend", fill = "Column Legend")
Figure 4: Completion By Age Group and Reporting Year

Completion By Qualification Level and Reporting Year

Code
By_QualLevel <- tribble(  ~'Completion_Year',     ~'Qual_Level',                 ~'n'
               ,2013          ,"Level 1-3 Certificate"           ,24
               ,2014          ,"Level 1-3 Certificate"           ,0
               ,2015          ,"Level 1-3 Certificate"           ,66
               ,2016          ,"Level 1-3 Certificate"           ,255
               ,2017          ,"Level 1-3 Certificate"           ,186
               ,2018          ,"Level 1-3 Certificate"           ,0
               ,2004          ,"Level 1-3 Certificate"           ,0
               ,2005          ,"Level 1-3 Certificate"           ,0
               ,2006          ,"Level 1-3 Certificate"           ,0
               ,2007          ,"Level 1-3 Certificate"           ,69
               ,2008          ,"Level 1-3 Certificate"           ,30
               ,2009          ,"Level 1-3 Certificate"           ,0
               ,2010          ,"Level 1-3 Certificate"           ,0
               ,2011          ,"Level 1-3 Certificate"           ,525
               ,2012          ,"Level 1-3 Certificate"           ,561
               ,2013          ,"Level 1-3 Certificate"           ,666
               ,2014          ,"Level 1-3 Certificate"           ,1029
               ,2015          ,"Level 1-3 Certificate"           ,849
               ,2016          ,"Level 1-3 Certificate"           ,903
               ,2017          ,"Level 1-3 Certificate"           ,933
               ,2018          ,"Level 1-3 Certificate"           ,1170
               ,2019          ,"Level 1-3 Certificate"           ,0
               ,2020          ,"Level 1-3 Certificate"           ,252
               ,2021          ,"Level 1-3 Certificate"           ,369
               ,2022          ,"Level 1-3 Certificate"           ,0
               ,2003       ,"Level 4-6 Certificate/Diploma"      ,339
               ,2004       ,"Level 4-6 Certificate/Diploma"      ,261
               ,2005       ,"Level 4-6 Certificate/Diploma"      ,288
               ,2006       ,"Level 4-6 Certificate/Diploma"      ,147
               ,2007       ,"Level 4-6 Certificate/Diploma"      ,243
               ,2008       ,"Level 4-6 Certificate/Diploma"      ,330
               ,2009       ,"Level 4-6 Certificate/Diploma"      ,567
               ,2010       ,"Level 4-6 Certificate/Diploma"      ,282
               ,2011       ,"Level 4-6 Certificate/Diploma"      ,264
               ,2012       ,"Level 4-6 Certificate/Diploma"      ,243
               ,2013       ,"Level 4-6 Certificate/Diploma"      ,564
               ,2014       ,"Level 4-6 Certificate/Diploma"      ,363
               ,2015       ,"Level 4-6 Certificate/Diploma"      ,285
               ,2016       ,"Level 4-6 Certificate/Diploma"      ,321
               ,2017       ,"Level 4-6 Certificate/Diploma"      ,447
               ,2018       ,"Level 4-6 Certificate/Diploma"      ,480
               ,2019       ,"Level 4-6 Certificate/Diploma"      ,726
               ,2020       ,"Level 4-6 Certificate/Diploma"      ,525
               ,2021       ,"Level 4-6 Certificate/Diploma"      ,603
               ,2022       ,"Level 4-6 Certificate/Diploma"      ,459
               ,2003       ,"Level 4-6 Certificate/Diploma"      ,189
               ,2004       ,"Level 4-6 Certificate/Diploma"      ,213
               ,2005       ,"Level 4-6 Certificate/Diploma"      ,159
               ,2006       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2007       ,"Level 4-6 Certificate/Diploma"      ,69
               ,2008       ,"Level 4-6 Certificate/Diploma"      ,63
               ,2009       ,"Level 4-6 Certificate/Diploma"      ,72
               ,2010       ,"Level 4-6 Certificate/Diploma"      ,66
               ,2011       ,"Level 4-6 Certificate/Diploma"      ,108
               ,2012       ,"Level 4-6 Certificate/Diploma"      ,60
               ,2013       ,"Level 4-6 Certificate/Diploma"      ,231
               ,2014       ,"Level 4-6 Certificate/Diploma"      ,399
               ,2015       ,"Level 4-6 Certificate/Diploma"      ,204
               ,2016       ,"Level 4-6 Certificate/Diploma"      ,222
               ,2017       ,"Level 4-6 Certificate/Diploma"      ,204
               ,2018       ,"Level 4-6 Certificate/Diploma"      ,210
               ,2019       ,"Level 4-6 Certificate/Diploma"      ,246
               ,2020       ,"Level 4-6 Certificate/Diploma"      ,246
               ,2021       ,"Level 4-6 Certificate/Diploma"      ,273
               ,2022       ,"Level 4-6 Certificate/Diploma"      ,147
               ,2004       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2005       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2006       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2007       ,"Level 4-6 Certificate/Diploma"      ,84
               ,2008       ,"Level 4-6 Certificate/Diploma"      ,87
               ,2009       ,"Level 4-6 Certificate/Diploma"      ,69
               ,2010       ,"Level 4-6 Certificate/Diploma"      ,162
               ,2011       ,"Level 4-6 Certificate/Diploma"      ,165
               ,2012       ,"Level 4-6 Certificate/Diploma"      ,180
               ,2013       ,"Level 4-6 Certificate/Diploma"      ,123
               ,2014       ,"Level 4-6 Certificate/Diploma"      ,18
               ,2015       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2017       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2018       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2019       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2020       ,"Level 4-6 Certificate/Diploma"      ,0
               ,2022       ,"Level 4-6 Certificate/Diploma"      ,0
)

color_palette <- c("#E69F00","#007282")

By_QualLevel %>% 
    group_by(Completion_Year,Qual_Level) %>% 
    summarise(Total_n=sum(n)) %>% 
    ungroup() %>%
    group_by(Completion_Year) %>% 
    mutate(Total_Year=sum(Total_n)) %>% 
    ggplot(aes(x=Completion_Year))+
    geom_col(aes(y=Total_n,fill=Qual_Level),show.legend = TRUE)+
    geom_line(aes(y=Total_Year),color="grey30", linetype = "dashed", linewidth=1)+
    geom_point(aes(y=Total_Year),color="black",size = 1.5, alpha=0.8)+
    scale_fill_manual(values = color_palette)+
    theme_void()+
    theme_minimal(base_size = 12, base_family = 'Source Sans Pro')+
    theme(
        legend.position = 'top',
        strip.text = element_blank(),
        axis.title = element_blank(),
        panel.grid = element_blank()
    )+
    labs(title = "Nga Toi Programme Completion By Reporting Year",
         subtitle = "2003 - 2022",
         color = "Line Legend", fill = "Column Legend")
Figure 5: Completion By Qual Level and Reporting Year

Employment Status By Ethnicity

Code
tribble(~"Ethnicity",           ~"JobStatus",       ~"n"
         ,"African nfd"          ,"Employed"         ,0
         ,"Australian"               ,"Employed"         ,0
         ,"British nfd"          ,"Employed"         ,0
         ,"Cambodian"                ,"Employed"         ,0
         ,"Canadian"                 ,"Employed"         ,0
         ,"Channel Islander"        ,"Employed"      ,0
         ,"Chinese nfd"          ,"Employed"         ,6
         ,"Cook Islands Maori"       ,"Employed"         ,60
         ,"Cornish"              ,"Employed"         ,0
         ,"Dutch"                    ,"Employed"         ,0
         ,"Egyptian"                 ,"Employed"         ,0
         ,"English"              ,"Employed"         ,6
         ,"European nec"             ,"Employed"         ,0
         ,"European nfd"             ,"Employed"         ,0
         ,"Fijian"                   ,"Employed"         ,0
         ,"Filipino"                 ,"Employed"         ,0
         ,"German"                   ,"Employed"         ,0
         ,"Hong Kong Chinese"        ,"Employed"         ,0
         ,"Indian nfd"               ,"Employed"         ,0
         ,"Indigenous American"  ,"Employed"         ,0
         ,"Iranian/Persian"      ,"Employed"         ,0
         ,"Irish"                    ,"Employed"         ,0
         ,"Italian"              ,"Employed"         ,0
         ,"Japanese"                 ,"Employed"         ,0
         ,"Korean"                   ,"Employed"         ,0
         ,"Latin American nfd"       ,"Employed"         ,0
         ,"Māori"                    ,"Employed"         ,1380
         ,"New Zealand European"     ,"Employed"         ,291
         ,"New Zealander"            ,"Employed"         ,9
         ,"Niuean"                   ,"Employed"         ,0
         ,"Other Ethnicity nec"  ,"Employed"         ,0
         ,"Other South African"  ,"Employed"         ,0
         ,"Romanian"                 ,"Employed"         ,0
         ,"Samoan"                   ,"Employed"         ,12
         ,"Sinhalese"                ,"Employed"         ,0
         ,"Slovak"                   ,"Employed"         ,0
         ,"South African European"   ,"Employed"         ,0
         ,"South African Indian"     ,"Employed"         ,0
         ,"Spanish"                  ,"Employed"         ,0
         ,"Tongan"                   ,"Employed"         ,6
         ,"Tuvaluan"                 ,"Employed"         ,0
         ,"African nfd"              ,"Not Employed"     ,0
         ,"American"                 ,"Not Employed"     ,0
         ,"Australian"               ,"Not Employed"     ,0
         ,"Chinese nec"          ,"Not Employed"     ,0
         ,"Chinese nfd"          ,"Not Employed"     ,0
         ,"Cook Islands Maori"   ,"Not Employed"     ,42
         ,"Dutch"                    ,"Not Employed"     ,0
         ,"English"              ,"Not Employed"     ,0
         ,"European nfd"             ,"Not Employed"     ,0
         ,"Fijian"               ,"Not Employed"     ,0
         ,"French"               ,"Not Employed"     ,0
         ,"German"               ,"Not Employed"     ,0
         ,"Indian nfd"           ,"Not Employed"     ,0
         ,"Indigenous American"  ,"Not Employed"     ,0
         ,"Indigenous Australian"    ,"Not Employed"     ,0
         ,"Japanese"                 ,"Not Employed"     ,0
         ,"Latin American nfd"   ,"Not Employed"     ,0
         ,"Māori"                    ,"Not Employed"     ,906
         ,"Moroccan"                 ,"Not Employed"     ,0
         ,"New Zealand European"     ,"Not Employed"     ,165
         ,"New Zealander"            ,"Not Employed"     ,0
         ,"Niuean"               ,"Not Employed"     ,0
         ,"Other Ethnicity nec"  ,"Not Employed"     ,0
         ,"Other South African"  ,"Not Employed"     ,0
         ,"Pacific Peoples nfd"  ,"Not Employed"     ,0
         ,"Russian"              ,"Not Employed"     ,0
         ,"Samoan"               ,"Not Employed"     ,9
         ,"Scottish"                ,"Not Employed"     ,0
         ,"Somali"                 ,"Not Employed"     ,0
         ,"South African European" ,"Not Employed"     ,0
         ,"Swedish"              ,"Not Employed"     ,0
         ,"Taiwanese"                ,"Not Employed"     ,0
         ,"Thai"                     ,"Not Employed"     ,0
         ,"Tokelauan"                ,"Not Employed"     ,0
         ,"Tongan"               ,"Not Employed"     ,6
         ,"Turkish"              ,"Not Employed"     ,0
         ,"Tuvaluan"                 ,"Not Employed"     ,0
         ,"Welsh"                    ,"Not Employed"     ,0
         ,"English"              ,"Not Stated"       ,0
         ,"Filipino"                 ,"Not Stated"       ,0
         ,"Indian nfd"           ,"Not Stated"       ,0
         ,"Māori"                    ,"Not Stated"       ,9
         ,"New Zealand European"     ,"Not Stated"       ,9
         ,"Samoan"               ,"Not Stated"       ,0
         ,"Tuvaluan"                 ,"Not Stated"       ,0
) %>% 
    mutate(Ethnicity_Recode=case_when(Ethnicity == "Māori" ~ "Māori",
                                      Ethnicity %in% c("Fijian",
                                                       "Niuean",
                                                       "Pacific Peoples nfd",
                                                       "Samoan",
                                                       "Tokelauan",
                                                       "Tongan",
                                                       "Tuvaluan") ~ "Pacific People",
                                      TRUE ~ "Others")) %>% 
    group_by(Ethnicity_Recode,JobStatus) %>%
    summarise(Total_Population=sum(n)) %>% 
    ungroup() %>% 
    group_by(Ethnicity_Recode) %>% 
    mutate(Grand_Total=sum(Total_Population)) %>% 
    mutate(Percent = Total_Population/Grand_Total) %>% 
    select(-Grand_Total) %>% 
    ggplot(aes(area=Percent,fill=JobStatus))+
    geom_treemap()+
    geom_treemap_text(aes(label=paste(JobStatus,scales::percent(round(Percent,4)),sep="\n")))+
    scale_fill_brewer(type="qual",palette = "Set2")+
    theme_minimal(base_size = 8,
                  base_family = 'Source Sans Pro')+
    facet_wrap(~Ethnicity_Recode)+
    labs(x=element_blank(),
         y=element_blank(),
         title="It is evident in CENSUS 2018 that Māori and Pacific Nga Toi Graduates' \npost study outcomes were not well, as there were \nsubstantial amounts of graduates unemployed",
         subtitle = "By Ethnicity Regroup",
         caption = "Data source: CENSUS 2018",
         fill = "Legend")+
    theme(legend.position = "none")
Figure 7: Employment Status by Ethnicity

Number Count By Occupation Filed in CENSUS 2018

Code
tribble(~"Occupation",                                                 ~"n"
         ,"Accommodation and Hospitality Managers nec"                  ,6
         ,"Accountant (General)"                                        ,9
         ,"Accounts Clerk"                                              ,9
         ,"Actor"                                                       ,0
         ,"Actors, Dancers and Other Entertainers nec"                  ,0
         ,"Aged or Disabled Carer"                                      ,21
         ,"Agricultural and Horticultural Mobile Plant Operator"        ,0
         ,"Agricultural Consultant"                                     ,0
         ,"Agricultural Technician"                                     ,0
         ,"Aircraft Baggage Handler and Airline Ground Crew"            ,0
         ,"Alarm, Security or Surveillance Monitor"                     ,0
         ,"Ambulance Officer"                                           ,0
         ,"Animal Attendants and Trainers nec"                          ,0
         ,"Apiarist"                                                    ,0
         ,"Apparel Cutter"                                              ,0
         ,"Aquaculture Farmer"                                          ,0
         ,"Arborist"                                                    ,0
         ,"Architect"                                                   ,0
         ,"Archivist"                                                   ,0
         ,"Autoglazier"                                                 ,0
         ,"Baker"                                                       ,0
         ,"Bank Worker"                                                 ,0
         ,"Bar Attendant"                                               ,9
         ,"Barista"                                                     ,6
         ,"Beauty Therapist"                                            ,0
         ,"Beef Cattle Farmer"                                          ,0
         ,"Body Artist"                                                 ,0
         ,"Bricklayer"                                                  ,0
         ,"Builder's Labourer"                                          ,9
         ,"Building and Engineering Technicians nec"                    ,0 
         ,"Building Inspector"                                          ,0
         ,"Bus Driver"                                                  ,9
         ,"Butcher or Smallgoods Maker"                                 ,0
         ,"Cafe or Restaurant Manager"                                  ,0
         ,"Cafe Worker"                                                 ,12
         ,"Call or Contact Centre Operator"                             ,0
         ,"Call or Contact Centre Team Leader"                          ,0
         ,"Camera Operator (Film, Television or Video)"                 ,0
         ,"Caravan Park and Camping Ground Manager"                     ,0
         ,"Cardiac Technician"                                          ,0
         ,"Caretaker"                                                   ,0
         ,"Carpenter"                                                   ,6
         ,"Cash Van Salesperson"                                        ,0
         ,"Cement and Concrete Plant Worker"                            ,0
         ,"Chauffeur"                                                   ,0
         ,"Checkout Operator"                                           ,9
         ,"Chef"                                                        ,9
         ,"Chemical Plant Operator"                                     ,0
         ,"Chemist"                                                     ,0
         ,"Chemistry Technician"                                        ,0
         ,"Chief Executive or Managing Director"                        ,9
         ,"Chief Information Officer"                                   ,0
         ,"Child Care Centre Manager"                                   ,0
         ,"Child Care Worker"                                           ,15
         ,"Child or Youth Residential Care Assistant"                   ,0
         ,"Civil Engineer"                                              ,0
         ,"Clerk of Court"                                              ,0
         ,"Clinical Psychologist"                                       ,0
         ,"Commercial Cleaner"                                          ,72
         ,"Commercial Housekeeper"                                      ,0
         ,"Commissioned Defence Force Officer"                          ,0
         ,"Community Arts Worker"                                       ,0
         ,"Community Worker"                                            ,33
         ,"Complementary Health Therapists nec"                         ,0
         ,"Computer Network and Systems Engineer"                       ,0
         ,"Concrete Products Machine Operator"                          ,0
         ,"Concrete Pump Operator"                                      ,0
         ,"Concreter"                                                   ,0
         ,"Confectionery Maker"                                         ,0
         ,"Conference and Event Organiser"                              ,6
         ,"Construction Project Manager"                                ,0
         ,"Construction Rigger"                                         ,0
         ,"Container Filler"                                            ,24
         ,"Contract Administrator"                                      ,0
         ,"Cook"                                                        ,12
         ,"Corporate General Manager"                                   ,21
         ,"Corporate Services Manager"                                  ,18
         ,"Counsellors nec"                                             ,6
         ,"Courier"                                                     ,0
         ,"Credit or Loans Officer (Aus) / Finance Clerk (NZ)"          ,0
         ,"Crop Farm Workers nec"                                       ,0
         ,"Customer Service Manager"                                    ,6
         ,"Customs Officer"                                             ,0
         ,"Dairy Cattle Farm Worker"                                    ,0
         ,"Dairy Cattle Farmer"                                         ,6
         ,"Dairy Products Maker"                                        ,0
         ,"Dance Teacher (Private Tuition)"                             ,0
         ,"Data Entry Operator"                                         ,0
         ,"Database Administrator"                                      ,0
         ,"Defence Force Member - Other Ranks"                          ,0
         ,"Delivery Driver"                                             ,9
         ,"Dental Assistant"                                            ,0
         ,"Dental Hygienist"                                            ,0
         ,"Dental Therapist"                                            ,0
         ,"Despatching and Receiving Clerk"                             ,0
         ,"Developer Programmer"                                        ,0
         ,"Diesel Motor Mechanic"                                       ,0
         ,"Diversional Therapist"                                       ,0
         ,"Domestic Cleaner"                                            ,0
         ,"Door-to-door Salesperson"                                    ,0
         ,"Drainer / Drainlayer"                                        ,6
         ,"Dressmaker or Tailor"                                        ,0
         ,"Drug and Alcohol Counsellor"                                 ,6
         ,"Early Childhood (Pre-primary School) Teacher"                ,102
         ,"Earthmoving Plant Operator (General)"                        ,0
         ,"Education Adviser"                                           ,18
         ,"Education Managers nec"                                      ,0
         ,"Education Reviewer"                                          ,0
         ,"Electrical Line Mechanic / Electrical Linesworker"           ,0
         ,"Electrician (General)"                                       ,9
         ,"Engineering Production Worker"                               ,6
         ,"Enrolled Nurse"                                              ,0
         ,"Entertainer or Variety Artist"                               ,0
         ,"Environmental Manager"                                       ,0
         ,"Excavator Operator"                                          ,0
         ,"Fabric and Textile Factory Worker"                           ,0
         ,"Facilities Administrator"                                    ,0
         ,"Factory Process Workers nec"                                 ,0
         ,"Family and Marriage Counsellor"                              ,0
         ,"Family Support Worker"                                       ,0
         ,"Fashion Designer"                                            ,0
         ,"Fast Food Cook"                                              ,0
         ,"Fencer"                                                      ,0
         ,"Fibrous Plasterer"                                           ,0
         ,"Finance Manager"                                             ,9
         ,"Financial Investment Adviser"                                ,0
         ,"Financial Investment Manager"                                ,0
         ,"Fire Fighter"                                                ,0
         ,"Fishing Hand"                                                ,0
         ,"Fitness Instructor"                                          ,0
         ,"Fitter (General)"                                            ,0
         ,"Floor Finisher"                                              ,0
         ,"Food and Drink Factory Workers nec"                          ,6
         ,"Forester / Forest Scientist"                                 ,0
         ,"Forestry Worker"                                             ,6
         ,"Forklift Driver"                                             ,0
         ,"Fruit and Vegetable Factory Worker"                          ,0
         ,"Fruit or Nut Farm Worker"                                    ,18
         ,"Fruit or Nut Grower"                                         ,0
         ,"Fruit or Nut Picker"                                         ,0
         ,"Furniture Removalist"                                        ,0
         ,"Gallery or Museum Curator"                                   ,0
         ,"Gallery or Museum Technician"                                ,0
         ,"Garden Labourer"                                             ,0
         ,"Gardener (General)"                                          ,6
         ,"General Clerk"                                               ,39
         ,"General Practitioner"                                        ,0
         ,"Grain, Oilseed or Pasture Grower / Field Crop Grower"        ,0
         ,"Graphic Designer"                                            ,0
         ,"Greenkeeper"                                                 ,0
         ,"Hairdresser"                                                 ,6
         ,"Health Promotion Officer"                                    ,18
         ,"Home Improvement Installer"                                  ,0
         ,"Homoeopath"                                                  ,0
         ,"Horticultural Nursery Assistant"                             ,0
         ,"Hospital Pharmacist"                                         ,0
         ,"Hospitality Workers nec"                                     ,0
         ,"Hotel or Motel Manager"                                      ,0
         ,"Hotel or Motel Receptionist"                                 ,0
         ,"Hotel Service Manager"                                       ,0
         ,"Human Resource Adviser"                                      ,0
         ,"Human Resource Manager"                                      ,0
         ,"ICT Customer Support Officer"                                ,0
         ,"ICT Project Manager"                                         ,0
         ,"ICT Quality Assurance Engineer"                              ,0
         ,"ICT Trainer"                                                 ,0
         ,"Import-Export Clerk"                                         ,0
         ,"Information and Organisation Professionals nec"              ,0
         ,"Inspectors and Regulatory Officers nec"                      ,0
         ,"Insurance Loss Adjuster"                                     ,0
         ,"Interior Decorator"                                          ,0
         ,"Jeweller"                                                    ,0
         ,"Jewellery Designer"                                          ,0
         ,"Joiner"                                                      ,0
         ,"Judicial and Other Legal Professionals nec"                  ,12
         ,"Kaiako Kohanga Reo (Maori Language Nest Teacher)"            ,30
         ,"Kaiako Kura Kaupapa Maori (Maori-medium Primary School Teacher)" ,0
         ,"Kaiawhina (Hauora) (Maori Health Assistant)"                 ,9
         ,"Kaiawhina Kohanga Reo (Maori Language Nest Assistant)"       ,6
         ,"Kaiawhina Kura Kaupapa Maori (Maori-medium School Assistant)"    ,0
         ,"Kitchenhand"                                                 ,15
         ,"Labourers nec"                                               ,51
         ,"Landscape Architect"                                         ,0
         ,"Landscape Gardener"                                          ,0
         ,"Laundry Worker (General)"                                    ,0
         ,"Law Clerk"                                                   ,0
         ,"Legal Executive"                                             ,0
         ,"Legal Secretary"                                             ,0
         ,"Liaison Officer"                                             ,0
         ,"Librarian"                                                   ,9
         ,"Library Assistant"                                           ,0
         ,"Licensed Club Manager"                                       ,0
         ,"Life Science Technician"                                     ,0
         ,"Lifeguard"                                                   ,0
         ,"Livestock Farm Workers nec"                                  ,0
         ,"Loader Operator"                                             ,0
         ,"Local Government Legislator"                                 ,0
         ,"Machine Operators nec"                                       ,12
         ,"Machine Shorthand Reporter"                                  ,0
         ,"Mail Clerk"                                                  ,0
         ,"Management Accountant"                                       ,0
         ,"Management Consultant"                                       ,0
         ,"Manufacturer"                                                ,0
         ,"Market Research Analyst"                                     ,0
         ,"Marketing Specialist"                                        ,6
         ,"Massage Therapist"                                           ,6
         ,"Meat Boner and Slicer"                                       ,0
         ,"Meat Packer"                                                 ,6
         ,"Meat Process Worker"                                         ,12
         ,"Mechanical Engineer"                                         ,0
         ,"Mechanical Engineering Technician"                           ,0
         ,"Medical Administrator / Medical Superintendent"              ,6
         ,"Medical Laboratory Scientist"                                ,0
         ,"Medical Receptionist"                                        ,6
         ,"Medical Technicians nec"                                     ,0
         ,"Metal Fabricator"                                            ,0
         ,"Middle School Teacher / Intermediate School Teacher"         ,0
         ,"Midwife"                                                     ,0
         ,"Mining Support Worker"                                       ,0
         ,"Minister of Religion"                                        ,0
         ,"Mixed Crop and Livestock Farm Worker"                        ,12
         ,"Mixed Crop and Livestock Farmer"                             ,6
         ,"Mixed Livestock Farmer"                                      ,0
         ,"Motor Mechanic (General)"                                    ,0
         ,"Music Teacher (Private Tuition)"                             ,0
         ,"Musician (Instrumental)"                                     ,0
         ,"Nanny"                                                       ,0
         ,"Natural Remedy Consultant"                                   ,0
         ,"Naturopath"                                                  ,0
         ,"Newspaper or Periodical Editor"                              ,0
         ,"Nurse Educator"                                              ,0
         ,"Nurse Manager"                                               ,9
         ,"Nurseryperson"                                               ,0
         ,"Nursing Support Worker"                                      ,0
         ,"Occupational Health and Safety Adviser"                      ,0
         ,"Occupational Therapist"                                      ,0
         ,"Office Cashier"                                              ,0
         ,"Office Manager"                                              ,84
         ,"Optical Mechanic"                                            ,0
         ,"Organisation and Methods Analyst"                            ,0
         ,"Osteopath"                                                   ,0
         ,"Other Sales Support Worker"                                  ,0
         ,"Other Sports Coach or Instructor"                            ,0
         ,"Other Wood Processing Machine Operator"                      ,0
         ,"Out of School Hours Care Worker"                             ,0
         ,"Packers nec"                                                 ,0
         ,"Painter (Visual Arts)"                                       ,0
         ,"Painting Trades Worker"                                      ,0
         ,"Panelbeater"                                                 ,0
         ,"Paper and Pulp Mill Operator"                                ,0
         ,"Paper and Pulp Mill Worker"                                  ,0
         ,"Parking Inspector"                                           ,0
         ,"Parole or Probation Officer"                                 ,6
         ,"Pastrycook"                                                  ,0
         ,"Pastrycook's Assistant"                                      ,0
         ,"Paving and Surfacing Labourer"                               ,0
         ,"Payroll Clerk"                                               ,0
         ,"Personal Assistant"                                          ,21
         ,"Personal Care Assistant"                                     ,60
         ,"Personal Service Workers nec"                                ,0
         ,"Pest Controller"                                             ,0
         ,"Pet Groomer"                                                 ,0
         ,"Pharmacy Sales Assistant"                                    ,0
         ,"Photographer"                                                ,0
         ,"Physiotherapist"                                             ,0
         ,"Plumber (General)"                                           ,0
         ,"Podiatrist"                                                  ,0
         ,"Police Officer"                                              ,9
         ,"Policy Analyst"                                              ,12
         ,"Policy and Planning Manager"                                 ,15
         ,"Postal Sorting Officer"                                      ,0
         ,"Pouako Kura Kaupapa Maori (Maori-medium Primary School Senior Teacher)"  ,0
         ,"Poultry Process Worker"                                      ,0
         ,"Primary School Teacher"                                      ,99
         ,"Print Journalist"                                            ,0
         ,"Printing Machinist"                                          ,0
         ,"Printing Table Worker"                                       ,0
         ,"Prison Officer"                                              ,15
         ,"Product Examiner"                                            ,0
         ,"Product Grader"                                              ,0
         ,"Production Assistant (Film, Television, Radio or Stage)"     ,0
         ,"Production Clerk"                                            ,0
         ,"Production Manager (Manufacturing)"                          ,0
         ,"Program or Project Administrator"                            ,15
         ,"Project Builder"                                             ,12
         ,"Property Manager"                                            ,0
         ,"Psychotherapist"                                             ,0
         ,"Public Relations Manager"                                    ,0
         ,"Public Relations Professional"                               ,0
         ,"Purchasing Officer"                                          ,0
         ,"Quality Assurance Manager"                                   ,0
         ,"Quantity Surveyor"                                           ,0
         ,"Quarantine Officer"                                          ,0
         ,"Radio Despatcher"                                            ,0
         ,"Radio Journalist"                                            ,0
         ,"Radio Presenter"                                             ,0
         ,"Real Estate Representative"                                  ,0
         ,"Receptionist (General)"                                      ,12
         ,"Recruitment Consultant"                                      ,0
         ,"Recycling or Rubbish Collector"                              ,0
         ,"Recycling Worker"                                            ,0
         ,"Regional Education Manager"                                  ,9
         ,"Registered Nurse (Aged Care)"                                ,0
         ,"Registered Nurse (Child and Family Health)"                  ,0
         ,"Registered Nurse (Community Health)"                         ,6
         ,"Registered Nurse (Critical Care and Emergency)"              ,0
         ,"Registered Nurse (Medical Practice)"                         ,0
         ,"Registered Nurse (Medical)"                                  ,0
         ,"Registered Nurse (Mental Health)"                            ,0
         ,"Registered Nurse (Perioperative)"                            ,0
         ,"Registered Nurses nec"                                       ,15
         ,"Religious Assistant"                                         ,0
         ,"Research and Development Manager"                            ,0
         ,"Resident Medical Officer"                                    ,0
         ,"Retail Buyer"                                                ,0
         ,"Retail Loss Prevention Officer"                              ,0
         ,"Retail Manager (General)"                                    ,18
         ,"Retail Supervisor"                                           ,0
         ,"Road Roller Operator"                                        ,0
         ,"Road Traffic Controller"                                     ,0
         ,"Roof Tiler"                                                  ,0
         ,"Safety Inspector"                                            ,0
         ,"Sales and Marketing Manager"                                 ,12
         ,"Sales Assistant (General)"                                   ,66
         ,"Sales Demonstrator"                                          ,0
         ,"Sales Representatives nec"                                   ,33
         ,"Sand Blaster"                                                ,0
         ,"Sawmill or Timber Yard Worker"                               ,0
         ,"Sawmilling Operator"                                         ,0
         ,"Scaffolder"                                                  ,6
         ,"School Principal"                                            ,12
         ,"Science Technicians nec"                                     ,0
         ,"Sculptor"                                                    ,0
         ,"Seafood Process Worker"                                      ,0
         ,"Secondary School Teacher"                                    ,75
         ,"Secretary (General)"                                         ,9
         ,"Security Officer"                                            ,12
         ,"Security Officers and Guards nec"                            ,0
         ,"Senior Non-commissioned Defence Force Member"                ,0
         ,"Service Station Attendant"                                   ,0
         ,"Sewing Machinist"                                            ,0
         ,"Shearer"                                                     ,0
         ,"Sheetmetal Trades Worker"                                    ,0
         ,"Shelf Filler"                                                ,12
         ,"Shot Firer"                                                  ,0
         ,"Singer"                                                      ,0
         ,"Slaughterer"                                                 ,6
         ,"Small Engine Mechanic"                                       ,0
         ,"Social Professionals nec"                                    ,12
         ,"Social Worker"                                               ,54
         ,"Software Engineer"                                           ,10
         ,"Solicitor"                                                   ,0
         ,"Solid Plasterer"                                             ,0
         ,"Special Needs Teacher"                                       ,6
         ,"Specialist Managers nec"                                     ,0
         ,"Sports Administrator"                                        ,0
         ,"Statistical Clerk"                                           ,0
         ,"Steel Fixer"                                                 ,0
         ,"Stock Clerk"                                                 ,0
         ,"Stockbroking Dealer"                                         ,0
         ,"Stonemason"                                                  ,0
         ,"Storeperson"                                                 ,24
         ,"Structural Engineer"                                         ,0
         ,"Student Counsellor"                                          ,0
         ,"Supply and Distribution Manager"                             ,0
         ,"Survey Interviewer"                                          ,0
         ,"Surveyor"                                                    ,0
         ,"Swimming Coach or Instructor"                                ,0
         ,"Systems Administrator"                                       ,0
         ,"Systems Analyst"                                             ,0
         ,"Tanker Driver"                                               ,0
         ,"Teacher of the Hearing Impaired"                             ,0
         ,"Teachers' Aide"                                              ,54
         ,"Technical Sales Representatives nec"                         ,0
         ,"Technical Writer"                                            ,0
         ,"Technicians and Trades Workers nec"                          ,0
         ,"Telecommunications Network Engineer"                         ,0
         ,"Telemarketer"                                                ,0
         ,"Television Journalist"                                       ,0
         ,"Ticket Seller"                                               ,0
         ,"Tour Guide"                                                  ,0
         ,"Traditional Maori Health Practitioner"                       ,0
         ,"Training and Development Professional"                       ,0
         ,"Transport Company Manager"                                   ,0
         ,"Transport Engineer"                                          ,0
         ,"Travel Consultant"                                           ,0
         ,"Tree Faller"                                                 ,0
         ,"Truck Driver (General)"                                      ,21
         ,"University Lecturer"                                         ,36
         ,"University Tutor"                                            ,30
         ,"Urban and Regional Planner"                                  ,0
         ,"Valuer"                                                      ,0
         ,"Vegetable Farm Worker (Aus) / Market Garden Worker (NZ)"     ,0
         ,"Vegetable Picker"                                            ,0
         ,"Vehicle Painter"                                             ,0
         ,"Veterinarian"                                                ,0
         ,"Visual Arts and Crafts Professionals nec"                    ,6
         ,"Vocational Education Teacher / Polytechnic Teacher"          ,15
         ,"Waiter"                                                      ,15
         ,"Warehouse Administrator"                                     ,0
         ,"Waterside Worker"                                            ,0
         ,"Weaving Machine Operator"                                    ,0
         ,"Web Developer"                                               ,0
         ,"Weighbridge Operator"                                        ,0
         ,"Welder (First Class) (Aus) / Welder (NZ)"                    ,0
         ,"Welfare Worker"                                              ,27
         ,"Whitewater Rafting Guide"                                    ,0
         ,"Window Cleaner"                                              ,0
         ,"Wine Maker"                                                  ,0
         ,"Wood and Wood Products Factory Worker"                       ,0
         ,"Wood Turner"                                                 ,0
         ,"Wool Handler"                                                ,0
         ,"Word Processing Operator"                                    ,0
         ,"Youth Worker"                                                ,15
) %>% 
    filter(n!=0) %>% 
    top_n(20,n) %>% 
    ggplot(aes(reorder(Occupation,n),n))+
    geom_col(fill="#207977")+
    geom_label(mapping = aes(label = n))+
    coord_flip()+
    theme_minimal(base_size = 8,
                  base_family = 'Source Sans Pro')+
    labs(x=element_blank(),
         y=element_blank(),
         title="It is evident in CENSUS 2018 that professionals tend to take relevant Nga Toi programmes as an upskilling opportunity.",
         subtitle = "By Occupation",
         caption = "Data source: CENSUS 2018")
Figure 8: Number Count by Occupation

Proportion of Confirmed Individuals by Industry

Code
tribble(~'Industry',    ~'n'
,'Accommodation'    ,27
,'Accounting Services'  ,0
,'Adult, Community and Other Education n.e.c.'  ,36
,'Advertising Services' ,0
,'Aged Care Residential Services'   ,24
,'Air and Space Transport'  ,0
,'Air Conditioning and Heating Services'    ,0
,'Aircraft Manufacturing and Repair Services'   ,0
,'Airport Operations and Other Air Transport Support Services'  ,0
,'Aluminium Rolling, Drawing, Extruding'    ,0
,'Aluminium Smelting'   ,0
,'Ambulance Services'   ,0
,'Amusement and Other Recreation Activities n.e.c.' ,0
,'Amusement Parks and Centres Operation'    ,0
,'Antique and Used Goods Retailing' ,0
,'Apple and Pear Growing'   ,15
,'Architectural Aluminium Product Manufacturing'    ,0
,'Architectural Services'   ,0
,'Arts Education'   ,0
,'Auxiliary Insurance Services' ,0
,'Bakery Product Manufacturing (Non-factory based)' ,0
,'Banking'  ,9
,'Beef Cattle Farming (Specialised)'    ,0
,'Beekeeping'   ,0
,'Berry Fruit Growing'  ,0
,'Biscuit Manufacturing (Factory based)'    ,0
,'Boiler, Tank and Other Heavy Gauge Metal Container Manufacturing' ,0
,'Book and Magazine Wholesaling'    ,0
,'Bricklaying Services' ,0
,'Brothel Keeping and Prostitution Services'    ,0
,'Building and Other Industrial Cleaning Services'  ,36
,'Building Pest Control Services'   ,0
,'Business and Professional Association Services'   ,0
,'Cafes and Restaurants'    ,39
,'Cake and Pastry Manufacturing (Factory based)'    ,0
,'Call Centre Operation'    ,0
,'Car Wholesaling'  ,0
,'Casino Operation' ,0
,'Catering Services'    ,9
,'Central Banking'  ,0
,'Central Government Administration'    ,96
,'Cereal Grain Wholesaling' ,0
,'Cheese and Other Dairy Product Manufacturing' ,0
,'Child Care Services'  ,42
,'Chiropractic and Osteopathic Services'    ,0
,'Citrus Fruit Growing' ,0
,'Clothing and Footwear Wholesaling'    ,0
,'Clothing Manufacturing'   ,0
,'Clothing Retailing'   ,9
,'Clubs (Hospitality)'  ,6
,'Combined Primary and Secondary Education' ,27
,'Commission-Based Wholesaling' ,0
,'Computer System Design and Related Services'  ,6
,'Concrete Product Manufacturing'   ,0
,'Concreting Services'  ,0
,'Confectionery Manufacturing'  ,0
,'Corporate Head Office Management Services'    ,75
,'Correctional and Detention Services'  ,48
,'Corrugated Paperboard and Paperboard Container Manufacturing' ,0
,'Courier Pick-up and Delivery Services'    ,0
,'Creative Artists, Musicians, Writers and Performers'  ,9
,'Cured Meat and Smallgoods Manufacturing'  ,0
,'Customs Agency Services'  ,0
,'Cut and Sewn Textile Product Manufacturing'   ,0
,'Dairy Cattle Farming' ,15
,'Dairy Produce Wholesaling'    ,0
,'Defence'  ,6
,'Dental Services'  ,6
,'Department Stores'    ,9
,'Document Preparation Services'    ,0
,'Domestic Appliance Repair and Maintenance'    ,0
,'Educational Support Services' ,0
,'Electrical Services'  ,6
,'Electrical, Electronic and Gas Appliance Retailing'   ,0
,'Electricity Distribution' ,0
,'Electricity Transmission' ,0
,'Electronic Information Storage Services'  ,0
,'Employment Placement and Recruitment Services'    ,12
,'Engineering Design and Engineering Consulting Services'   ,0
,'Financial Asset Investing'    ,6
,'Fire and Security Alarm Installation Services'    ,0
,'Fire Protection and Other Emergency Services' ,0
,'Floor Coverings Retailing'    ,0
,'Footwear Retailing'   ,0
,'Forestry' ,0
,'Forestry Support Services'    ,0
,'Fossil Fuel Electricity Generation'   ,0
,'Free-to-Air Television Broadcasting'  ,0
,'Freight Forwarding Services'  ,0
,'Fresh Meat, Fish and Poultry Retailing'   ,0
,'Fruit and Vegetable Processing'   ,6
,'Fruit and Vegetable Retailing'    ,0
,'Fruit and Vegetable Wholesaling'  ,0
,'Fuel Retailing'   ,12
,'Furniture Retailing'  ,0
,'Garden Supplies Retailing'    ,0
,'Gardening Services'   ,12
,'General Insurance'    ,0
,'General Line Grocery Wholesaling' ,6
,'General Practice Medical Services'    ,9
,'Grape Growing'    ,0
,'Hairdressing and Beauty Services' ,9
,'Hardware and Building Supplies Retailing' ,9
,'Health and Fitness Centres and Gymnasia Operation'    ,0
,'Health Insurance' ,0
,'Heavy Machinery and Scaffolding Rental and Hiring'    ,0
,'Higher Education' ,105
,'Horse Farming'    ,0
,'Hospitals (Except Psychiatric Hospitals)' ,51
,'House Construction'   ,15
,'Industrial and Agricultural Chemical Product Wholesaling' ,0
,'Interurban and Rural Bus Transport'   ,0
,'Investigation and Security Services'  ,12
,'Iron and Steel Casting'   ,0
,'Iron Smelting and Steel Manufacturing'    ,0
,'Jewellery and Silverware Manufacturing'   ,0
,'Justice'  ,9
,'Kiwifruit Growing'    ,6
,'Labour Association Services'  ,0
,'Labour Supply Services'   ,27
,'Land Development and Subdivision' ,0
,'Landscape Construction Services'  ,6
,'Laundry and Dry-Cleaning Services'    ,0
,'Legal Services'   ,12
,'Libraries and Archives'   ,0
,'Liquor and Tobacco Product Wholesaling'   ,0
,'Liquor Retailing' ,0
,'Local Government Administration'  ,33
,'Log Sawmilling'   ,9
,'Logging'  ,0
,'Management Advice and Related Consulting Services'    ,24
,'Manchester and Other Textile Goods Retailing' ,0
,'Marine Equipment Retailing'   ,0
,'Market Research and Statistical Services' ,0
,'Meat Processing'  ,36
,'Medical and Surgical Equipment Manufacturing' ,0
,'Metal and Mineral Wholesaling'    ,0
,'Metal Coating and Finishing'  ,0
,'Milk and Cream Processing'    ,0
,'Motion Picture and Video Production'  ,0
,'Motor Cycle Retailing'    ,0
,'Motor Vehicle Body and Trailer Manufacturing' ,0
,'Motor Vehicle New Parts Wholesaling'  ,0
,'Museum Operation' ,15
,'Natural Textile Manufacturing'    ,0
,'Nature Reserves and Conservation Parks Operation' ,0
,'Newspaper and Book Retailing' ,0
,'Newspaper Publishing' ,0
,'Non-Depository Financing' ,0
,'Non-Financial Intangible Assets (Except Copyrights) Leasing'  ,0
,'Non-Residential Building Construction'    ,6
,'Non-Residential Property Operators'   ,0
,'Non-Store Retailing'  ,0
,'Nursery Production (Outdoors)'    ,0
,'Nursery Production (Under Cover)' ,0
,'Office Administrative Services'   ,18
,'Oil and Fat Manufacturing'    ,0
,'Oil and Gas Extraction'   ,0
,'Optometry and Optical Dispensing' ,0
,'Other Administrative Services n.e.c.' ,12
,'Other Agricultural Product Wholesaling'   ,0
,'Other Agriculture and Fishing Support Services'   ,12
,'Other Allied Health Services' ,108
,'Other Automotive Repair and Maintenance'  ,9
,'Other Auxiliary Finance and Investment Services'  ,0
,'Other Building Installation Services' ,0
,'Other Ceramic Product Manufacturing'  ,0
,'Other Construction Material Mining'   ,0
,'Other Construction Services n.e.c.'   ,12
,'Other Crop Growing n.e.c.'    ,0
,'Other Electrical Equipment Manufacturing' ,0
,'Other Fabricated Metal Product Manufacturing n.e.c.'  ,0
,'Other Food Product Manufacturing n.e.c.'  ,0
,'Other Fruit and Tree Nut Growing' ,0
,'Other Gambling Activities'    ,0
,'Other Goods and Equipment Rental and Hiring n.e.c.'   ,0
,'Other Goods Wholesaling n.e.c.'   ,0
,'Other Grocery Wholesaling'    ,0
,'Other Hardware Goods Wholesaling' ,0
,'Other Health Care Services n.e.c.'    ,27
,'Other Heavy and Civil Engineering Construction'   ,9
,'Other Interest Group Services n.e.c.' ,48
,'Other Livestock Farming n.e.c.'   ,0
,'Other Machinery and Equipment Manufacturing n.e.c.'   ,6
,'Other Manufacturing n.e.c.'   ,0
,'Other Motor Vehicle and Transport Equipment Rental and Hiring'    ,0
,'Other Motor Vehicle Parts Manufacturing'  ,0
,'Other Personal Accessory Retailing'   ,0
,'Other Personal Services n.e.c.'   ,0
,'Other Polymer Product Manufacturing'  ,0
,'Other Professional, Scientific and Technical Services n.e.c.' ,0
,'Other Public Order and Safety Services'   ,0
,'Other Repair and Maintenance n.e.c.'  ,0
,'Other Residential Building Construction'  ,0
,'Other Residential Care Services'  ,21
,'Other Social Assistance Services' ,60
,'Other Specialised Design Services'    ,0
,'Other Specialised Food Retailing' ,0
,'Other Specialised Industrial Machinery and Equipment Wholesaling' ,0
,'Other Store-Based Retailing n.e.c.'   ,21
,'Other Transport Support Services n.e.c.'  ,0
,'Other Warehousing and Storage Services'   ,0
,'Other Wood Product Manufacturing n.e.c.'  ,0
,'Packaging Services'   ,18
,'Paint and Coatings Manufacturing' ,0
,'Painting and Decorating Services' ,6
,'Parking Services' ,0
,'Passenger Car Rental and Hiring'  ,0
,'Pathology and Diagnostic Imaging Services'    ,0
,'Performing Arts Operation'    ,0
,'Performing Arts Venue Operation'  ,0
,'Petroleum Product Wholesaling'    ,0
,'Pharmaceutical and Toiletry Goods Wholesaling'    ,0
,'Pharmaceutical, Cosmetic and Toiletry Goods Retailing'    ,0
,'Physiotherapy Services'   ,0
,'Plastering and Ceiling Services'  ,0
,'Plumbing Services'    ,0
,'Police Services'  ,0
,'Polymer Film and Sheet Packaging Material Manufacturing'  ,0
,'Port and Water Transport Terminal Operations' ,0
,'Postal Services'  ,6
,'Post-production Services and Other Motion Picture and Video Activities'   ,0
,'Poultry Farming (Eggs)'   ,0
,'Poultry Farming (Meat)'   ,0
,'Poultry Processing'   ,0
,'Preschool Education'  ,147
,'Primary Education'    ,150
,'Printing' ,0
,'Psychiatric Hospitals'    ,0
,'Pubs, Taverns and Bars'   ,6
,'Pulp, Paper and Paperboard Manufacturing' ,6
,'Radio Broadcasting'   ,0
,'Rail Freight Transport'   ,0
,'Rail Passenger Transport' ,0
,'Real Estate Services' ,9
,'Reconstituted Wood Product Manufacturing' ,0
,'Regulatory Services'  ,0
,'Religious Services'   ,0
,'Rigid and Semi-Rigid Polymer Product Manufacturing'   ,0
,'Road and Bridge Construction' ,9
,'Road Freight Transport'   ,21
,'Roofing Services' ,0
,'Scientific Research Services' ,0
,'Scientific Testing and Analysis Services' ,0
,'Seafood Processing'   ,6
,'Secondary Education'  ,90
,'Sewerage and Drainage Services'   ,0
,'Shearing Services'    ,9
,'Sheep Farming (Specialised)'  ,0
,'Sheep-Beef Cattle Farming'    ,6
,'Site Preparation Services'    ,6
,'Special School Education' ,0
,'Specialist Medical Services'  ,0
,'Sport and Camping Equipment Retailing'    ,0
,'Sports and Physical Recreation Administrative Service'    ,0
,'Sports and Physical Recreation Clubs and Sports Professionals'    ,0
,'Sports and Physical Recreation Instruction'   ,0
,'Sports and Physical Recreation Venues, Grounds and Facilities Operation'  ,9
,'Stevedoring Services' ,0
,'Structural Steel Erection Services'   ,0
,'Structural Steel Fabricating' ,0
,'Supermarket and Grocery Stores'   ,33
,'Surveying and Mapping Services'   ,0
,'Takeaway Food Services'   ,18
,'Taxi and Other Road Transport'    ,0
,'Technical and Vocational Education and Training'  ,27
,'Tiling and Carpeting Services'    ,0
,'Timber Resawing and Dressing' ,0
,'Timber Wholesaling'   ,0
,'Toy and Sporting Goods Wholesaling'   ,0
,'Toy, Sporting and Recreational Product Manufacturing' ,0
,'Travel Agency and Tour Arrangement Services'  ,12
,'Tyre Retailing'   ,0
,'Urban Bus Transport (Including Tramway)'  ,6
,'Vegetable Growing (Outdoors)' ,0
,'Veneer and Plywood Manufacturing' ,0
,'Veterinary Services'  ,0
,'Waste Remediation and Materials Recovery Services'    ,0
,'Waste Treatment and Disposal Services'    ,0
,'Watch and Jewellery Retailing'    ,0
,'Wired Telecommunications Network Operation'   ,0
,'Wooden Furniture and Upholstered Seat Manufacturing'  ,0
,'Wooden Structural Fitting and Component Manufacturing'    ,0
,'Zoological and Botanical Gardens Operation'   ,0
) %>% 
    mutate(Total_Number=sum(n)) %>% 
    mutate(Percent = n/Total_Number) %>% 
    select(-Total_Number) %>%
    ggplot(aes(area=Percent,fill=Industry))+
    geom_treemap()+
    geom_treemap_text(aes(label=paste(Industry,scales::percent(round(Percent,4)),sep="\n")))+
    tidyquant::scale_fill_tq()+
    theme_minimal(base_size = 8,
                  base_family = 'Source Sans Pro')+
    labs(x=element_blank(),
         y=element_blank(),
         title="From the industry perspective, it is evident that professionals \nfrom education industry were more likely to \ntake relevant programmes as an upskilling opportunity",
         subtitle = "By Industry",
         caption = "Data source: CENSUS 2018",
         fill = "Legend")+
    theme(legend.position = "none")
Figure 9: Proportion of Confirmed Individuals by Industry
Code
tribble(~"Income_Band",         ~"n"
         ,"$1-$5,000"           ,114
         ,"$10,001-$15,000"     ,156
         ,"$100,001-$150,000"   ,36
         ,"$15,001-$20,000"     ,201
         ,"$150,001 or More"    ,15
         ,"$20,001-$25,000"     ,189
         ,"$25,001-$30,000"     ,186
         ,"$30,001-$35,000"     ,150
         ,"$35,001-$40,000"     ,183
         ,"$40,001-$50,000"     ,312
         ,"$5,001-$10,000"      ,108
         ,"$50,001-$60,000"     ,273
         ,"$60,001-$70,000"     ,189
         ,"$70,001-$100,000"    ,267
         ,"Loss"                ,6
         ,"Zero income"         ,15
) %>% 
    mutate(Income_Band = factor(Income_Band, levels = c("$150,001 or More",
                                                        "$100,001-$150,000",
                                                        "$70,001-$100,000",
                                                        "$60,001-$70,000",
                                                        "$50,001-$60,000",
                                                        "$40,001-$50,000",
                                                        "$35,001-$40,000",
                                                        "$30,001-$35,000",
                                                        "$25,001-$30,000",
                                                        "$20,001-$25,000",
                                                        "$15,001-$20,000",
                                                        "$10,001-$15,000",
                                                        "$5,001-$10,000",
                                                        "$1-$5,000",
                                                        "Zero income",
                                                        "Loss"))) %>% 
    mutate(Total_Count = sum(n)) %>% 
    mutate(Percent = n/Total_Count) %>% 
    ggplot(aes(area=Percent,fill=Income_Band))+
    geom_treemap()+
    geom_treemap_text(aes(label=paste(Income_Band,scales::percent(round(Percent,4)),sep="\n")))+
    tidyquant::scale_fill_tq()+
    theme_minimal(base_size = 8,
                  base_family = 'Source Sans Pro')+
    labs(x=element_blank(),
         y=element_blank(),
         title="A significant proportion of graduates come from low-income backgrounds",
         subtitle = "By Income Band",
         caption = "Data source: CENSUS 2018",
         fill = "Legend")+
    theme(legend.position = "right")
Figure 10: Proportion of Confirmed Individuals by Industry

Proportion of Confirmed Individuals by Job Status

Code
tribble(~"JobStatus",   ~"n"
        ,"Employed"    ,2406
      ,"Not Employed"  ,1518
      ,"Not Stated"    ,36
) %>% 
    mutate(Total_Count=sum(n)) %>% 
    mutate(Percent = n/Total_Count) %>% 
    ggplot(aes(area=Percent,fill=JobStatus))+
    geom_treemap()+
    geom_treemap_text(aes(label=paste(JobStatus,scales::percent(round(Percent,4)),sep="\n")))+
    tidyquant::scale_fill_tq()+
    theme_minimal(base_size = 8,
                  base_family = 'Source Sans Pro')+
    labs(x=element_blank(),
         y=element_blank(),
         title="A significant proportion of graduates were not employed in CENSUS 2018",
         subtitle = "By Job Status",
         caption = "Data source: CENSUS 2018",
         fill = "Legend")+
    theme(legend.position = "top")
Figure 11: Proportion of Confirmed Individuals by Job Status

Proportion of UpSkilling Graduates by NZSCED

Code
tribble(~'Enrol_Year',  ~'NZSCED_Name', ~'n'
,2017   ,'Employment Skills Programmes not elsewhere classified'    ,12
,2017   ,'Graphic Arts and Design Studies'  ,0
,2017   ,'General Education Programmes not elsewhere classified'    ,12
,2018   ,'Hospitality'  ,0
,2016   ,'Performing Arts not elsewhere classified' ,0
,2017   ,'Social Skills Programmes not elsewhere classified'    ,42
,2017   ,'Learning Skills Programmes'   ,15
,2018   ,'Hairdressing' ,0
,2017   ,'Audio Visual Studies' ,0
,2018   ,'Literacy and Numeracy Programmes' ,0
,2018   ,'Creative Arts not elsewhere classified'   ,42
,2018   ,'Social Skills Programmes not elsewhere classified'    ,45
,2018   ,'Journalism, Communication and Media Studies'  ,0
,2017   ,'Mixed Field Programmes not elsewhere classified'  ,0
,2018   ,'Job Search Skills Programmes' ,0
,2016   ,'Mana Whakairo (Māori Carving)'    ,0
,2017   ,'Creative Arts not elsewhere classified'   ,90
,2018   ,'Career Development Programmes'    ,0
,2018   ,'Beauty Therapy'   ,0
,2017   ,'Visual Arts and Crafts not elsewhere classified'  ,0
,2016   ,'Learning Skills Programmes'   ,9
,2018   ,'Employment Skills Programmes not elsewhere classified'    ,12
,2016   ,'Life Skills'  ,0
,2016   ,'General Primary and Secondary Education'  ,0
,2017   ,'Fine Arts'    ,48
,2016   ,'Beauty Therapy'   ,0
,2018   ,'Performing Arts not elsewhere classified' ,0
,2017   ,'Mana Whakairo (Māori Carving)'    ,0
,2016   ,'Fine Arts'    ,60
,2016   ,'Social Skills Programmes not elsewhere classified'    ,21
,2018   ,'Food and Beverage Service'    ,0
,2016   ,'Fashion Design'   ,0
,2018   ,'Graphic Arts and Design Studies'  ,21
,2016   ,'Cookery'  ,0
,2018   ,'Social and Interpersonal Skills Programmes'   ,0
,2016   ,'Ngā Mahi a Rēhia (Māori Performing Arts)' ,45
,2018   ,'Mana Whakairo (Māori Carving)'    ,0
,2016   ,'Communication and Media Studies not elsewhere classified' ,0
,2018   ,'Mixed Field Programmes not elsewhere classified'  ,12
,2017   ,'Food and Beverage Service'    ,0
,2016   ,'Baking and Pastry Making' ,0
,2016   ,'Employment Skills Programmes not elsewhere classified'    ,18
,2018   ,'Fashion Design'   ,0
,2016   ,'General Education Programmes not elsewhere classified'    ,0
,2017   ,'General Primary and Secondary Education'  ,0
,2018   ,'Visual Arts and Crafts not elsewhere classified'  ,0
,2018   ,'Learning Skills Programmes'   ,0
,2018   ,'Dance'    ,0
,2017   ,'Ngā Mahi a Rēhia (Māori Performing Arts)' ,39
,2016   ,'Food and Beverage Service'    ,6
,2017   ,'Hairdressing' ,0
,2016   ,'Food Hygiene' ,0
,2016   ,'Hospitality'  ,0
,2016   ,'Graphic Arts and Design Studies'  ,18
,2018   ,'Cookery'  ,0
,2017   ,'Music'    ,0
,2016   ,'Food and Hospitality not elsewhere classified'    ,0
,2017   ,'Beauty Therapy'   ,0
,2016   ,'Creative Arts not elsewhere classified'   ,15
,2018   ,'Ngā Mahi a Rēhia (Māori Performing Arts)' ,63
,2016   ,'Mixed Field Programmes not elsewhere classified'  ,6
,2018   ,'General Education Programmes not elsewhere classified'    ,33
,2018   ,'Fine Arts'    ,48
,2017   ,'Cookery'  ,0
,2016   ,'Visual Arts and Crafts not elsewhere classified'  ,0
) %>% 
    filter(n!=0) %>% 
    group_by(Enrol_Year) %>% 
    mutate(Total_Number = sum(n)) %>% 
    mutate(Percent = n/Total_Number) %>% 
    ggplot(aes(Enrol_Year,Percent,fill=NZSCED_Name))+
    geom_col()+
    tidyquant::scale_fill_tq()+
    geom_label(mapping = aes(label = scales::percent(round(Percent,3))),position = position_stack(vjust = 0.2))+
    scale_y_continuous(labels = scales::percent_format())+
    theme_minimal(base_size = 8,
                  base_family = 'Source Sans Pro')+
    labs(x=element_blank(),
         y=element_blank(),
         title="It is evident that those graduates chose to stay \nwithin the teritary education system \nwould continue their journeys in Toi",
         subtitle = "By NZSCED",
         caption = "Data source: Statistic New Zealand Integrated Data Infrastructure ",
         fill = "Legend")+
    theme(legend.position = "right")
Figure 12: Proportion of UpSkilling Graduates by NZSCED