1. Introduction to topChef

In the works:

Difference between 0.2.0 and upcoming 0.2.1:

Difference between version 0.1.0 and 0.2.0:

2. Installation

install.packages("topChef")

devtools::install_github("celevitz/topChef")

3. Acknowledgments and Inspiration

4. Overview of datasets

4.a. Datasets

4.a.i. Chef details

chefdetails#> # A tibble: 432 × 14#>    name    chef  hometown city  state   age season seasonNumber series placement#>    <chr>   <chr> <chr>    <chr> <chr> <dbl> <chr>         <dbl> <chr>      <dbl>#>  1 Ross L… Ross… <NA>     St. … Newf…    31 Canad…            6 Canada         1#>  2 Mark S… Mark… <NA>     Vanc… Brit…    29 Canad…            6 Canada         2#>  3 Jinhee… Jinh… <NA>     Calg… Albe…    38 Canad…            6 Canada         3#>  4 JP Mir… JP M. <NA>     Mont… Queb…    30 Canad…            6 Canada         3#>  5 Nathan… Nath… <NA>     Sask… Sask…    35 Canad…            6 Canada         5#>  6 Darren… Darr… <NA>     Mont… Queb…    27 Canad…            6 Canada         6#>  7 Jesse … Jess… <NA>     Sask… Sask…    29 Canad…            6 Canada         7#>  8 Matt S… Matt… <NA>     Toro… Onta…    34 Canad…            6 Canada         7#>  9 Elia H… Elia… <NA>     Toro… Onta…    37 Canad…            6 Canada         9#> 10 Ivana … Ivan… <NA>     Toro… Onta…    33 Canad…            6 Canada        10#> # ℹ 422 more rows#> # ℹ 4 more variables: personOfColor <chr>, occupation <chr>, gender <chr>,#> #   occupation_category <chr>

4.a.ii. Challenge descriptions

challengedescriptions#> # A tibble: 666 × 17#>    season   seasonNumber series episode challengeType outcomeType#>    <chr>           <dbl> <chr>    <dbl> <chr>         <chr>#>  1 Kentucky           16 US           1 Quickfire     Team#>  2 Kentucky           16 US           1 Elimination   Team#>  3 Kentucky           16 US           2 Quickfire     Individual#>  4 Kentucky           16 US           2 Elimination   Team#>  5 Kentucky           16 US           3 Quickfire     Individual#>  6 Kentucky           16 US           3 Elimination   Individual#>  7 Kentucky           16 US           4 Quickfire     Individual#>  8 Kentucky           16 US           4 Elimination   Team#>  9 Kentucky           16 US           5 Elimination   Team#> 10 Kentucky           16 US           6 Elimination   Individual#> # ℹ 656 more rows#> # ℹ 11 more variables: challengeDescription <chr>, shopTime <chr>,#> #   shopBudget <chr>, prepTime <dbl>, cookTime <dbl>, productPlacement <chr>,#> #   advantage <chr>, lastChanceKitchenWinnerEnters <chr>,#> #   restaurantWarWinner <chr>, restaurantWarEliminated <chr>,#> #   didJudgesVisitWinningTeamFirst <chr>

4.a.iii. Challenge wins

challengewins#> # A tibble: 10,053 × 10#>    season   seasonNumber series episode inCompetition immune chef  challengeType#>    <chr>           <dbl> <chr>    <dbl> <lgl>         <lgl>  <chr> <chr>#>  1 All Sta…            8 US           1 TRUE          FALSE  Ange… Quickfire#>  2 All Sta…            8 US           1 TRUE          FALSE  Anto… Quickfire#>  3 All Sta…            8 US           1 TRUE          FALSE  Carl… Quickfire#>  4 All Sta…            8 US           1 TRUE          FALSE  Case… Quickfire#>  5 All Sta…            8 US           1 TRUE          FALSE  Dale… Quickfire#>  6 All Sta…            8 US           1 TRUE          FALSE  Dale… Quickfire#>  7 All Sta…            8 US           1 TRUE          FALSE  Elia… Quickfire#>  8 All Sta…            8 US           1 TRUE          FALSE  Fabi… Quickfire#>  9 All Sta…            8 US           1 TRUE          FALSE  Jami… Quickfire#> 10 All Sta…            8 US           1 TRUE          FALSE  Jenn… Quickfire#> # ℹ 10,043 more rows#> # ℹ 2 more variables: outcome <chr>, rating <dbl>

4.a.iv. Judges

judges#> # A tibble: 784 × 11#>    season   seasonNumber series episode challengeType outcomeType guestJudge#>    <chr>           <dbl> <chr>    <dbl> <chr>         <chr>       <chr>#>  1 Canada 6            6 Canada       2 Quickfire     Individual  Danny Bowien#>  2 Canada 6            6 Canada       2 Elimination   Individual  Lynn Crawford#>  3 Canada 6            6 Canada       3 Quickfire     Individual  Peter Meehan#>  4 Canada 6            6 Canada       3 Elimination   Individual  Carlos Gaytan#>  5 Canada 6            6 Canada       4 Quickfire     Individual  Mark McEwan#>  6 Canada 6            6 Canada       4 Quickfire     Individual  Rob Gentile#>  7 Canada 6            6 Canada       4 Elimination   Team        Ruth Reichl#>  8 Canada 6            6 Canada       5 Quickfire     Individual  Brandon Olsen#>  9 Canada 6            6 Canada       5 Elimination   Team        Alexandra Fes…#> 10 Canada 6            6 Canada       6 Quickfire     Individual  Nicole Gomes#> # ℹ 774 more rows#> # ℹ 4 more variables: gender <chr>, personOfColor <chr>, competedOnTC <chr>,#> #   otherShows <chr>

4.a.v. Rewards

rewards#> # A tibble: 345 × 9#>    season       seasonNumber series episode challengeType outcomeType rewardType#>    <chr>               <dbl> <chr>    <dbl> <chr>         <chr>       <chr>#>  1 All Stars: …            8 US           1 Elimination   Individual  Money#>  2 All Stars: …            8 US           3 Quickfire     Team        Money#>  3 All Stars: …            8 US           3 Quickfire     Team        Money#>  4 All Stars: …            8 US           3 Quickfire     Team        Money#>  5 All Stars: …            8 US           3 Quickfire     Team        Money#>  6 All Stars: …            8 US           3 Elimination   Team        Prize#>  7 All Stars: …            8 US           4 Quickfire     Individual  Money#>  8 All Stars: …            8 US           4 Elimination   Team        Prize#>  9 All Stars: …            8 US           5 Quickfire     Individual  Prize#> 10 All Stars: …            8 US           6 Elimination   Team        Prize#> # ℹ 335 more rows#> # ℹ 2 more variables: reward <chr>, chef <chr>

4.a.vi. Episode info

episodeinfo#> # A tibble: 372 × 8#>    season        seasonNumber series overallEpisodeNumber episode episodeName#>    <chr>                <dbl> <chr>                 <dbl>   <dbl> <chr>#>  1 Canada 6                 6 Canada                   60       1 The Next Wave#>  2 Canada 6                 6 Canada                   61       2 The Chicken o…#>  3 Canada 6                 6 Canada                   62       3 Que Rico#>  4 Canada 6                 6 Canada                   63       4 Restaurant Wa…#>  5 Canada 6                 6 Canada                   64       5 Double Overti…#>  6 Canada 6                 6 Canada                   65       6 That's a Lot …#>  7 Canada 6                 6 Canada                   66       7 Wine of the T…#>  8 Canada 6                 6 Canada                   67       8 Finale Four W…#>  9 San Francisco            1 US                        1       1 Who Deserves …#> 10 San Francisco            1 US                        2       2 Food of Love#> # ℹ 362 more rows#> # ℹ 2 more variables: airDate <date>, nCompetitors <dbl>

4.b. Example using multiple datasets: How many elimination challenge wins did Top Chef winners have?

4.b.i. Visualization

4.b.ii. Code

library(ggplot2)chefdetails %>%# Keep just winners and relevant variables (just the winning chef's name)  filter(placement==1) %>%  select(chef,gender,series,season) %>%# Bring on the challenge result data  left_join(challengewins) %>%# Keep just elimination & sudden death quickfire challenges  filter(challengeType%in% c("Elimination","Quickfire Elimination"                              ,"Sudden Death Quickfire")) %>%# Get the number of wins for each person  group_by(series,season,seasonNumber,chef,gender) %>%  filter(outcome%in% c("WIN","WINNER")) %>%  summarise(wins=n()) %>%# Plot  ggplot(aes(x=wins,y=chef,color=gender,fill=gender,shape=series))+    geom_point(size=4)+    theme_minimal()+# beautification    scale_color_manual(values=c("#1170AA","#A3ACB9"))+    scale_shape_manual(values=c(0,17,1))+    scale_x_continuous(name="Number of elimination wins",breaks=seq(1,9,1),limits=c(.8,9.5),labels=seq(1,9,1))+    theme(panel.grid= element_blank(),title=element_text(size=12),axis.line.x=element_line(color="black"),axis.ticks.x=element_line(color="black"),axis.text.x=element_text(size=12),axis.title.x=element_text(size=12))+  labs(title="Number of elimination wins of Top Chefs"       ,caption="I should have ordered by # of wins...")

4.c. Example using multiple datasets: winning an episode

4.c.i. Visualization

4.c.ii. Code

library(ggplot2)library(topChef)## Won the episode# Data set up# how many episodes each chef won in each seasonwonepi<-challengewins %>% select(!rating) %>%                    mutate(challengeType=case_when(challengeType%in% c("Quickfire Elimination","Sudden Death Quickfire")~"Quickfire"                                                    ,TRUE~challengeType)) %>%                    filter(outcome%in% c("WIN","WINNER")&challengeType%in% c("Elimination","Quickfire")) %>%                    distinct() %>%                    pivot_wider(names_from=challengeType,values_from=outcome) %>%                    filter(Quickfire=="WIN"& (Elimination%in% c("WIN","WINNER"))) %>%# were there multiple winners                      group_by(series,season,seasonNumber,episode) %>%                      mutate(nchefs=n()                             ,chef=ifelse(nchefs>1,paste0(chef,"*"),chef)) %>%# how many times did each chef win an episode?                    ungroup() %>% group_by(series,season,seasonNumber,chef) %>%                    summarise(n=n()) %>%                    select(series,season,seasonNumber,chef,n) %>%                    distinct() %>%                    mutate(seasonNumberchar=case_when(seasonNumber<=9~paste0("0",as.character(seasonNumber))                                                   ,TRUE~as.character(seasonNumber)) ) %>%                    filter(series=="US")# visualizewonepivizdata<-wonepi %>%# add on placement of chefs, just for those who have won an episode            left_join(topChef::chefdetails %>% select(season,seasonNumber,chef,placement)) %>%            mutate(placement=as.character(case_when(placement>5~5                                                    ,TRUE~placement))                    ,placement= case_when(placement=="5"~"5th or lower"                                          ,placement=="1"~"1st"                                          ,placement=="2"~"2nd"                                          ,placement=="3"~"3rd"                                          ,placement=="4"~"4th"                                          ,TRUE~placement))wonepivizdata<-wonepivizdata[order(wonepivizdata$seasonNumberchar,wonepivizdata$n,wonepivizdata$chef),]## Visualizationwonepivizdata %>%            ggplot(aes(x=seasonNumberchar,y=n,label=chef,fill=factor(placement)))+            scale_fill_manual(values=c("#141B41","#1170AA","#5fa2ce","#a3cce9","#ababab"))+            geom_col(position="stack",color="white")+            geom_text(size=1,position= position_stack(vjust=.5),angle=15                      ,color=case_when(wonepivizdata$placement=="1st"~"white"                                       ,wonepivizdata$placement=="2nd"~"white"                                       ,TRUE~"black"                                       ,is.na(wonepivizdata$placement)~"black"))+            labs(title="A Chef has won an episode in all but Seasons 1 and 16"                 ,subtitle="Winning an episode means that one chef won both the Quickfire and Elimination Challenges.\nThis has happened 35 times. Eight Top Chefs won an episode in their season.\n           Brooke is the only one to do it in two different seasons. In all but three seasons, only           one or two chefs won an episode. In seasons four and seven, three chefs won an           episode. In season 11, six chefs won an episode. Stefan and Gregory G. are the only           chefs to have ever won three episodes in one season. Four chefs have won two           episodes in one season: Angelo S., Ed C., Tiffany D., and Brooke W.           * Travis and Carlos won the team quickfire and the paired elimination challenge."                 ,caption="Data: github.com/celevitz/topChef /// Twitter@carlylevitz")+            ylab("\n# of times a chef won an episode this season\n")+            xlab("Season")+            theme_minimal()+            theme(panel.grid= element_blank()                  ,axis.line.x=element_line(color="black")                  ,axis.ticks.x=element_line(color="black")                  ,axis.line.y=element_line(color="black")                  ,axis.ticks.y=element_line(color="black")                  ,axis.text.x=element_text(color="black")                  ,axis.text.y=element_text(color="black")                  ,axis.title.x= element_text(color="black")                  ,axis.title.y= element_text(color="black") )+            guides(fill= guide_legend(title="Placement"))

5. Weighted Index Function

5.a. Distribution of Weighted Index Scores at the Completion of All Seasons

5.b. Examples that use theweightedindex function: full seasons

5.b.i. Visualizations

5.b.ii. Code

library(topChef)library(ggplot2)library(tidyr)library(dplyr)## Get the index for all seasonsallseasons<- weightedindex("US",1,20,20)for (seasonin seq(2,20,1)) {allseasons<- rbind(allseasons,weightedindex("US",season,20,20))          }## Graph it# for sorting reasons, have the season be a characterallseasons$seasonnumchar[allseasons$seasonNumber<=9]<-       paste0("0",as.character(allseasons$seasonNumber[allseasons$seasonNumber<=9]))allseasons$seasonnumchar[allseasons$seasonNumber>9]<-       as.character(allseasons$seasonNumber[allseasons$seasonNumber>9])# for sorting reasons, have the placement as a characterallseasons$placementchar[allseasons$placement<=9]<-       paste0("0",as.character(allseasons$placement[allseasons$placement<=9]))allseasons$placementchar[allseasons$placement>9]<-       as.character(allseasons$placement[allseasons$placement>9])# Distribution of scores at the end of the competition/seasonsgraphalltitles<-function(dataset) {dataset %>%      ggplot(aes(x=placement,y=indexWeight,label=chef))+        facet_wrap(~paste0("Season",seasonnumchar))+        geom_hline(yintercept=0,color="#ffbc69")+        geom_text(hjust=0.5,size=2)+      theme_minimal()+      labs(title=paste0("Top Chef Weighted Index Scores at the End of Seasons")           ,subtitle="Comparing All Chefs Across All Seasons\n")+      ylab("Index Score")+ xlab("Placement")+      scale_y_continuous(lim=c(-30,70))+      scale_x_continuous(lim=c(0,20),breaks=seq(1,18,2),labels= seq(1,18,2))+      theme(panel.grid= element_blank()             ,axis.text.x=element_text(size=6,color="black")            ,axis.text.y=element_text(size=6,color="black")            ,axis.ticks=element_line(color="gray15")             ,axis.line=element_line(color="gray15")             ,strip.background=element_rect(fill="darkcyan")            ,strip.text=element_text(color="black"))    }graphnotitlenocaption<-function(dataset) {dataset %>%      ggplot(aes(x=placement,y=indexWeight,label=chef))+        facet_wrap(~paste0("Season",seasonnumchar))+        geom_hline(yintercept=0,color="#ffbc69")+        geom_text(hjust=0.5,size=2)+      theme_minimal()+      ylab("Index score")+ xlab("Placement")+      scale_y_continuous(lim=c(-30,70))+      scale_x_continuous(lim=c(0,20),breaks=seq(1,18,2),labels= seq(1,18,2))+      theme(panel.grid= element_blank()             ,axis.text.x=element_text(size=6,color="black")            ,axis.text.y=element_text(size=6,color="black")            ,axis.ticks=element_line(color="gray15")             ,axis.line=element_line(color="gray15")            ,strip.background=element_rect(fill="darkcyan")            ,strip.text=element_text(color="black"))    }graphonlycaption<-function(dataset) {dataset %>%      ggplot(aes(x=placement,y=indexWeight,label=chef))+        facet_wrap(~paste0("Season",seasonnumchar))+        geom_hline(yintercept=0,color="#ffbc69")+        geom_text(hjust=0.5,size=2)+        theme_minimal()+        ylab("Index Score")+ xlab("Placement")+        scale_y_continuous(lim=c(-30,70))+        scale_x_continuous(lim=c(0,20),breaks=seq(1,18,2),labels= seq(1,18,2))+        theme(panel.grid= element_blank()               ,axis.text.x=element_text(size=6,color="black")              ,axis.text.y=element_text(size=6,color="black")              ,axis.ticks=element_line(color="gray15")               ,axis.line=element_line(color="gray15")              ,strip.background=element_rect(fill="darkcyan")              ,strip.text=element_text(color="black"))+        labs(caption="Scoring: Elimination win = 7 points. Elimination high = 3. Elimination low = -3. Eliminated = -7.\nQuickfire win = 4. Quickfire high = 2. Quickfire low = -2.\nData github.com/celevitz/topChef ||| Twitter @carlylevitz")    }        graphalltitles(allseasons %>%      filter(seasonNumber%in% c(1,2,3,4,5,6)) )     graphnotitlenocaption(allseasons %>%      filter(seasonNumber%in% c(7,8,9,10,11,12)) )     graphnotitlenocaption(allseasons %>%      filter(seasonNumber%in% c(13,14,15,16,17,18)) )          graphonlycaption(allseasons %>%      filter(seasonNumber%in% c(19,20)) )

5.c. Examples that use theweightedindex function 10 Elimination Challenges or 7 Quickfires into the season

5.c.i. Visualizations

5.c.ii. Code

library(topChef)library(ggplot2)library(tidyr)library(dplyr)## Get the index for all seasonsallseasons<- weightedindex("US",1,10,7)for (seasonin seq(2,20,1)) {allseasons<- rbind(allseasons,weightedindex("US",season,10,7))          }# drop unneeded variablesallseasons<-allseasons[,c("chef","season","seasonNumber","placement","indexWeight")]## Graph it# for sorting reasons, have the season be a characterallseasons$seasonnumchar[allseasons$seasonNumber<=9]<-       paste0("0",as.character(allseasons$seasonNumber[allseasons$seasonNumber<=9]))allseasons$seasonnumchar[allseasons$seasonNumber>9]<-       as.character(allseasons$seasonNumber[allseasons$seasonNumber>9])# for sorting reasons, have the placement as a characterallseasons$placementchar[allseasons$placement<=9]<-       paste0("0",as.character(allseasons$placement[allseasons$placement<=9]))allseasons$placementchar[allseasons$placement>9]<-       as.character(allseasons$placement[allseasons$placement>9])# Distribution of scores at this stage of the competitionallseasons %>%      ggplot(aes(x=seasonnumchar,y=indexWeight) )+      geom_boxplot()+# add horizontal line at 0      geom_hline(yintercept=0,color="#ffbc69")+      theme_minimal()+      labs(title=paste0("Top Chef Weighted Index: 7 quickfires & 10 elimination challenges\ninto each season")           ,subtitle="Comparing All Chefs Across All Seasons\n"           ,caption="Scoring: Elimination win = 7 points. Elimination high = 3. Elimination low = -3. Eliminated = -7.\nQuickfire win = 4. Quickfire high = 2. Quickfire low = -2.\nData github.com/celevitz/topChef ||| Twitter @carlylevitz")+      scale_x_discrete(labels=unique(allseasons$season[order(allseasons$seasonNumber)]))+      theme_minimal()+      ylab("Index score")+ xlab("")+      theme(panel.grid= element_blank()             ,axis.text.x=element_text(angle=90)            )# Top Four: Distribution of scores at this stage of the competitionallseasons[allseasons$placement<=4,]  %>%      ggplot(aes(x=placement,y=indexWeight,label=chef) )+# add horizontal line at 0      geom_hline(yintercept=0,color="#ffbc69")+      geom_text(size=2)+      theme_minimal()+      labs(title=paste0("Top Chef Weighted Index: 7 quickfires & 10 elimination challenges\ninto each season")           ,subtitle="Comparing Top Four Chefs Across All Seasons\n"           ,caption="Scoring: Elimination win = 7 points. Elimination high = 3. Elimination low = -3. Eliminated = -7.\nQuickfire win = 4. Quickfire high = 2. Quickfire low = -2.\nData github.com/celevitz/topChef ||| Twitter @carlylevitz")+      scale_x_continuous(lim=c(.5,4.5),breaks=c(1,1.5,2,3,4),labels=c("1","Current\nseason","2","3","4"))+      theme_minimal()+      ylab("Index score")+ xlab("Placement")+      theme(panel.grid= element_blank()                         )

6. Modified Index Function: Scores Through a Given # of Chefs