plot_team_cluster_facets.R

team_cluster <- read_csv("~/src/aibook/src/chapter7/data/nba_2017_att_val_elo_win_housing_cluster.csv", 
                         col_types = cols(X1 = col_skip()))
library("ggplot2")

#Name Clusters
team_cluster$cluster_name[team_cluster$cluster == 0] <- "Low Valuation/Low Performance"
team_cluster$cluster_name[team_cluster$cluster == 1] <- "Medium Valuation/High Performance"
team_cluster$cluster_name[team_cluster$cluster == 2] <- "High Valuation/Low Performance"

#Create faceted plot
p <- ggplot(data = team_cluster) +
    geom_point(mapping = aes(x = ELO,
                             y = VALUE_MILLIONS, 
                             color = factor(WINNING_SEASON, labels=c("LOSING","WINNING")), 
                             size = MEDIAN_HOME_PRICE_COUNTY_MILLIONS,
                             shape = CONF)) +
    facet_wrap(~ cluster_name) +
    ggtitle("NBA Teams 2016-2017 Faceted Plot of Valuation of Team and Performance (ELO)") +
    ylab("Value NBA Team in Millions") +
    xlab("Relative Team Performance (ELO)") +
    geom_text(aes(x = ELO, y = VALUE_MILLIONS, label=ifelse(VALUE_MILLIONS>1200,as.character(TEAM),'')),hjust=.35,vjust=1)    

#Change legends
p + 
    guides(color = guide_legend(title = "Winning Season")) +
    guides(size = guide_legend(title = "Median Home Price County in Millions" )) +
    guides(shape = guide_legend(title = "NBA Conference"))