The data of all football players collected from Futwiz will be continuously used for visuallisation. This paper will focus on practicing in the use of geom_segment and facet_wrap functions. One problem while using facet_wrap is that the aspect ratio of facets can not be changed manually. Cowplot package with plot_grid function could be a solution for better visuallisation.

THE MOST POTENTIAL PLAYERS BY POSITIONS

rm(list = ls())

library(tidyverse)

df_tidy <- read_csv("C:\\Users\\Thinh Dao\\Desktop\\Mini R Project 7.7.19\\Fifa 19\\Practice#1\\fifa19_tidy.scv") #load the data

df_tidy  %>% 
  select(Player_name, Club, League, OVR, POT, POS, GROW, Age, Foot) -> df_tidy # Select some columns of the datat set 

df_tidy  %>% 
  mutate(POS_group = case_when(POS %in% c("CB", "LB", "RB", "LWB", "RWB") ~ "DEF", 
                               POS %in% c("CM", "CDM", "CAM", "LM", "RM") ~ "MID",
                               POS == "GK" ~ "GK",
                               TRUE ~ "ATT")) %>% 
  mutate(Age_group = case_when(Age < 19 ~ "U19", 
                               Age >= 19 & Age < 23 ~ "A19-U23",
                               Age >=23 & Age < 27 ~ "A23-U27",
                               Age >=27 & Age < 31 ~ "A27-U31",
                               Age >=31 & Age < 35 ~ "A31-U35",
                               TRUE ~ "O35"))  %>% 
  mutate(Player_pos = paste0(Player_name, " ", "(", POS, ")")) -> df_tidy # Classify Position group and age group 


df_tidy[!(df_tidy$POT %>% is.na()),] -> df_plot #Remove the NA in POT columns

# Plotting the most potential players by position:

df_plot %>% 
  group_by(POS) %>% 
  filter(POT == max(POT)) %>% 
  ungroup() -> df_segment1 


 df_segment1 %>% 
  ggplot(aes(y  = reorder(Player_pos, POT)))+
  geom_segment(data = df_segment1,
               aes(x = OVR, xend = POT, yend = Player_pos),
               size = 1,
               color = "lightslategrey") +
  geom_segment(data = df_segment1,
               aes(x = 72, xend = OVR, yend = Player_pos),
               linetype = "dotted",
               size = 0.5,
               color = "lightslategrey") +
  geom_point(data = df_segment1, aes(x = OVR, color = "color1"), size =5, alpha = 1)+
  geom_point(data = df_segment1, aes(x = POT, color = "color2"), size =5, alpha = 1)+
  geom_text(data = df_segment1 %>% filter(GROW != 0), aes(x= OVR, label = OVR), size = 5.5, hjust = 1.4, color = "grey20") +
  geom_text(data = df_segment1 , 
            aes(x = POT, y = Player_pos, label = POT), 
            size = 5.5, hjust = - 0.4, color = "grey20") +
  theme_minimal() +
  theme(plot.background = element_rect(fill = "whitesmoke", linetype = 0))+
  theme(panel.grid = element_blank())+
  scale_x_continuous(limits = c(72, 97), 
                     expand = c(0 , 0)) +
  theme(axis.text.x = element_blank(),
        axis.title.x = element_blank(),
        axis.ticks.x = element_blank(),
          axis.line.x = element_blank()) +
  theme(axis.text.y = element_text(color = "grey20", size = 15),
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank(),
        axis.line.y = element_blank())+
  scale_color_manual(name="", values= c("color1" = "#ff7f00", "color2" = "#4daf4a"),
                      labels = c("Current Overall Score", "Potential Score"))+
  theme(legend.title = element_blank(),
        legend.text = element_text(face = "italic", color = "grey20", size = 15),
        legend.position = c(0.83, 0.25))+
  theme(plot.margin = unit(c(1.2, 1.2, 1.2, 1.2), "cm")) + 
  theme(plot.title = element_text(size = 29, color = "gray20")) + 
  theme(plot.subtitle = element_text(size = 17, color = "gray20", face ="italic" )) + 
  theme(plot.caption = element_text(size = 15, color = "gray20", face = "italic"))+ 
  labs(x = NULL, y = NULL, 
       title = "Fifa19: The most potential players by positions" ,
       subtitle = "Therer are 15 positions in total including 4 positions of Attacker \n 5 positions of Midfielder, 5 positions of Defender and Goalkeeper position",
         caption = "Data Source: https://www.futwiz.com/en/fifa19/career-mode")+
    annotate("text", label = "*", 
             x = 94.6,
           y = 21.2, 
           color = "firebrick", 
           size = 7, hjust = 0, vjust = 1)+
   annotate("text", label = "*", 
            x = 92.6,
            y = 15.2, 
            color = "firebrick", 
            size = 7, hjust = 0, vjust = 1)+
   annotate("text", label = "*", 
            x = 91.6,
            y = 12.2, 
            color = "firebrick", 
            size = 7, hjust = 0, vjust = 1)+
   annotate("text", label = "* The player who already reached his limit ", 
            x = 90.7,
            y = 5.5, 
            color = "firebrick",
            size = 5, hjust = 0, vjust = 1)

THE MOST POTENTIAL PLAYERS BY POSITION GROUP USING FACET_WRAP

 df_plot %>% 
   group_by(POS_group) %>% 
   top_n(10, wt = POT) %>%
   ungroup() %>% 
   arrange(POS_group, -POT) -> df_segment2
 
 my_label <- c("ATT" = "ATTACKER", "MID" = "MIDFIELDER", "DEF" = "DEFENDER", "GK" = "GOALKEEPER")
 
 df_segment2$POS_group <- factor(df_segment2$POS_group, levels = c("ATT", "MID", "DEF", "GK"))
 
 df_segment2 %>% 
   ggplot(aes(y = reorder(Player_pos,POT)))+
   geom_segment(data = df_segment2,
                aes(x = OVR, xend = POT, yend = Player_pos),
                size = 1,
                color = "lightslategrey")+
   geom_segment(data = df_segment2,
                aes(x = 71.5, xend = OVR, yend = Player_pos),
                linetype = "dotted",
                size = 0.5,
                color = "lightslategrey")+
   geom_point(data = df_segment2, aes(x = OVR, color = "color1"), size =5, alpha = 1)+
   geom_point(data = df_segment2, aes(x = POT, color = "color2"), size =5, alpha = 1)+
   geom_text(data = df_segment2 %>% filter(GROW != 0), 
             aes(x= OVR, y = Player_pos, label = OVR), 
             size = 5.5, hjust = 1.4, color = "grey20") +
   geom_text(data = df_segment2, 
             aes(x = POT, y = Player_pos, label = POT), 
             size = 5.5, hjust = - 0.4, color = "grey20") +
   theme_minimal() +
   theme(plot.background = element_rect(fill = "whitesmoke", linetype = 0))+
   theme(panel.grid = element_blank())+
   scale_x_continuous(limits = c(71.5, 97), expand = c(0, 0)) +
      theme(axis.text.x = element_blank(),
         axis.title.x = element_blank(),
         axis.ticks.x = element_blank(),
         axis.line.x = element_blank()
         ) +
   theme(axis.text.y = element_text(color = "grey20", size = 15),
         axis.title.y = element_blank(),
         axis.ticks.y = element_blank(),
         axis.line.y = element_blank()
         )+
   facet_wrap(~ POS_group, scales = "free", 
              labeller = labeller(POS_group = my_label),
              ncol = 2) +
   theme(strip.text = element_text(face = "bold", color = "grey20", size = 15)
         )+
   scale_color_manual(name="", values= c("color1" = "#ff7f00", "color2" = "#4daf4a"),
                      labels = c("Current Overall Score", "Potential Score"))+
   theme(legend.title = element_blank(),
         legend.text = element_text(face = "bold.italic", color = "grey20", size = 15),
         legend.position = "bottom")+
   theme(plot.margin = unit(c(1.2, 1.2, 1.2, 1.2), "cm")) + 
   theme(plot.title = element_text(size = 29, color = "gray20")) + 
   theme(plot.subtitle = element_text(size = 17, color = "gray20", face ="italic" )) + 
   theme(plot.caption = element_text(size = 15, color = "gray20", face = "italic"))+ 
   labs(x = NULL, y = NULL, 
        #subtitle = "Attacker: ST, CF, LW, RW\nMidfielder: CM, CAM, CDM, RM, LM\nDefender: CB, LB, RB, LWB, RWB\nGoalkeeper: GK",
        title = "Fifa19: The most potential players by position groups" , 
        caption = "Data Source: https://www.futwiz.com/en/fifa19/career-mode")+
   theme(panel.spacing = unit(1.5, "line"))

THE MOST POTENTIAL PLAYERS BY AGE GROUP USING FACET_WRAP THEN PLOT_GRID

As most of over 31 year old players reached to their limit already so the graph only shows the most potential U31 players. The use of package cowplot especially the plot_grid function allows us setting up manually the ratio of selected graphs which we want to combine.
df_plot %>% 
   filter(Age_group == "U19" | Age_group == "A19-U23") %>% 
   group_by(Age_group) %>% 
   top_n(10, wt = POT) %>%
   ungroup() %>% 
   arrange(Age_group, -POT) -> df_segment3
 
 df_segment3$Age_group %>% unique()
 
 my_label1 <- c("U19" = "Under 19", 
                "A19-U23" = "From 19 to under 23")
                
 df_segment3$Age_group <- factor(df_segment3$Age_group, 
                                 levels = c("U19", "A19-U23"))
 
 df_segment3 %>%
   ggplot(aes(y = reorder(Player_pos,POT)))+
   geom_segment(data = df_segment3,
                aes(x = OVR, xend = POT, yend = Player_pos),
                size = 1,
                color = "lightslategrey")+
   geom_segment(data = df_segment3,
                aes(x = 63.5, xend = OVR, yend = Player_pos),
                linetype = "dotted",
                size = 0.5,
                color = "lightslategrey")+
   geom_point(data = df_segment3, 
              aes(x = OVR, color = "color1"), size =5, alpha = 1)+
   geom_point(data = df_segment3, 
              aes(x = POT, color = "color2"), size =5, alpha = 1)+
   geom_text(data = df_segment3 %>% filter(GROW != 0), 
             aes(x= OVR, y = Player_pos, label = OVR), 
             size = 5.5, hjust = 1.4, color = "grey20") +
   geom_text(data = df_segment3, 
             aes(x = POT, y = Player_pos, label = POT), 
             size = 5.5, hjust = - 0.4, color = "grey20") +
   theme_minimal() +
   theme(plot.background = element_rect(fill = "whitesmoke",linetype = 0))+
   theme(panel.grid = element_blank())+
   scale_x_continuous(limits = c(63.5, 97), 
                      expand = c(0,0)) +
   theme(axis.text.x = element_blank(),
         axis.title.x = element_blank(),
         axis.ticks.x = element_blank(),
         axis.line.x = element_blank()
   ) +
   theme(axis.text.y = element_text(color = "grey20", size = 15),
         axis.title.y = element_blank(),
         axis.ticks.y = element_blank(),
         axis.line.y = element_blank()
   )+
   facet_wrap(~ Age_group, scales = "free", 
              labeller = labeller(Age_group = my_label1),
              ncol = 2) +
   theme(strip.text = element_text(face = "bold", color = "grey20", size = 15)
   )+
   scale_color_manual(name="", values= c("color1" = "#ff7f00", "color2" = "#4daf4a"),
                      labels = c("Current Overall Score", "Potential Score"))+
   theme(legend.title = element_blank(),
         legend.text = element_text(face = "bold.italic", color = "grey20", size = 15),
         legend.position = "top")+
   theme(plot.margin = unit(c(1.2, 1.2, 0.5, 1.2), "cm")) + 
   theme(plot.title = element_text(size = 29, color = "gray20")) + 
   theme(plot.subtitle = element_text(size = 17, color = "gray20", face ="italic" )) + 
   theme(plot.caption = element_text(size = 15, color = "gray20", face = "italic"))+ 
   labs(x = NULL, y = NULL, 
        subtitle = "The age groups are defined as under 19 (U19), from 19 to under 23 (A19-U23) and so on" , 
        title = "Fifa19: The most potential players by age groups") -> g3
 
 df_plot %>% 
   filter(Age_group == "A23-U27" | Age_group == "A27-U31") %>% 
   group_by(Age_group) %>% 
   top_n(10, wt = POT) %>%
   ungroup() %>% 
   arrange(Age_group, -POT) -> df_segment4
 
 my_label2 <- c("A23-U27" = "From 23 to under 27",
                "A27-U31" = "From 27 to under 31")
 
 df_segment4$Age_group <- factor(df_segment4$Age_group, 
                                 levels = c("A23-U27", "A27-U31"))
 
 df_segment4 %>%
   ggplot(aes(y = reorder(Player_pos,POT)))+
   geom_segment(data = df_segment4,
                aes(x = OVR, xend = POT, yend = Player_pos),
                size = 1,
                color = "lightslategrey")+
   geom_segment(data = df_segment4,
                aes(x = 63.5, xend = OVR, yend = Player_pos),
                linetype = "dotted",
                size = 0.5,
                color = "lightslategrey")+
   geom_point(data = df_segment4, 
              aes(x = OVR, color = "color1"), size =5, alpha = 1)+
   geom_point(data = df_segment4, 
              aes(x = POT, color = "color2"), size =5, alpha = 1)+
   geom_text(data = df_segment4 %>% filter(GROW != 0), 
             aes(x= OVR, y = Player_pos, label = OVR), 
             size = 5.5, hjust = 1.4, color = "grey20") +
   geom_text(data = df_segment4, 
             aes(x = POT, y = Player_pos, label = POT), 
             size = 5.5, hjust = - 0.4, color = "grey20") +
   theme_minimal() +
   theme(plot.background = element_rect(fill = "whitesmoke", linetype = 0))+
   theme(panel.grid = element_blank(),
         panel.border = element_blank())+
   scale_x_continuous(limits = c(63.5, 97), 
                      expand = c(0,0)) +
   theme(axis.text.x = element_blank(),
         axis.title.x = element_blank(),
         axis.ticks.x = element_blank(),
         axis.line.x = element_blank()) +
   theme(axis.text.y = element_text(color = "grey20", size = 15),
         axis.title.y = element_blank(),
         axis.ticks.y = element_blank(),
         axis.line.y = element_blank())+
   facet_wrap(~ Age_group, scales = "free", 
              labeller = labeller(Age_group = my_label2),
              ncol = 2) +
   theme(strip.text = element_text(face = "bold", color = "grey20", size = 15))+
   scale_color_manual(values= c("color1" = "#ff7f00", "color2" = "#4daf4a"))+
   theme(legend.title = element_blank(),
         legend.text = element_blank(),
         legend.position = "none")+
   theme(plot.margin = unit(c(0, 1.2, 1.2, 1.2), "cm")) + 
   theme(plot.caption = element_text(size = 15, color = "gray20", face = "italic"))+ 
   labs(x = NULL, y = NULL, 
        caption = "Data Source: https://www.futwiz.com/en/fifa19/career-mode") -> g4
 
 library(cowplot) 

 plot_grid(g3, g4, nrow = 2, rel_heights =  c(1.65, 1))