Code

First Visual

dataset <- read.csv("C:/Users/adikh/OneDrive/Desktop/Stat/AnkitBorle/Dataset/StatDataset.csv")

p1 = ggplot(dataset, aes(x = reorder(Team, -Perfect.Seasons.Needed), y = Perfect.Seasons.Needed, group = League))+
  geom_point(aes(color = League), size = 2) +
  geom_line(aes(color = League)) +
  theme(axis.text.x = element_text(angle = 65, hjust = 1),
        legend.position = "right")   + 
  facet_wrap(~League, scales = "free_x", nrow = 3) +
  labs(x = "Team",
       y = "Perfect Seasons Needed")

p1

p2 = ggplot(dataset, aes(x = League, y = Perfect.Seasons.Needed, fill = League)) +
  geom_boxplot() +
  labs(title = "Distribution of Perfect Seasons Needed by League",
       x = "League", y = "Perfect Seasons Needed")

ggplotly(p2)

Second Visual

data <- read.csv("C:/Users/adikh/OneDrive/Desktop/Stat/AnkitBorle/Dataset/stat_proj.csv")

#Plotting Bar Graph
bar_graph<-ggplot(data, aes(x = reorder(region, dollars_millions), y = dollars_millions))+
  geom_bar(stat = 'identity', aes(fill = continent))+
  coord_flip() +
  labs(title = "Share of countries by palm oil import", y = "Dollars (in Millions)", x = "Region", fill = "Continent") +
  theme_minimal()
  
#Converting Bar Graph to Interactive Graph
ggplotly(bar_graph)

#Plotting Weighted Scatter Graph
scatter <- ggplot(data, aes(x = region, y = dollars_millions, size = dollars_millions, color = continent)) +
  geom_point(alpha = 0.8) +
  scale_size_continuous(range = c(3, 15)) +
  geom_text(aes(label = dollars_millions), 
            vjust = 0.5,
            hjust = 0.5,
            color = "black",
            size = 2) +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 65, hjust = 1)) + 
  labs(title = "Share of countries by palm oil export",
       x = "Region",
       y = "Dollars (in Millions)",
       color = "Continent")+
  guides(size = "none")

scatter

world_tbl <- map_data("world") %>% as_tibble()

left <- left_join(world_tbl, data, by="region")

map1 <- ggplot(left, aes( x = long, y = lat, group=group)) +
  geom_polygon(aes(fill = dollars_millions), color = "black")+
  scale_fill_gradient2(low = "white", mid = "yellow", high = "red", midpoint = 1500)+
  labs(title = "Region wise share of palm oil export",
       x = "Longitude",
       y = "Latitude",
       fill = "Million Dollars")

ggplotly(map1)