library(ggplot2) ggplot(fruit_data, aes(x = Fruit, y = Sales)) + geom_point(size = 4, color = "red") + labs(title = "Fruit Sales (Scatter Plot)", x = "Fruit", y = "Sales Count")

data <- data.frame( Communication = c(5, 4, 3, 2, 1), Teamwork = c(4, 5, 2, 3, 1), ProblemSolving = c(3, 4, 5, 2, 1), Creativity = c(2, 3, 4, 5, 1) ) data <- rbind(rep(5, 4), rep(0, 4), data) radarchart(data, title = "Radar Chart: Employee Performance", pcol = "purple", pfcol = rgb(0.5, 0, 0.5, 0.3), plwd = 2)

data <- data.frame( Product1 = c(5, 4, 3, 2, 1), Product2 = c(4, 5, 2, 3, 1), Product3 = c(3, 4, 5, 2, 1) ) data <- rbind(rep(5, 3), rep(0, 3), data) radarchart(data, title = "Radar Chart: Comparing Products", pcol = c("blue", "red", "green"), pfcol = c(rgb(0, 0, 1, 0.3), rgb(1, 0, 0, 0.3), rgb(0, 1, 0, 0.3)), plwd = 2)

install.packages("fmsb") library(fmsb) data <- data.frame( Speed = c(5, 4, 3, 2, 1), Durability = c(4, 5, 2, 3, 1), Reliability = c(3, 4, 5, 2, 1), Efficiency = c(2, 3, 4, 5, 1) ) data <- rbind(rep(5, 4), rep(0, 4), data) radarchart(data, title = "Radar Chart: Product Attributes", pcol = "blue", pfcol = rgb(0, 0, 1, 0.3), plwd = 2)

us_map <- map_data("state") ggplot(us_map, aes(x = long, y = lat, group = group)) + geom_polygon(fill = "lightgreen", color = "black") + theme_minimal() + ggtitle("US State Map Example")

install.packages("maps") install.packages("ggplot2") library(maps) library(ggplot2) world_map <- map_data("world") ggplot(world_map, aes(x = long, y = lat, group = group)) + geom_polygon(fill = "lightblue", color = "black") + theme_minimal() + ggtitle("World Map Example")

set.seed(123) group1 <- rnorm(100, mean = 70, sd = 10) group2 <- rnorm(100, mean = 80, sd = 15) group3 <- rnorm(100, mean = 60, sd = 5) boxplot(group1, group2, group3, names = c("Group 1", "Group 2", "Group 3"), col = "orange", main = "Box Plot: Exam Scores by Group")

install.packages("waffle") library(waffle) parts <- c(30, 20, 15, 35) waffle(parts, rows = 5, colors = c("red", "blue", "green", "yellow"), title = "Waffle Chart: Distribution")

install.packages("fmsb") library(fmsb) data <- data.frame( Speed = c(5, 4, 3, 2, 1), Durability = c(4, 5, 2, 3, 1), Reliability = c(3, 4, 5, 2, 1), Efficiency = c(2, 3, 4, 5, 1) ) radarchart(data, title = "Radar Chart: Product Attributes")

install.packages("wordcloud") library(wordcloud) words <- c("Data", "Visualization", "R", "Programming", "Analysis", "Statistics", "Charts", "Graphs") freq <- c(50, 40, 30, 25, 20, 15, 10, 5) wordcloud(words, freq, colors = brewer.pal(8, "Dark2"), main = "Word Cloud Example")

time <- c(1, 2, 3, 4, 5, 6) sales <- c(200, 220, 250, 300, 320, 350) plot(time, sales, type = "o", col = "red", main = "Line Plot: Sales Over Time", xlab = "Time (Months)", ylab = "Sales ($)") abline(lm(sales ~ time), col = "blue")

height <- c(160, 165, 170, 175, 180, 185) weight <- c(60, 65, 70, 75, 80, 85) plot(height, weight, col = "blue", pch = 19, main = "Scatter Plot: Height vs Weight", xlab = "Height (cm)", ylab = "Weight (kg)")

market_share <- c(30, 25, 20, 15, 10) labels <- c("Company A", "Company B", "Company C", "Company D", "Others") pie(market_share, labels = labels, col = rainbow(length(labels)), main = "Pie Chart: Market Share")

set.seed(123) data <- rnorm(1000, mean = 50, sd = 10) hist(data, breaks = 30, col = "lightgreen", main = "Histogram: Random Normal Distribution", xlab = "Values")