In this work, with google translate notebook, a spreadsheet is exported then imported to R studio to generate a webpage.

boxplot(Sepal.Length ~ Species, data = iris, main = "Box Plot of Sepal Length by Species", col = "lightblue")

waffle(table(iris$Species), rows = 5, title = "Waffle Chart of Iris Species")

library(fmsb) iris_means <- aggregate(iris[, 1:4], by = list(iris$Species), FUN = mean) radarchart(iris_means[, -1], title = "Radar Chart of Iris Species Means")

library(maps) library(ggmap) data("USArrests") us_map <- map_data("state") USArrests$region <- tolower(rownames(USArrests)) map_data <- merge(us_map, USArrests, by = "region") map_plot <- ggplot(map_data, aes(x = long, y = lat, group = group, fill = Murder)) + geom_polygon(color = "black") + scale_fill_gradient(low = "white", high = "red") + labs(title = "Map: Murder Rate by State", fill = "Murder Rate") + theme_void() print(map_plot)

Wordcloud

box_plot <- ggplot(diamonds, aes(x = cut, y = price, fill = cut)) + geom_boxplot() + labs(title = "Box Plot: Price Distribution by Cut", x = "Cut", y = "Price") + theme_minimal() print(box_plot)

library(wordcloud) library(fmsb) library(waffle) library(reshape2) color_counts <- diamonds %>% group_by(color) %>% summarise(count = n()) waffle_chart <- waffle(color_counts$count, rows = 5, title = "Waffle Chart: Proportion of Diamonds by Color") print(waffle_chart)

library(wordcloud) library(fmsb) library(waffle) library(reshape2) wordcloud(words = unique(diamonds$clarity), freq = table(diamonds$clarity), colors = brewer.pal(8, "Dark2"), main = "Word Cloud: Diamond Clarity")

ggplot(airquality, aes(x = Temp, y = Ozone)) + geom_point() + geom_smooth(method = "lm", col = "red") + ggtitle("Regression Plot: Temperature vs Ozone") + xlab("Temperature") + ylab("Ozone")

plot(iris$Sepal.Length, type = "l", main = "Line Plot of Sepal Length", xlab = "Index", ylab = "Sepal Length", col = "purple")