Recently Published
BoxPlot
boxplot(Sepal.Length ~ Species, data = iris,
main = "Box Plot of Sepal Length by Species",
col = "lightblue")
Waffle chart
waffle(table(iris$Species),
rows = 5,
title = "Waffle Chart of Iris Species")
Radar chart
library(fmsb)
iris_means <- aggregate(iris[, 1:4], by = list(iris$Species), FUN = mean)
radarchart(iris_means[, -1], title = "Radar Chart of Iris Species Means")
Map
library(maps)
library(ggmap)
data("USArrests")
us_map <- map_data("state")
USArrests$region <- tolower(rownames(USArrests))
map_data <- merge(us_map, USArrests, by = "region")
map_plot <- ggplot(map_data, aes(x = long, y = lat, group = group, fill = Murder)) +
geom_polygon(color = "black") +
scale_fill_gradient(low = "white", high = "red") +
labs(title = "Map: Murder Rate by State",
fill = "Murder Rate") +
theme_void()
print(map_plot)
World cloud
Wordcloud
Box Plot
box_plot <- ggplot(diamonds, aes(x = cut, y = price, fill = cut)) +
geom_boxplot() +
labs(title = "Box Plot: Price Distribution by Cut",
x = "Cut",
y = "Price") +
theme_minimal()
print(box_plot)
Waffle chart
library(wordcloud)
library(fmsb)
library(waffle)
library(reshape2)
color_counts <- diamonds %>%
group_by(color) %>%
summarise(count = n())
waffle_chart <- waffle(color_counts$count, rows = 5,
title = "Waffle Chart: Proportion of Diamonds by Color")
print(waffle_chart)
Word Cloud
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")
Scatter plot & Line plot
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")
Line plot
plot(iris$Sepal.Length, type = "l",
main = "Line Plot of Sepal Length",
xlab = "Index",
ylab = "Sepal Length",
col = "purple")
Line Plot
line_plot <- ggplot(diamonds, aes(x = carat, y = price)) +
geom_point(alpha = 0.3) +
geom_smooth(method = "lm", color = "red") +
labs(title = "Line Plot with Regression: Price Trends Over Carat",
x = "Carat",
y = "Price") +
theme_minimal()
print(line_plot)
Scatter plot
plot(iris$Sepal.Length, iris$Sepal.Width,
main = "Scatter Plot: Sepal Length vs Sepal Width",
xlab = "Sepal Length",
ylab = "Sepal Width",
col = iris$Species,
pch = 19)