How to do basic data exploration in R?

iris <- read.csv("Iris_Data.csv")

# Display the first few rows of the iris data.
head(iris)

# Rename the column name Species to Type.
names(iris)[5] <- "Type"

# Display the first 5 rows and last 3 columns of the iris data frame.
iris[1:5, 3:5]

# What is the data type of each column in this data frame of iris data?
str(iris)

# Draw a box plot of Sepal Length.
boxplot(iris$Sepal.Length)

# Draw a scatter plot of Sepal Length vs Sepal Width.
plot(Sepal.Width ~ Sepal.Length, data = iris)

# Create a new column in the iris data frame which is the sum of Sepal Length and Sepal Width.
iris$sum <- iris$Sepal.Length + iris$Sepal.Width

# What are the means, medians, and standard deviations of the four predictor columns in this data frame?
summary(iris[, 1:4])
sd(iris$Sepal.Length)
sd(iris$Sepal.Width)
sd(iris$Petal.Length)
sd(iris$Petal.Width)

# Draw the pair-wise correlations between the features of the iris data set.
pairs(iris[,1:4])

Another way to visualize the distributions of the variables in the data which can be Length and Width is to use the ggplot library in R. Histograms can also be plotted using this library. To get to know about these features in detail here is the link to the documentation: ggplot function | R Documentation