ALL in R studio

Q$1.$ Display the contents of the dataframe.

# Do not display the dataframe, just its contents.

#Q$2.$ How many cases were sampled in the dataframe?

#Q$3.$ How many variables are in the dataframe?

#Q$4.$ Display the top and bottom six rows of the dataframe.

#Q$5.($Respond with code and short written response$)$

#a$.$ Which variables are quantitative?

#b$.$ Which variables are categorical?

#Q$6.$ Create a frequency table per the state and employment sectors variables.

#a$.$ State

#b$.$ Employment Sector

#Q$7.$ Create a new variable with categories of the household variable as a factor, and assign levels and labels to its values.

# Decide on the levels and labels according to what you believe to be interpretable and meaningful for analysis.

# $($There$\text{'}$s no right or wrong answer, just provide your rationale$)$

#Q$8.$ Filter observations that have missing data on the age variable in a new dataframe.

#Q$9.$ How many observations were dropped, based on missing values in the age variable?

#Q$10.$ Create a histogram of the age variable of the filter$\_$dat dataframe.

#Q$11.$ Draw a random sample of $10$ observations from your filter$\_$dat dataframe in a new dataframe.

#Q$12.$ Create a histogram of the age variable from the random sample.

#Q$13.$ What do you notice is different between the random sample and dataset histograms? $($Respond with code and short written response$)$

#Q$14.$ Create a new variable of the income variable, called income$3$ with $3$ levels, and assign levels and labels to its values.

#Q$15.$ Use the aggregate$()$ function to compute the mean and standard deviation of three quantitative variables, by one categorical variable