help with the following assignment ITS836 Assignment 1: Data
Analysis in R1) Read the income dataset, “zipIncomeAssignment.csv”,
into R. (You can find the csv file in iLearn under the C
help with the following assignment
Assignment 1: Data Analysis in R
1) Read the
income dataset, “zipIncomeAssignment.csv”, into R. (You can find
the csv file in iLearn under the Content -> Week 2 folder.)
Change the column names of
your data frame so
that zcta becomes zipCode and meanhouseholdincome becomes income.
Analyze the summary of
your data. What are the mean and median average incomes?
4) Plot a
scatter plot of the data. Although this graph is not too
informative, do you see any outlier values? If so, what are
In order to omit outliers, create a subset of
the data so that:
< income=””>< $200,000=”” (or=””
in=”” r=”” syntax=”” ,=””
income=””> 7000 & income <>
What’s your new mean?
Create a simple box
your data. Be sure to add a title and label the axes.
Take a look
at: https://www.tutorialspoint.com/r/r_boxplots.htm (specifically,
Creating the Boxplot.) Instead of “mpg ~ cyl”, you want to use
“income ~ zipCode”.
the box plot you created, notice that all of the income data is
pushed towards the bottom of the graph because most average incomes
tend to be low. Create a new box plot where the y-axis uses a
log scale. Be sure to add a title and label the axes. For the
next 2 questions, use the ggplot library
in R, which enables you to create graphs with several different types
of plots layered over each other.
Make a ggplot that
consists of just a scatter plot using the function geom_point() with
position = “jitter” so
that the data points are grouped by zip code. Be sure to
function for taking the log10 of the y-axis data. (Hint:
Create a new ggplot by
adding a box plot layer to your previous graph. To do this, add
the ggplot function geom_boxplot().
Also, add color to the scatter plot so that data points between
different zip codes are different colors. Be sure to label the
axes and add a title to the graph. (Hint:
What can you conclude from this data analysis/visualizati
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