辅导ETF5922、辅导Assignment 1: Visualisation Java/Python语言

ETX2250/ETF5922 Data Visualisation and

Analytics

Assignment 1: Visualisation – The Arts

Submission instructions

This assignment comprises 15% of the assessment in ETX2250 and

ETF5922.

Your assignment submission will consist of a pdf document. The

document must include both your code and graphical and other output

as well as paragraph answers that provide description and discussion

of the output. The presentation of graphs is important. In

particular, headings and labels should be provided.

In your completed assignment, graphs should be easy to read, with

appropriate use of headings, colour, formatting and text.

The pdf document must be submitted as a hard copy in class, and also

must be uploaded to Moodle.

The pdf document should be titled <studentid>_A1.pdf

(Note: No spaces, No Names, No other characters, No extra

characters)

The assignment is due before class on Friday 25 January 2019 (9.00

am), and a hard copy of the pdf document should be submitted in

class, securely stapled in the top left corner and with a signed

COVER SHEET on top.

If for some reason you are unable to submit the assignment

personally, there will be an assignment box available on level 5 of

Building H to place it there before the due time.

The cover sheet is available at URL:

https://www.monash.edu/__data/assets/word_doc/0004/903379/assignment

-cover-sheet-fbe-1.doc you must supply the unit code and further

details.

Upload your assignment to Moodle as follows:

Go to the Assignments section

Click on Submission of Assignment 1: Visualisation

Click on Add submission

Drag and drop the file to submit it

Save changes

To confirm that your upload was successful, go to the Assignments

section, and click on the Assignment 1: Visualisation link. The

uploaded filename will be shown.

Retain your marked assignment until after the publication of the

final results for this unit.

Assignment 1: Introduction

This assignment relates to the Visualisation component of the unit.

We ask you to report on two different data sets.

Part A: Painters

The first is the data set painters relating to various qualities of

the artwork of some famous classical painters.

Part B: Movies

The second part of the assignment is unrelated to the first. You

will investigate certain aspects of a data set about movies.

Assignment 1 Part A (10 Points)

The data set painters.csv is available on the Moodle site. This data

consists of scores assigned to 54 classical painters on the basis of

the four attributes:

Composition

Drawing

Colour

Expression

Thus there are 216 scores altogether. The names of the artists are

given as row label. In addition there is a categorical variable:

School , taking values A, B, C, D, E, F, G, H (see the details in

the library MASS and type ?painters in a cell).

a) Data Wrangling (1 Point)

Some of the graphics you will be asked to produce relating to the

painters data set are more conveniently produced using long form

data. So prepare by producing a version of this data in long form.

Also provide the head and tail of the resulting data frame.

b) Produce each of the following graphs. (2 Points)

(i) To determine the distribution of scores over the possible

range, provide a histogram of all 216 scores. Use a binwidth

of 1 so that it is clear exactly how many of each score have

been assigned. (0.5 Points)

(ii) Provide four histograms showing the distribution of scores

in each of the four Attributes. (0.5 Points)

(iii) Provide boxplots of the scores, one for each of the four

Attributes. (0.5 Points)

(iv) Provide a scatterplot matrix for the scores across all

attributes (i.e. the scatterplot matrix includes

scatterplots for each pair of attributes.) (0.5 Points)

(c) Summarise what you learn from the plots in (b) about the

distributions of scores. (3 Points)?

(d) Suppose we now would like to also distinguish scores

between the different schools (A to H) (1.5 Points)

(i) Apply a facet wrap to the graph produced in (b) (iii) to

obtain thirty-two boxplots, four for each School,

corresponding to the four Attributes. (0.5 Points)

(ii) Provide a graph of the scores for each School, coloured

by Attributes. (e.g. schools A to H along x axis, and in a

line above a given school, points representing the scores for

painters in that school, coloured by attribute.) (0.5 Points)

(iii) Provide a facet plot where facets correspond to schools,

and for which in each facet, attributes are plotted on the x

axis and scores on the y axis, with dots coloured by attribute

and appropriate use of jittering. (0.5 Points)

(e) For the various plots you have provided in part (d),

discuss the advantages and disadvantages of using them to

represent the data about scores by schools. (1 Point)

(f) Choose your preferred plot from part (d). Choose three

Schools to focus on, and discuss what your chosen plot

indicates about the attributes of these schools. (1.5 Points)

Assignment 1 Part B (4 Points)

There is a package ggplot2movies containing the data set movies.

(a) Create a histogram for the variable length in the data set

movies, limiting the range of the x axis so that the shape can

be seen. Comment on the shape. (1 Points)

b) (1 Point)?

We are going to focus on certain feature length movies. Use the

subset commands on the data frame movies to create a data frame

entitled movies.df satisfying the following:

It includes only the variables title, year, length, rating,

votes, Action, Comedy, Drama, and Romance.

It includes only those movies that are at least 60 minutes and

at most 180 minutes long.

It includes only those movies that are listed as being in at

least one of the four categories Action, Comedy, Drama, and

Romance

c) (1 Point)

(i) Construct a mosaic plot for the four binary variables

Action, Comedy, Drama, and Romance. Choose the order of

the variables so that the mosaic plot splits simply into

a section that is comedy and a section that is not

comedy. (0.25 Points)

(ii) One possible plot that you might obtain is:

For each segment of the mosaic plot labelled X1 through

X8, state which of the classifications Comedy, Drama,

Romance, and Action it belongs to. (Of course, in many

cases, it will belong to more than one. You should state

all categories it belongs to. ) (0.25 Points)

(iii) Given that a movie is a Comedy, which is it most likely

to also be: Action, Drama or Romance? Which is it least

likely to also be? Explain your answers by referring to

the mosaic plot above. (0.5 Points)

d) (1 Point)

Using the movies in the movies.df data frame, construct a scatter

plot for rating vs votes. Discuss what conclusions can be drawn from

this scatter plot about these two variables and their relationship.

Overall presentation: 1 point