Directions

In this chapter we discussed why well-designed data graphics are important and we described a taxonomy for understanding their composition.

The objective of this assignment is for you to understand what characteristics you can use to develop a great data graphic.

Each question is worth 5 points.

To submit this homework you will create the document in Rstudio, using the knitr package (button included in Rstudio) and then submit the document to your Rpubs account. Once uploaded you will submit the link to that document on Canvas. Please make sure that this link is hyper linked and that I can see the visualization and the code required to create it.

Question #1

Answer the following questions for this graphic Relationship between ages and psychosocial maturity

  1. Identify the visual cues, coordinate system, and scale(s) Visual cues: color, position, length, direction Coordinate System: Cartesian Scale: Time / Linear

  2. How many variables are depicted in the graph? Explicitly link each variable to a visual cue that you listed above. Four pairs of 2 identical variables: menarche and phychosocial muturation Length: different length between menarche and psychosicial maturation Position: 4 sets of variables in different position Color: Menarche and Phychosocial maturation in different colors Direction: 2 lines in different direction

  3. Critique this data graphic using the taxonomy described in the lecture. The Visualization differenciate menarche and physhosocial maturation by different colors, it shows the mismatch between menarche and phychosicial maturation in present time. It includes time with numerical values as a scale which contains unique properties.

Question #2

Answer the following questions for this graphic World’s top 10 best selling cigarette brands 2004-2007

  1. Identify the visual cues, coordinate system, and scale(s) Visual Cues: Color, Length Coordinate System: Cartesian Scale: Linear (x), Categorical (y)

  2. How many variables are depicted in the graph? Explicitly link each variable to a visual cue that you listed above. 2 variables: cigarette brands and sales. sales (billion) is represented by bar length, colors represent different brands.

  3. Critique this data graphic using the taxonomy described in the lecture. It used both color and lengthe to show information. It shows marlboro is the top best selling brand from 2004 to 2007. Title and X label provide context for date and present meaningful comparison. Linear Scale of X-axis represent sales (billion $).

Question #3

Find two data graphics published in a newspaper on on the internet in the last two years.

  1. Identify a graphical display that you find compelling. What aspects of the display work well, and how do these relate to the principles that we have just gone over in lecture. Include a screenshot of the display along with your solution (Hint:use the following in a code chunk: knitr::include_graphics(“your_graphic”). I found this one compelling because of it is simple and comprehensive. With visual cues of colors and the corresponding indication under the title it’s easy to distinguish. It shows time scale and numbers of respondents labeled clearly.
knitr::include_graphics("graph1.png")

  1. Identify a graphical display that you find less compelling. What aspects of the display don’t work well? Are there ways that the display might be improved? Include a screenshot of the display along with your solution (Hint:use the following in a code chunk: knitr::include_graphics(“your_graphic”). I found this graph hard to interpret and complex. There are some labels attached to the properties but without a title, subtitle to explain the context it’s hard to tell what the visualization is for. using different dashed lines also increase the difficulty to connect the lines and read the graph. I think they could clarify it by placing appropriate titles and separate the curves which represent days of the week to be solid and more contrasting colors.
knitr::include_graphics("graph2.png")

Question #4

Briefly (one paragraph) critique the designer’s choices. Would you have made different choices? Why or why not? Note: Link contains a collection of many data graphics, and I don’t expect (or want) you to write a full report on each individual graphic. But each collection shares some common stylistic elements. You should comment on a few things that you notice about the design of the collection.

What is a Data Scientist

Answer: It is a professional infographic report with cohesive color palette and visual language. it is impressive that they manage to translate all visualization while using similar colors between graphs without causing confusion. The top to bottom order shows a clear logic of how these info should be read and understood. the visual of each graph is clear and compelling along with the actual percentages labeled. Lastly, with the title and description on top, the purpose and audience of this report is clear.

Question #5

Briefly (one paragraph) critique the designer’s choices. Would you have made different choices? Why or why not ? Note: Link contains a collection of many data graphics, and I don’t expect (or want) you to write a full report on each individual graphic. But each collection shares some common stylistic elements. You should comment on a few things that you notice about the design of the collection.

Charts that explain food in America

Answer:

With a mix of geographic coordinate system and cartesian coordinate system, I found it hard to concentrate on the subject these graphics are explaining. Most graphs has clear visual cues of colors to distinguish data points on the graph, such as “meat consumption, per capita” that clearly shows a relation between the darkness of red to the consumption amount by kg. However, some graphs doesn’t provide such clear understanding such as “No Car and No Supermarket Store Within a Mile”, which doesn’t provide a clear explanation of the actual scarcity of these resource, instead showing the percentage of the land that are far from food resources despite the size of the area. I would also refrain from showing such large amount of different subjects within one collection, which could further confuse audiences of the focused subject.