Stat 515 Spring 2016
Redesign Project
By Voravan CharnsawatPatcharaporn Munchupaiboon
Data visualization is one of the important factors that influence human cognitive. There are several factors to gain a comprehension from the readers such as model, color, and shape. To implement this project, we redesign two graphswhichbased on the data sets of Cancer Types Grouped by Race and Ethnicity 2012 andCancer Death Ranking by State 2012.The original data sets arecollected from the Centers for Disease Control and Prevention and National Cancer Institute.The data were accessed on April 2, 2016.
1. Cancer Types Grouped by Race and Ethnicity 2012
Flaws of the original design
As illustrated in Fig.1, the tableshows the information of cancer rate categorized by cancer types and races. We found that the table can represent the value of the cancer rates on each types and races. However, it might be difficult to see the tendency of the cancer rate or the comparison between each race.
Figure 1: Original design of Cancer Types Grouped by Race and Ethnicity by using table
Redesign concept
Rather than showing the data using the table,the redesign version is represented by using the plot as illustrated in Fig.2. We use ggplot() to create theperceptual groups and connecting dots. The datais divided into two groupsand connected using lines, which is long enough to compare the shapes withanother panel. The simplicity of the shapes makes the comparison fast and easy to remember the value when compare the data points. Moreover, blue color has added advantage of being colorblind friendly and help the reader to focus on each data point.A small white dot on the top of blue dot helps to identify the obvious value on each data point.The light gray background with white line that divide the panels in the graph help the reader see the data points obviously. We improve the labeling by providing the title, type of cancer, and type of race in order to give more information of the graph.
Figure 2: Redesign the graph of Cancer Types Grouped by Race and Ethnicity by creating perceptual groups and connecting dots.
2. Cancer Death Ranking by State 2012, Male and Female, all cancer sites combined
Flaws of the original design
As illustrated in Fig.3, the original design used bar chart to represent the Cancer Death Ranking by State 2012 and female and male death rate as illustrated in Fig.4 and Fig.5, this design might be difficult to compare thecancer rates between genders. Using the same color on each bar make it difficult for the readers to distinguish the value of each state. Moreover, the list of states in the bar chart is too long when comparing the value between each state if the state is far away from each other,this design may confuse the readers while reading the chart.
Figure 3: Original design of Cancer Death Ranking by State by using bar chart
Figure 4: Original design of Cancer Death rate of female using bar chart /
Figure 5: Original design of Cancer Death rate of male using bar chart
Redesign concept
As illustrated in Fig.6,We use Micromap to redesign the original version. By using the Micromap, we can separate the data into two sections by showing the overall cancer death rates and the comparison of cancer death rates between genders. By using Micromap, we can sort the value from the lowest to the highest, which helps the readers to see the tendency of the death rates and easily compare the rates between each state. The perceptual grouping and the distinctive color of each data point help the reader to focus on the points within the panels.In the gender rate panels are demonstrated by using centered stacked barswiththe hue and tint colors to make the comparison of the death rates between genders. The highlighted states on each block help the reader to see the position of the stateon the map. We provide the label of the title, type of gender, and list of stateto give the description more information of the graph.
Figure 6: Redesign the graph of Cancer Death Ranking by State by using Micromap
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