Visual representation and data compilation

 Visual representation and data compilation

Details of the selected visual

The selected visual representation is a line graph that constitutes two specific data about the earning of individuals against a time period from 1920 to 2010. In the chosen figure, the percentage of income growth is plotted in the Y-axis with differences of 50% marked on each line. For the X-axis, time spans of 10 years are plotted on each line. However, the visual starts abruptly from 1920 with no prior information about the income growth before that period as well as no data are provided for the time period after 2010. Two separate line charts are plotted to separate out the income growth of the top 10% from the bottom 90%.

Purpose of the visual

The primary purpose of the chosen visual is to represent the differences in the income growth of the top 10% of the earners in the US from that of the bottom 90% earners of the nation. The visual compare the earning of the two categories over a selected time period and points out the variations in the rate of income growth of the two groups. This visual can be used to identify the steadiness of the considered element for the graph or to compare the signs of progress made by the selected groups and their financial growth over the years (Kosara, 2016).

Data to be compiled in the visual

There are certain elements that must be compiled in such a visual. To begin with, the starting and ending period of the intervals must be chosen – irrespective of the scales chosen for the axis. This visual is often used to represent continuous data from a specific time frame based on a standard scale, thus revealing the data trends at specific time intervals. In general, the category data is plotted in the X-axis, while the values are evenly distributed upon the Y-axis. Once the data is compiled, providing a legible legend is a must (Fisher III, Dempsey & Marousky, 1997).

Data to be avoided in the visual

One of the primary issues that can impact a visual representation of data is the inconsistency of the axis intervals. Also, the data intervals must have a finite beginning. Adding up too much data can make it messy and hard to understand as well. In the case of these types of visuals, it is best to keep away overlapping data as much as possible. Using too many colors to make the data sets distinguishable is something that must be avoided as well.

Avoiding misleading making of the visual

The best way to ensure that a visual is not misleading is to confirm that it has all the elements necessary to explain the data to the reader (Heer & Robertson, 2007). If the reader needs the help of the maker to understand the visual, then it is not appropriate. Also, the proper markings in the X and Y axis must be provided as its absence can make the visual data illegible to the familiar eyes. In addition, it is necessary to maintain a uniform scale for the visualization and to pay attention to the accuracy of the plots made on the visual.

Reference

Fisher III, S. H., Dempsey, J. V., & Marousky, R. T. (1997). Data visualization: Preference and use of two-dimensional and three-dimensional graphs. Social Science Computer Review, 15(3), 256-263.

Heer, J., & Robertson, G. (2007). Animated transitions in statistical data graphics. IEEE transactions on visualization and computer graphics, 13(6), 1240-1247.

Kosara, R. (2016). Presentation-oriented visualization techniques. IEEE computer graphics and applications, 36(1), 80-85.