Presenting visual data – compiling inclusions and exclusions

Visual selection – the essential details

The selected visual represents an approximated summary of the eligible votes cast in the 2015 general elections of the United Kingdom. From the chosen visual, the percentage of the votes as divided among the different parties can be seen. The visual is divided into three segments with varying colors to represent the varying categories of eligible voters. Only 25% of the votes were cast for conservative party while 42% of the votes went in for the other party. The remaining 33% of votes were not cast for any of the parties and are represented in black.

Purpose served by the visual

The chosen visual provides a clear explanation of the ratio that the various categories hold against each other. In a pie chart, the categories are represented as a portion of the circle – filling up the proportionate area that each category should have in comparison to the other categories. The prime purpose of using pie charts is to display classified data into ordinal categories. The prime purpose of this nature of visual is to represent a large set of data into a visual form. It also enables a visual check of the calculation accuracy without having to give in the exact details (Donalek et. al., 2014).

Ideal data to include for visual compilation

The ideal data sets that can be included in a pie chart include the respective components of a specific aspect that merge in together for the final results. Keeping that in mind, any range of data can be included in a pie chart as long as it is a relevant part of the subject taken under consideration. The prime purpose of a pie chart is to bring in a visual appearance to the data that would otherwise have been presented as a table. The nominal and ordinal elements are the best fits for the proportional display of the categories as a pie slice.

Data to avoid while compiling the chosen visual

As mentioned already, any data that is a component of the aspect taken under consideration can be included in a pie chart. However, it is necessary to ensure that the sector of the circle that represents the categories is proportionate and at par, with the mathematical fraction they are accountable for (Kelleher & Wagener, 2011). For example, putting in an element of 30% proportion over an area of 50% of the circle can direct make it misleading and inaccurate. Using similar color to represent varying categories must be avoided.

Ways to prevent misleading visual compilation

Misleading data is one of the biggest threats in present times. It is because most of the visual makers refrain from providing all the essential elements that must be included within the chart. At times, it is an intentional step to keep the audience in the dark while the maker lacks the skills to prepare an accurate visual (Cairo, 2015). It is essential to ensure that the maker has a firm knowledge of what they are doing and the purpose that their effort needs to serve. All the essential data, along with a consistent scale, can help to cut down data misleading to a great extent.