Data visualization aims to make it easy for users and stakeholders to infer values from complex data and ultimately make data-driven decisions. This involves being able to accurately represent the story your data tells. To do this, you must understand the two components of data visualization — the data itself and the plane of representation. This is because the size of this plane, in other words, the scale, drastically affects your audience’s perception of any data charts. In this case, the value you’ll infer from a given chart is as good as your choice of scale. So, which scale is suitable for your data type? Linear vs. logarithmic?
In this article, you’ll learn the difference between linear and logarithmic scales. And which you should use for your data. But before we dive into all that, let’s define the scale. What exactly is a scale, and how does it impact your chart’s perception?
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How To Define Scale?
A scale is a set of values or numbers that indicate certain intervals on a chart or graph for measurement. Data visualization involves representing data sets in pixels. However, the values in any data set cannot all correspond to pixel measurements. Scales provide a way to represent data values as new pixel values. For example, let’s assume the following data set represents the number of unique customers that walk into a supermarket each month. Var NumberOfCustomers = [ 1000, 2000, 3000, 4000, 5000 ] We can see that the supermarket records 1000 additional customers each month. Business is flourishing! But what if we want to showcase this success using a pie chart or a bar chart? Without scales, we’ll be using data values as display values. In other words, the bar chart for the first month would be 1000 pixels tall. Your users would require screens, at least the size of your largest data value (in pixels), to see the height of each bar. This is where scales play a crucial role of visualizing our data values. Scales affect charts the same way, regardless of their real-world application. In a stock chart, a trader’s interpretations or inferred values largely depend on the price scale used during analysis. There are different types of scales; however, we’ll be discussing the two most common scale types, particularly for measuring price movement — linear and logarithmic scales.What Is Linear Scaling?
Another name for the linear price scale is the arithmetic chart. It does not plot price movements according to their percent change. Rather, the linear scale represents each unit change with a constant unit value. Because each value change is constant, the linear price scale is easy to understand. This makes it the most common of the two price scales discussed in this article. The listed prices on a linear scale, mainly on the y-axis—vertical—side of the chart, are equidistant. Also, a linear scale results in a linear graph. And, being a linear chart means having a constant slope. In other words, each unit price change remains constant, irrespective of the price the change occurs.What Is Logarithmic Scaling?
Logarithmic scales are used in charts and graphs for two main reasons.- To represent changes or skewness due to large data values in a dataset. For instance, where some values are larger than the majority within a dataset.
- To represent the percent rate of change over time or a multiplicative factor.