Data classification is a process in which graduated numeric values are grouped into ranges and each classification range is represented by a shade or color on a color ramp. Classification is available for data clocks and heat charts.
The classification method that you use depends on the data you're using and the information you want to convey on the chart.
Natural breaks
Natural breaks classification creates classes based on natural groupings inherent in the data. This is the default classification.
Use the natural breaks classification when you want to emphasize the natural groupings in the data. For example, use natural breaks to compare the crime rates for a city across months and years using a data clock. The crime rates will be grouped so that months and years with a similar crime rate will be symbolized with the same color.
Do not use natural breaks to compare charts created with different data.
Equal interval
Equal interval classification divides the range of attribute values into equal-sized subranges.
The equal interval classification emphasizes the amount of an attribute relative to other values. Use equal interval for data that has familiar ranges. For example, use equal intervals to compare the percentage of different species of trees with invasive beetles across parks in a county using a heat chart. The percentages range is from 0 to 100. If you use four bins, the classes will be based on 25 percent intervals.
Quantile
Quantile classification divides the attributes into bins with equal numbers of features.
The quantile classification can distort the look of a chart by placing similar values in different classes. Use quantile classification for data that is relatively uniform. You can also use quantile classification for visual ranking. For example, use quantile intervals to compare the unemployment rates across states in the United States by year using a heat chart. If you apply five bins to the 50 states and the District of Columbia, there will be approximately 10 states per bin. The results can be used to see the unemployment rates ranked in groups of 10.
Manual
Manual classification adds custom class breaks that are appropriate for your data.
Manual classification can be used to create new class breaks or modify the breaks created using a different classification method. For example, you may classify the data using equal intervals, then use manual classification to modify the breaks to round numbers.
Use the manual classification when there are known ranges that must be applied to the data, such as when creating multiple charts with the same bins. For example, use the manual classification to compare the average housing rental cost by month and year for different neighborhoods using a data clock. You can apply the same bins to all charts so that patterns and comparisons can be made without making false assumptions due to differences in the classification.
Resources
Use the following resources to learn more: