When many people hear “data,” they immediately picture large tables full of numbers like the excerpt shown in Figure 7-1. Numerical data sits at the heart of most analysis; therefore, being confident and comfortable with numbers is key to successfully preparing data for analysis and sharing. In this chapter we will cover considerations for using numerical data.
Figure 7-1. Normal table of data
What Do We Mean by Numbers?
If only we could just think about 0, 1, 2, 3, 4, 5, 6, 7, 8, 9. These numerals form the basis for using numbers in data analysis, but it’s much more complex than that. Your analyses will often focus on numerical questions, such as:
What is my total sales?
How many staff work in our organization?
How many customers have we sold to?
What percent of suppliers have billed us?
As discussed in earlier chapters, we commonly call these numbers the measures of our data. Analyses will typically compare these measures or break them down by categories to give them more context.
Types of Numbers
There are two types of numbers:
Integer
Whole numbers (i.e., those without decimal places) such as 4 and 16,874
Decimal/float
Numbers with decimal places such as 3.1415 and 0.31
Category or Measure?
Numerical data is often used as a category, or dimension, instead of a measure. Customer IDs (identifiers) are a classic example of numerical ...
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