# The Exclusive Differences Between Discrete and Continuous Data

Data engineers often get data from multiple sources for analysis. Understanding whether data is discrete or continuous helps them provide solid insights.

1. What’s the difference? Discrete Vs. Continuous data

## What’s the difference? Discrete Vs. Continuous data

Here are the differences between these two data.

### Discrete data

What is discrete data? Maybe you might not hear about it. In data science, it’s usual. Discrete data is a set of values that you can count.

#### Best example of discrete data

• For instance, Discrete data can “reasonably” fit in a drop-down list of values. So a list of 500 values is discrete since the count is known and fixed.
• So the data you can count is discrete, and the opposite is not discrete. It’s a simple tip to remember the concept. Also, the discrete data are limited. That means countable.

### Continuous data

The continuous data is measured. The temperature, humidity, and barometric pressure are considered continuous data. Currency is also treated as continuous, even though there is a measurable difference between two consecutive values. The smallest unit of currency for U.S. currency is one penny, which is 1/100th of a dollar (accounting-based measurements use the “mil,” which is 1/1,000th of a dollar).

#### Best example of continues data

The best example of continuous data is Continuous data types can have subtle differences. For example, someone who is 200 centimeters tall is twice as tall as someone who is 100 centimeters tall; the same is true for 100 kilograms versus 50 kilograms. However, the temperature is different: 80 degrees Fahrenheit is not twice as hot as 40 degrees Fahrenheit.[You can see industry temperatures]

For instance, values for stock prices are discrete: they must differ by at least a penny (or some other minimal unit of currency), which is to say, it’s meaningless to say that the stock price changes by one-millionth of a penny. However, since there are “so many” possible stock values, it’s treated as a continuous variable. The same comments apply to car mileage, ambient temperature, barometric pressure, etc.

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## Author: Srini

Experienced software developer. Skills in Development, Coding, Testing and Debugging. Good Data analytic skills (Data Warehousing and BI). Also skills in Mainframe.