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Types of Data

It is necessary to understand the different types of data we are dealing with to choose the right visualization technique or statistical measure for our data.

In this blog post, we’ll discuss two types of data

  • Numerical and
  • Categorical

Let’s start with the numerical data


It is also called as quantitative data. Numerical data have values that represent counts or measurements such as weights of people. These data are quantifiable.

Numerical data can be divided into two continuous and discrete data.


Continuous data can take an infinite number of values within a finite or infinite interval. These data cannot be counted but can be measured.

For example, the weight of a person could be any value within the human weights range. 


The other type of numerical data is discrete. Discrete data cannot be measured but can be counted. For example, the number of students in a class.


It is also called qualitative data. It generally describes categories or groups, such as gender.

This type of data has no inherent numeric meaning. But that doesn’t mean that it can’t have numerical.

For example, it can take values like 1 for male and 0 for female; however, that doesn’t have any numerical meaning.

Categorical data is further divided into nominal and ordinal data.


The nominal data is described by name or category. It has no order and quantitative value to its categories.

Primary examples include nationality, the color of the iris of the human eye, or gender.


Unlike nominal data, ordinal data provides us with rank order.

There is some kind of natural order in the values of the ordinal data. Even though ordinal data provides rank order, it cannot be quantified.

One good example of ordinal data is ratings for a movie. Say that we have to rate a film between 1 and 5. 

We know that a rating of five is better than four, but we cannot quantify how better it is.


In this blog post, we discussed two types of data numerical and categorical.

Numerical data are quantifiable. Numerical data have values that represent counts and measurements.

It is divided into two types discrete and continuous data.

Categorical data generally describes categories or groups, such as gender. These types of data do not have any inherent numeric meaning.

It has two types nominal and ordinal data.

The nominal data has no order, while the ordinal data provides some rank order.

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