Data Science II - Types of Data

Data is defined as a collection of facts, numbers, words, observations or other useful information.

This definition can be very broad in its scope. It is important to understand the data we are working with so that we can solve our problem in the most efficient manner. That's where data types enters the picture.

So in order to better understand data it has been divided into 2 broad categories. These are - Qualitative (Categorical) and Quantitative (Numerical).

Qualitative or Categorical Data

Data that represents information that is not in the form of numbers is called qualitative or categorical data. It focuses on characteristics and concepts.

Examples of qualitative data are:

Customer feedback about a restaurant (e.g., "The service was excellent," "The food was too spicy").
Types of flowers in a garden (e.g., roses, tulips, sunflowers).

Qualitative data can be further classified into Nominal and Ordinal data.

Nominal Data

Nominal data is data that is represented by names. Nominal data cannot be ranked or ordered. Some examples are:

Eye color: Blue, Brown, Green
Types of fruit: Apple, Banana, Orange
Car brands: Toyota, Honda, Ford

Ordinal Data

Ordinal data is data that consists of categories than can be ordered or ranked.

Some examples are:

Education level: High School, Bachelor's, Master's, PhD
Customer satisfaction: Very Unsatisfied, Unsatisfied, Neutral, Satisfied, Very Satisfied
Movie ratings: 1 star, 2 stars, 3 stars, 4 stars, 5 stars

Now that we learned about qualitative data, lets take a look at quantitative data.

Quantitative or Numerical Data

Data that is represented in the form of numbers is called quantitative or numerical data.

Examples of quantitative data are:

The number of students in a classroom (e.g., 25, 30, 18).
Heights of individuals (e.g., 5’8”, 172 cm, 6’2”)

Quantitative data can be further classified into Discrete and Continuous data.

Discrete data

Discrete data is the data that uses discrete values or single values. They are countable and cannot be fractions. Examples are:

Number of students in a classroom: 25, 30, 35
Number of cars in a parking lot: 10, 20, 50
Number of books on a shelf: 3, 7, 12

Continuous data

Continuous data is data that consists of a range of numbers. The variable can have any number in the range of values. Examples are:

Height of a person: 170.2 cm, 182.5 cm
Weight of an object: 12.3 kg, 45.7 kg
Temperature: 36.5°C, 98.6°F

Understanding these data types helps us analyze, interpret, and solve problems effectively. The next time you encounter data in your day to day life try to see if you can figure out if it is categorical or numerical.