Basic Data Types in Python

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Martin Ganchev 8 Sept 2022 5 min read

The data types in Python that we will look at in this tutorial are integers, floats, Boolean, and strings.

If you are not comfortable with using variables in Python, our article on how to declare python variables can change that. Since there are many programmers who are good at math, let’s take a look at the numeric data types in Python first.

Table of Contents 

  1. Numeric Data Types in Python 
  2. Boolean Data Type in Python 
  3. String Data Type in Python 
  4. How to State Values? 
  5. Basic Data Types in Python: Next Steps 

Numeric Data Types in Python

Data types in python

When programming, if you say that a variable has a numeric value, you are being ambiguous. This is because numbers can be either integers or floats (floating points).

Data Types: Ints

Integers are positive or negative whole numbers without a decimal point. I believe in learning through doing, so let me show you what you can do with integers. Let’s create x1 and bind to it the value of 5.

Integers: positive or negative whole numbers without decimal point, data types

Now, x1 is an integer. In fact, there is a specific function in Python that can prove this is correct.  It is called type().

The type() Function

We can apply the type() function on different data types in Python following this rule. Within the brackets, we must place the name of the variable whose type of value we want to verify. So, in this case, we’ll type x1.

After executing the code, the result we obtain is “int”, which indicates the value is an integer.

x1 = 5 type (x1), data types

The type() function can also be applied directly to a value instead of a variable. For instance, if we write type(-6), Python will correctly point out that -6 is an integer.

type -6, data types

Data Types: Floats

Now, let’s assign the value of 4.75 to a new variable, x2. We can check its type by using the type() function again.

x2 = 4.75 type (x2) Float, data types

This is a float.

Floating points, or as you’ll more frequently hear - floats, are real numbers. Hence, they have a decimal point. 4.75 is such a number so Python reads it as a float.

floating points real numbers with a decimal point, data types

Let’s look at two other built-in functions, int()and float().

The int() Function

int() transforms the variable into an integer. That’s why 4.75 turns into 4 after executing the code shown in the picture.

int transforms the variable into an integer, data types

The float() Function

float(), instead, will add a decimal point to the integer or Boolean value and will turn it into a float.

float () transforms the variable into a float, data types

Boolean Data Type in Python

Not all variables should assume numeric values. An example of such type of values is the Boolean type. In Python, this means a True or False value, corresponding to the machine’s logic of understanding 1s and 0s, on or off, right or wrong, true or false. Let’s create a new variable, x3, and assign to it the value True. If we check its type with the type() function, we get the output ‘bool’. This means that x3 is a Boolean.

x3 = true type (x3) bool, data types

Side note:  An important detail you should remember is that you have to type True or False with capital letters! Otherwise, Python won’t recognize your variable as a Boolean and will display an error message.

Error, data types

So, to sum up, the two Boolean values a variable can have are True or False, and they must be written with a capital letter.

String Data Type in Python

The last example of data types in Python we will go over is string. Strings are text values composed of a sequence of characters.

Let’s see how we can create a string in practice.

If we ask the machine to display the name George this way, we’ll obtain an error message.

name 'George' is not defined

If you are wondering why, it is because Python assumes George is the name of a variable to which we have assigned no value. Here’s the magic trick that will correct this mistake.

Typing quotation marks around the name George would do the job. We can put both single or double quotation marks to achieve this result.


The output values of these two inputs are the same. This is how Python displays text results if you don’t use the print() function. Should you use print(), the output will be shown with no quotes – you’ll be able to see plain text. Basic data types in python print() function example 1

If we assign “George” to a new variable, let’s say x4, we can obtain its output as we did with the integers and floats.

x4 = george

All right, so that’s it. If the values you’d like to assign are not numerical, the quotes can come into play!

How to Print Several Strings?

Let’s create the variable y which is supposed to represent the number of dollars you have in your pocket. In addition, we would like to ask the machine to print out a statement that says: “Y dollars”, where y is a number.

The proper way to combine the value of y and the string “Dollars” is to use a “+” sign, as shown below.

print y + dollars

And to check if we are missing something, we can execute the cell.

Basic data types in python print() function example 2

Apparently, we did not respect the rules of coding in Python. We cannot put different types of variables in the same expression. Y is an integer, and “Dollars” is a string.

How to Convert Integers into Strings?

We can convert y into a string. str() is the built-in function we need. Analogically to integers and floats, str() will convert our number into text, and that will unlock our result. Basic data types in python print() function example 3

To summarize, Python can automatically guess the type of data you are entering. It is within its capabilities to know for sure whether you have assigned an integer, a float, a Boolean, or a string. You need not declare the types of variables explicitly, as you must do in some other programming languages. Python always knows the type of variable and this is yet another reason why you should program in Python.

Single vs Double Quotation

What will happen if we type something like “I’m fine”? We’ll need the apostrophe in the English syntax, not for the Pythonic one. Observe, if we execute the command like this, we will make a mistake.

I'm fine invalid syntax

To distinguish between the two symbols, let’s try putting the text within double quotes and leaving the apostrophe, which technically coincides with the single quote. I'm fine I'm fine

An alternative way to do that would be to leave the quotes on the sides and place a backslash before the apostrophe within the phrase to obtain the same result. This backslash is called an escape character, as it changes the interpretation of the characters immediately after it.

escape character

And what if we wanted to state ‘press “Enter”’, where we put Enter within inverted commas? Same logic – the outer symbols must differ from the inner ones. For instance, we can put single quotes on the sides and obtain the desired result!

press enter

How to State Values?

Finally, let’s go through a few ways of stating values. Say, we wish to print the string “Red car” on the same line. If we write it like this – two words next to each other, separated by a blank space, we’ll see them attached.


One trick would be to put a blank space before the second apostrophe of the first word.


Another technique would be to sort of “add” one of the strings to the other by typing in a plus sign between the two, just as we did with the “10-dollar” example before. red car

As your intuition probably tells you, if we print this combination instead, we’ll obtain the same outcome, but it won’t have the quotes on the two sides. Basic data types in python print() function example 4

How about we learn another trick we can do with the data types in Python? First, we can type “print ‘Red’", and then if we put a comma, which is called a trailing comma, Python will print the next word, ‘car’, on the same line, separating the two words with a blank space.

Basic data types in python print() function example 5

Let’s prove this technique works for numeric values as well. Let’s print the number 3 next to the number 5.

Basic data types in python print() function example 6

What will happen if we don’t use the print() command and just list a few integers, floats, and strings separating them with commas? Python will execute the command as expected but will place the values within parentheses. 3 5 6.9 7.0 car

How many data types does Python have?
There are four basic data types in Python:
1. Numeric: These can be either integers or floats. Integers are positive or negative whole numbers without a decimal point. Floats are real numbers with a decimal point.
2. Boolean: These are True/False values.
3. String: These are text values composed of a sequence of characters.
4. Sequence: These are collections of data types that can be the same or different. Examples include list, string, and tuples.


What are data types in Python?
Data types are used to classify data items. They tell us what operations can be performed on a particular data set. Python is unique in the way it handles data types because everything in the language is technically an object. This is why Python treats data types as classes, while it treats variables as instances (objects) of these classes.


Basic Data Types in Python: Next Steps

Now that you’ve mastered the basic data types in Python, you will be able to move on to the world of programming in Python! Provided that you want to improve your skills, you can go deeper into Python syntax. As the most popular programming language on the market, Python is the go-to coding tool for aspiring data scientists. With our extensive line-up of courses dedicated to its numerous features and operations, you can build actionable skills in the language quickly and effectively. Sign up below for free to explore our Python Programmer Bootcamp course and many others! 

Martin Ganchev

Instructor at 365 Data Science

Martin holds an MSc degree in Economic and Social Sciences from Bocconi University. His diverse academic and research experience combined with his friendly and explanatory approach to teaching have made him one of the most beloved instructors on our team. Some of the courses he has authored include: SQL, SQL + Tableau, SQL+Tableau+Python, Introduction to Python, Introduction to Jupyter, to name a few.