Python Data Types — Python Tutorial

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Variables can hold values, and every value has a data type. Python is a dynamically typed language; hence, we do not need to define the type of the variable while declaring it. The interpreter implicitly binds the value to its type.

a = 5

The variable a holds an integer value of five, and we did not define its type. Python interpreter will automatically interpret variables a as an integer type.

Python enables us to check the type of the variable used in the program. Python provides us with the type() function, which returns the type of the variable passed.

Consider the following example to define the values of different data types and check their type:

a=10  
b="Hi Python"  
c = 10.5  
print(type(a))  
print(type(b))  
print(type(c))  

Output:

<type 'int'>
<type 'str'>
<type 'float'>

Standard data types

A variable can hold different types of values. For example, a person’s name must be stored as a string, whereas its id must be stored as an integer.

Python provides various standard data types that define the storage method for each of them. The data types defined in Python are given below.

1. Numbers
2. Sequence Type
3. Boolean
4. Set
5. Dictionary

In this section of the tutorial, we will give a brief introduction to the above data types. We will discuss each one of them in detail later in this tutorial.

Numbers

A number stores numeric values. The integer, float, and complex values belong to the Python Numbers data type. Python provides the type() function to know the data-type of the variable. Similarly, the isinstance() function is used to check whether an object belongs to a particular class.

Python creates Number objects when a number is assigned to a variable. For example;

a = 5  
print("The type of a", type(a))  
  
b = 40.5  
print("The type of b", type(b))  
  
c = 1+3j  
print("The type of c", type(c))  
print(" c is a complex number", isinstance(1+3j,complex))  

Output:

The type of a <class 'int'>
The type of b <class 'float'>
The type of c <class 'complex'>
c is complex number: True

Python supports three types of numeric data.

1. Int — Integer value can be any length such as integers 10, 2, 29, -20, -150 etc. Python has no restriction on the length of an integer. Its value belongs to int
2. Float — Float is used to store floating-point numbers like 1.9, 9.902, 15.2, etc. It is accurate upto 15 decimal points.
3. complex — A complex number contains an ordered pair, i.e.., x + iy where x and y denote the real and imaginary parts, respectively. The complex numbers like 2.14j, 2.0 + 2.3j, etc.

Sequence Type

String

The string can be defined as the sequence of characters represented in the quotation marks. In Python, we can use single, double, or triple quotes to define a string.

String handling in Python is a straightforward task since Python provides built-in functions and operators to perform operations on the string.

In the case of string handling, the operator + is used to concatenate two strings, as the operation “hello" + "python” returns “hello python”.

The operator * is known as a repetition operator, as the operation “Python” *2 returns "Python Python."

The following example illustrates the string in Python.

Example — 1

str = "string using double quotes"  
print(str)  
s = '''''A multiline 
string'''  
print(s)  

Output:

string using double quotes
A multiline
string

Consider the following example of string handling:

Example — 2

str1 = 'hello javatpoint' #string str1    
str2 = ' how are you' #string str2    
print (str1[0:2]) #printing first two character using slice operator    
print (str1[4]) #printing 4th character of the string    
print (str1*2) #printing the string twice    
print (str1 + str2) #printing the concatenation of str1 and str2    

Output:

he
o
hello javatpointhello javatpoint
hello javatpoint how are you

List

Python lists are similar to arrays in C. However, the list can contain data of different types. The items stored in the list are separated with a comma (,) and enclosed within square brackets [].

We can use slice [:] operators to access the data of the list. The concatenation operator (+) and repetition operator (*) work with the list in the same way they worked with the strings.

Consider the following example:

list1  = [1, "hi", "Python", 2]    
#Checking type of given list  
print(type(list1))  
  
#Printing the list1  
print (list1)  
  
# List slicing  
print (list1[3:])  
  
# List slicing  
print (list1[0:2])   
  
# List Concatenation using + operator  
print (list1 + list1)  
  
# List repetation using * operator  
print (list1 * 3)  

Output:

[1, 'hi', 'Python', 2]
[2]
[1, 'hi']
[1, 'hi', 'Python', 2, 1, 'hi', 'Python', 2]
[1, 'hi', 'Python', 2, 1, 'hi', 'Python', 2, 1, 'hi', 'Python', 2]

Tuple

Tuples are similar to the list in many ways. Like lists, tuples also contain a collection of items of different data types. The items of the tuple are separated by a comma (,) and enclosed in parentheses ().

A tuple is a read-only data structure, as we can’t modify the size and value of the items in it.

Let’s see a simple example of the tuple.

tup  = ("hi", "Python", 2)    
# Checking type of tup  
print (type(tup))    
  
#Printing the tuple  
print (tup)  
  
# Tuple slicing  
print (tup[1:])    
print (tup[0:1])    
  
# Tuple concatenation using + operator  
print (tup + tup)    
  
# Tuple repatation using * operator  
print (tup * 3)     
  
# Adding value to tup. It will throw an error.  
t[2] = "hi"  

Output:

<class 'tuple'>
('hi', 'Python', 2)
('Python', 2)
('hi',)
('hi', 'Python', 2, 'hi', 'Python', 2)
('hi', 'Python', 2, 'hi', 'Python', 2, 'hi', 'Python', 2)

Traceback (most recent call last):
  File "main.py", line 14, in <module>
    t[2] = "hi";
TypeError: 'tuple' object does not support item assignment

Dictionary

Dictionary is an unordered set of a key-value pair of items. It is like an associative array or a hash table where each key stores a specific value. Key can hold any primitive data type, whereas value is an arbitrary Python object.

The items in the dictionary are separated with the comma (,) and enclosed in curly braces ().

Consider the following example:

d = {1:'Jimmy', 2:'Alex', 3:'john', 4:'mike'}     
  
# Printing dictionary  
print (d)  
  
# Accesing value using keys  
print("1st name is "+d[1])   
print("2nd name is "+ d[4])    
  
print (d.keys())    
print (d.values())    

Output:

1st name is Jimmy
2nd name is mike
{1: 'Jimmy', 2: 'Alex', 3: 'john', 4: 'mike'}
dict_keys([1, 2, 3, 4])
dict_values(['Jimmy', 'Alex', 'john', 'mike'])

Boolean

The Boolean type provides two built-in values: true and false. These values are used to determine whether the given statement is true or false. It is denoted by the class bool. True can be represented by any non-zero value or ‘T’ whereas false can be represented by the 0 or ‘F’. Consider the following example:

# Python program to check the boolean type  
print(type(True))  
print(type(False))  
print(false)  

Output:

<class 'bool'>
<class 'bool'>
NameError: name 'false' is not defined

Set

Python Set is the unordered collection of the data type. It is iterable, mutable (it can be modified after creation), and has unique elements. In set, the order of the elements is undefined; it may return the changed sequence of the element. The set is created by using the built-in function set(), or a sequence of elements is passed in the curly braces and separated by the comma. It can contain various types of values. Consider the following example:

# Creating Empty set  
set1 = set()  
  
set2 = {'James', 2, 3,'Python'}  
  
#Printing Set value  
print(set2)  
  
# Adding element to the set  
  
set2.add(10)  
print(set2)  
  
#Removing element from the set  
set2.remove(2)  
print(set2)  

Output:

{3, 'Python', 'James', 2}
{'Python', 'James', 3, 2, 10}
{'Python', 'James', 3, 10}