Python Variable Types

Variables are the reserved memory locations to keep values. This explains that you reserve little space in memory when you any variable. 

The interpreter allocates memory on the basis of the data type of a variable and selects what is possible to store in the reserved memory. Therefore, by assigning various data categories to variables, you can store all integers, decimals or characters in these variables.

Assigning Values to Variables

The explicit declaration is not required to Python variables to reserve memory space. When you refer a value to a variable, the declaration happens automatically. You can assign values to variables with the help of equal sign (=).

The operand to the left of the = operator indicates the name of the variable while the operand to the right of the = operator indicates the value stored in the variable. For instance −


counter = 100          # An integer assignment
miles   = 1000.0       # A floating point
name    = "John"       # A string

print counter
print miles
print name

In this example, 100, 1000.0 and "John" are the values assigned to countermiles, and name variables, respectively. This generates the following result −


Multiple Assignment

Python permits you to allocate a single value to numerous variables simultaneously. For instance −

a = b = c = 1

In this example, an integer object is created with the value 1, and all three variables (a, b, c) are assigned to the same memory location. It is also possible to assign multiple objects to multiple variables. For instance −

a,b,c = 1,2,"john"

Here, two integer objects with values 1 and 2 are allocated to variables a and b respectively, and one string object with the value "john" is assigned to the variable c.

Standard Data Types

The data stored in memory can be of various types. For instance, a person's age is stored as a numerical value and his or her address is stored as alphanumeric characters. Python has various standard data categories that are used to explain the operations possible on them and the storage method for each of them.

Python has five standard data categories which are as follows −

Python Numbers

Number data types store only numeric values. When you assign a value to them, number objects are created.. For instance −

var1 = 1
var2 = 10

You can also delete the reference to a number object with the help of the del statement. The syntax of the del statement is as follows-

del var1[,var2[,var3[....,varN]]]]

You can delete a single object or multiple objects with the help of del statement. To exemplify:

del var
del var_a, var_b

Python supports four distinct numerical categories −

  • int (signed integers)
  • long (long integers, they can also be expressed in octal and hexadecimal)
  • float (floating point real values)
  • complex (complex numbers)


Let's discuss, some illustrations of numbers as follows −

int long float complex
10 51924361L 0.0 3.14j
100 -0x19323L 15.20 45.j
-786 0122L -21.9 9.322e-36j
080 0xDEFABCECBDAECBFBAEl 32.3+e18 .876j
-0490 535633629843L -90. -.6545+0J
-0x260 -052318172735L -32.54e100 3e+26J
0x69 -4721885298529L 70.2-E12 4.53e-7j
  • Python permits you to use a lowercase l with long, but it is suggested that you use only an uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase L.

  • A complex number contains an ordered pair of real floating-point numbers expressed as x + yj, where x and y are the real numbers and j is the imaginary unit.

Python Strings

Strings in Python are identified as a contiguous set of characters expressed in the quotation marks. Python permits for either pair of single or double quotes. Subsets of strings can be taken with the help of slice operator ([ ] and [:] ) with indexes starting at 0 at the beginning of the string and working their way from -1 at the end.

The plus (+) sign is the string concatenation operator while the asterisk (*) is the repetition operator. For instance −


str = 'Hello World!'

print str          # Prints complete string
print str[0]       # Prints first character of the string
print str[2:5]     # Prints characters starting from 3rd to 5th
print str[2:]      # Prints string starting from 3rd character
print str * 2      # Prints string two times
print str + "TEST" # Prints concatenated string

This will generate the following result −

Hello World!
llo World!
Hello World!Hello World!
Hello World!TEST

Python Lists

Lists are the most versatile of Python's compound data categories. A list consists of items distinguished by commas and enclosed within square brackets ([]). To some level, lists are similar to arrays in C. One difference between them is that all the items belonging to a list can be of separate data categories.

The values stored in a list can be accessed with the help of slice operator ([ ] and [:]) with indexes starting at 0 at the beginning of the list and working their way to end -1. The plus (+) sign is the list concatenation operator while the asterisk (*) is the repetition operator. For instance −


list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
tinylist = [123, 'john']

print list          # Prints complete list
print list[0]       # Prints first element of the list
print list[1:3]     # Prints elements starting from 2nd till 3rd 
print list[2:]      # Prints elements starting from 3rd element
print tinylist * 2  # Prints list two times
print list + tinylist # Prints concatenated lists

This generates the following result −

['abcd', 786, 2.23, 'john', 70.2]
[786, 2.23]
[2.23, 'john', 70.2]
[123, 'john', 123, 'john']
['abcd', 786, 2.23, 'john', 70.2, 123, 'john']

Python Tuples

A tuple is another sequence data type which is similar to the list. A tuple contains a number of values distinguished by commas. Unlike lists, however, tuples are enclosed within parentheses.

Particular differences between lists and tuples are: Lists are enclosed in brackets ( [ ] ) and their elements and size are changeable, while tuples are enclosed in parentheses ( ( ) ) and cannot be updated again. Tuples can be thought of as read-only lists. For instance −


tuple = ( 'abcd', 786 , 2.23, 'john', 70.2  )
tinytuple = (123, 'john')

print tuple           # Prints complete list
print tuple[0]        # Prints first element of the list
print tuple[1:3]      # Prints elements starting from 2nd till 3rd 
print tuple[2:]       # Prints elements starting from 3rd element
print tinytuple * 2   # Prints list two times
print tuple + tinytuple # Prints concatenated lists

This generates the following result −

('abcd', 786, 2.23, 'john', 70.2)
(786, 2.23)
(2.23, 'john', 70.2)
(123, 'john', 123, 'john')
('abcd', 786, 2.23, 'john', 70.2, 123, 'john')

The following code is not valid with a tuple, as we attempted to update a tuple, which is not allowed. A similar case is possible with the following lists −


tuple = ( 'abcd', 786 , 2.23, 'john', 70.2  )
list = [ 'abcd', 786 , 2.23, 'john', 70.2  ]
tuple[2] = 1000    # Invalid syntax with tuple
list[2] = 1000     # Valid syntax with list

Python Dictionary

Python's dictionaries are similar to a hash table type. They work like associative arrays or hashes found in Perl and contains key-value pairs. A dictionary key can be almost any Python type but are commonly numbers or strings. On the other hand, Values can be any arbitrary Python object.

Dictionaries are enclosed by curly braces ({ }) and values can be assigned and accessed using square braces ([]). For instance −


dict = {}
dict['one'] = "This is one"
dict[2]     = "This is two"

tinydict = {'name': 'john','code':6734, 'dept': 'sales'}

print dict['one']       # Prints value for 'one' key
print dict[2]           # Prints value for 2 key
print tinydict          # Prints complete dictionary
print tinydict.keys()   # Prints all the keys
print tinydict.values() # Prints all the values

This generates the following result −

This is one
This is two
{'dept': 'sales', 'code': 6734, 'name': 'john'}
['dept', 'code', 'name']
['sales', 6734, 'john']

Dictionaries do not contain any concept of order among elements. It is incorrect to say that the elements are "out of order"; they are simply unordered.

Data Type Conversion

Sometimes, you may need to perform conversions among the built-in types. To convert between types, you basically use the type name as a function.

There are numerous built-in functions to perform the conversion from one data type to another. These functions return a new object expressing the converted value.

Sr.No. Function & Explanation

int(x [,base])

Converts x to an integer. base indicates the base if x is a string.


long(x [,base] )

Converts x to a long integer. base indicates the base if x is a string.



Converts x to a floating-point number.


complex(real [,imag])

Generate a complex number.



Converts object x to a string representation.



Converts object x to an expression string.



Check out a string and returns an object.



Converts s to a tuple.



Converts s to a list.



Converts s to a set.



Designs a dictionary. d must be a sequence of (key,value) tuples.



Converts s to a frozen set.



Converts an integer to a character.



Converts an integer to a Unicode character.



Converts a single character to its integer value.



Converts an integer to a hexadecimal string.



Converts an integer to an octal string