- Python 3 - Exceptions
- Python 3 - Files I/O
- Python 3 - Modules
- Python 3 - Functions
- Python 3 - Date & Time
- Python 3 - Numbers
- Python 3 - Loops
- Python 3 - Decision Making
- Python 3 - Basic Operators
- Python 3 - Variable Types
- Python 3 - Basic Syntax
- Python 3 - Environment Setup
- Python 3 - Overview
- What is New in Python 3
- Python 3 - Home
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Python 3 Advanced Tutorial
- Python 3 - Further Extensions
- Python 3 - GUI Programming
- Python 3 - XML Processing
- Python 3 - Multithreading
- Python 3 - Sending Email
- Python 3 - Networking
- Python 3 - Database Access
- Python 3 - CGI Programming
- Python 3 - Reg Expressions
- Python 3 - Classes/Objects
Python 3 Useful Resources
- Python 3 - Discussion
- Python 3 - Useful Resources
- Python 3 - Tools/Utilities
- Python 3 - Quick Guide
- Python 3 - Questions and Answers
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Python 3 - Variable Types
Variables are nothing but reserved memory locations to store values. It means that when you create a variable, you reserve some space in the memory.
Based on the data type of a variable, the interpreter allocates memory and decides what can be stored in the reserved memory. Therefore, by assigning different data types to the variables, you can store integers, decimals or characters in these variables.
Assigning Values to Variables
Python variables do not need exppcit declaration to reserve memory space. The declaration happens automatically when you assign a value to a variable. The equal sign (=) is used to assign values to variables.
The operand to the left of the = operator is the name of the variable and the operand to the right of the = operator is the value stored in the variable. For example −
#!/usr/bin/python3 counter = 100 # An integer assignment miles = 1000.0 # A floating point name = "John" # A string print (counter) print (miles) print (name)
Here, 100, 1000.0 and "John" are the values assigned to counter, miles, and name variables, respectively. This produces the following result −
100 1000.0 John
Multiple Assignment
Python allows you to assign a single value to several variables simultaneously.
For example −
a = b = c = 1
Here, an integer object is created with the value 1, and all the three variables are assigned to the same memory location. You can also assign multiple objects to multiple variables. For example −
a, b, c = 1, 2, "john"
Here, two integer objects with values 1 and 2 are assigned to the 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 many types. For example, a person s age is stored as a numeric value and his or her address is stored as alphanumeric characters. Python has various standard data types that are used to define the operations possible on them and the storage method for each of them.
Python has five standard data types −
Numbers
String
List
Tuple
Dictionary
Python Numbers
Number data types store numeric values. Number objects are created when you assign a value to them. For example −
var1 = 1 var2 = 10
You can also delete the reference to a number object by using the del statement. The syntax of the del statement is −
del var1[,var2[,var3[....,varN]]]]
You can delete a single object or multiple objects by using the del statement.
For example −
del var del var_a, var_b
Python supports three different numerical types −
int (signed integers)
float (floating point real values)
complex (complex numbers)
All integers in Python3 are represented as long integers. Hence, there is no separate number type as long.
Examples
Here are some examples of numbers −
int | float | complex |
---|---|---|
10 | 0.0 | 3.14j |
100 | 15.20 | 45.j |
-786 | -21.9 | 9.322e-36j |
080 | 32.3+e18 | .876j |
-0490 | -90. | -.6545+0J |
-0x260 | -32.54e100 | 3e+26J |
0x69 | 70.2-E12 | 4.53e-7j |
A complex number consists of an ordered pair of real floating-point numbers denoted by x + yj, where x and y are real numbers and j is the imaginary unit.
Python Strings
Strings in Python are identified as a contiguous set of characters represented in the quotation marks. Python allows either pair of single or double quotes. Subsets of strings can be taken using the spce operator ([ ] and [:] ) with indexes starting at 0 in the beginning of the string and working their way from -1 to the end.
The plus (+) sign is the string concatenation operator and the asterisk (*) is the repetition operator. For example −
#!/usr/bin/python3 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 produce the following result −
Hello World! H llo llo World! Hello World!Hello World! Hello World!TEST
Python Lists
Lists are the most versatile of Python s compound data types. A pst contains items separated by commas and enclosed within square brackets ([]). To some extent, psts are similar to arrays in C. One of the differences between them is that all the items belonging to a pst can be of different data type.
The values stored in a pst can be accessed using the spce operator ([ ] and [:]) with indexes starting at 0 in the beginning of the pst and working their way to end -1. The plus (+) sign is the pst concatenation operator, and the asterisk (*) is the repetition operator. For example −
#!/usr/bin/python3 pst = [ abcd , 786 , 2.23, john , 70.2 ] tinypst = [123, john ] print (pst) # Prints complete pst print (pst[0]) # Prints first element of the pst print (pst[1:3]) # Prints elements starting from 2nd till 3rd print (pst[2:]) # Prints elements starting from 3rd element print (tinypst * 2) # Prints pst two times print (pst + tinypst) # Prints concatenated psts
This produces the following result −
[ abcd , 786, 2.23, john , 70.200000000000003] abcd [786, 2.23] [2.23, john , 70.200000000000003] [123, john , 123, john ] [ abcd , 786, 2.23, john , 70.200000000000003, 123, john ]
Python Tuples
A tuple is another sequence data type that is similar to the pst. A tuple consists of a number of values separated by commas. Unpke psts, however, tuples are enclosed within parenthesis.
The main difference between psts and tuples are − Lists are enclosed in brackets ( [ ] ) and their elements and size can be changed, while tuples are enclosed in parentheses ( ( ) ) and cannot be updated. Tuples can be thought of as read-only psts. For example −
#!/usr/bin/python3 tuple = ( abcd , 786 , 2.23, john , 70.2 ) tinytuple = (123, john ) print (tuple) # Prints complete tuple print (tuple[0]) # Prints first element of the tuple print (tuple[1:3]) # Prints elements starting from 2nd till 3rd print (tuple[2:]) # Prints elements starting from 3rd element print (tinytuple * 2) # Prints tuple two times print (tuple + tinytuple) # Prints concatenated tuple
This produces the following result −
( abcd , 786, 2.23, john , 70.200000000000003) abcd (786, 2.23) (2.23, john , 70.200000000000003) (123, john , 123, john ) ( abcd , 786, 2.23, john , 70.200000000000003, 123, john )
The following code is invapd with tuple, because we attempted to update a tuple, which is not allowed. Similar case is possible with psts −
#!/usr/bin/python3 tuple = ( abcd , 786 , 2.23, john , 70.2 ) pst = [ abcd , 786 , 2.23, john , 70.2 ] tuple[2] = 1000 # Invapd syntax with tuple pst[2] = 1000 # Vapd syntax with pst
Python Dictionary
Python s dictionaries are kind of hash-table type. They work pke associative arrays or hashes found in Perl and consist of key-value pairs. A dictionary key can be almost any Python type, but are usually numbers or strings. Values, on the other hand, can be any arbitrary Python object.
Dictionaries are enclosed by curly braces ({ }) and values can be assigned and accessed using square braces ([]). For example −
#!/usr/bin/python3 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 produces the following result −
This is one This is two { name : john , dept : sales , code : 6734} dict_keys([ name , dept , code ]) dict_values([ john , sales , 6734])
Dictionaries have no concept of order among the 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 between the built-in types. To convert between types, you simply use the type-names as a function.
There are several built-in functions to perform conversion from one data type to another. These functions return a new object representing the converted value.
Sr.No. | Function & Description |
---|---|
1 | int(x [,base]) Converts x to an integer. The base specifies the base if x is a string. |
2 | float(x) Converts x to a floating-point number. |
3 | complex(real [,imag]) Creates a complex number. |
4 | str(x) Converts object x to a string representation. |
5 | repr(x) Converts object x to an expression string. |
6 | eval(str) Evaluates a string and returns an object. |
7 | tuple(s) Converts s to a tuple. |
8 | pst(s) Converts s to a pst. |
9 | set(s) Converts s to a set. |
10 | dict(d) Creates a dictionary. d must be a sequence of (key,value) tuples. |
11 | frozenset(s) Converts s to a frozen set. |
12 | chr(x) Converts an integer to a character. |
13 | unichr(x) Converts an integer to a Unicode character. |
14 | ord(x) Converts a single character to its integer value. |
15 | hex(x) Converts an integer to a hexadecimal string. |
16 | oct(x) Converts an integer to an octal string. |