Python data types and string

Python Notes Unit 1, Part 2

UNIT – 1(part 2)

     

Introduction to Python Part 1

Introduction to Python Part 3

Introduction to Python

History and its Features

Basic Syntax

Understanding Python variables

Numeric data types

Using string data type and string operations

Basic Operators

Understanding coding blocks.

Defining list and list slicing,

Other Data Types- Tuples. List, Python Dictionary, Arrays, Associative Arrays/Hashes

 

Data types: -

    1.   The type of variable present in our code is represented by Data Types.

    2.   A data type is the classification of data items.

    3.   Data type represents the kind of value that tell what operation can perform on particular code.

    4.   Various type of data types that define the storage method on each of them.

 

Numeric data type - 

In python, three types of numeric data types

1.   Integer

2.   Float

3.   Complex number

Mainly two types of numeric data types are used in code.

                    Integer or float.

 Numeric data type represents the data that has a numeric value. This numeric value can be integer, float and complex number. These values are defined as int, float and complex classes.

 

For example – int data type

                         a=5

  print (“the type of a”, type(a))

  Output – The type of a <class ‘int’ >

 

For example – float datatype

            a = 4.5

            print (“the type of b”, type(b))

Output – The type of b <class ‘float’ >

 

 

Dictionary data type –

    1.   Dictionary data type are working as hash table type.

    2.   In dictionary data type each key are stored and indicate different value at searching time.

Boolean data type: -

    1.   Boolean data type is also a type of one of the built-in data types.

    2.   This data type is representing one of the two values.

a.    Either TRUE

b.   Or FALSE

    3.   Boolean data type is also a logical data type than can have only the values.

    4.   True and False are also used as keywords.

    5.   The keyword True and False must an Upper Case first letter if we are using lowercase true return an error.

Example –

               print(True)

               print(type(True))

               print(False)

               print(type(False))

Output –

            True

            <class ‘bool’>

            False

            <class ‘bool’>

 

Set data type: -

    1.   A set data type is collection which is unordered, unchangeable and unindexed.

    2.   Set is defined by comma inside braces { }.

    3.   Items under the set are not ordered.

Example –

                   a = {5, 2, 3, 1, 4}

                   print (“a = “, a)

                   print(type(a))

Output -  

              a= {1, 2, 3, 4, 5}

              <class ‘set’>

                 

Sequence type data type   -

1.   Sequence type data type is used to store data in containers.

2.   List, Tuple and String are the different types of containers in python programming language.

 

String: -

    1.   A string is generally considered as a data type and is often implemented as an array data structure of bytes that stores a sequence of elements, typically characters, using some character encoding.

    2.   Strings are sequences of character data.

    3.   The string type in Python is called str.

    4.      String can be considered as a special type of sequence, where all its elements are characters.

 

For example- string “Hello, World” is basically in sequence

 [‘H’,’E’,’L’,’L’,’O’,’’,, ‘ ’,’W’,’O’,’R’,’l’,’d’]

 

Declaration of strings: - 

                        >>> mystring = “This is not my first copy”

                         >>> print (mystring);

                         This is not my first copy            

List –

    1.   The list data type is a versatile data type.

    2.   In Python is list can simultaneously hold different types of data.

    3.   Formally list is an ordered sequence.

    4.   Defining a list in python is easy – just use the brackets syntax to indicate items in a list.

               List_of_ints= [1, 2, 3]

    5.   Items in a list do not have to all be the same type, either. They can be any python object.

 

Tuple –

    1.   The tuple data type is the same as List Datatype except that it is immutable, that means once we create any tuple, you cannot make any changes to that.

    2.   The tuple is a Read-only version of List, which means we cannot add, remove and replace any elements.

 The syntax for the Tuple is –

                                    Tuple=(Elements)

 

Example-          

                              Tuple= (10,20,30, “banana”)

                               Print(type(Tuple))

                         

Output - <class ‘tuple’>

 

List Slicing          

    1.   List Slicing refers to accessing a specific portion of a subset of the list for some operation while the original list remains unaffected.

    2.   The slicing operator in python can take three parameters out of which two are optional depending on the requirement.

 

Syntax of list slicing:    

                              List_name [start:stop:steps]          

    3.   The start parameter is a mandatory parameter, whereas the stop and steps are both optional parameters.

                       

    a.    The start represents the index from where the list slicing is supposed to begin. Its default value is 0, it begins from index 0.

    b.   The stop represents the last index up to which the list slicing will go on. Its default value is (length(list)-1) or the index of last element in the list.

    c.    The step represents the number of steps, i.e after every n number of steps, the start index is updated and list slicing is performed on that index, or in simple words, steps if defined, specifies the number of elements to jump over while counting from start to stop.

 

    This means we can do list slicing in three ways:

    1.   By passing just the start or stop parameter

    2.   By passing the start and stop parameter.

    3.   By passing the start, stop and steps parameters.

 

Next Part is coming soon..!! keep study and keep growing

Thank you..!!