Data Handling - Chapter:8

Data Handling - Chapter:8

​Chapter - 8

​Topics :

• ​Introduction

• ​Data Types

• ​Mutable and Immutable

• ​Operators

• ​Expressions

• ​Introduction to Python Standard Library Modules

• ​Debugging

​Introduction

• ​Python introduces the fundamentals:

  Data Types, Variables, Operators and expressions.

• Python provides a predefined set of data types for handling the data it uses.

• ​Data can be stored in any data type.

• ​Mutable and immutable variables .

​Data Types

• ​Data can be of many types.

​e.g. Character, integer, real ,

​string etc.,

• ​Python is capable to handle a specific data and the memory space it allocates to hold and the range of values supported by a data type.​

​Numbers

​Integers

• ​Integers are whole numbers.

​ e.g. 5,39,1917,0 etc.,

• They have no fractional parts.

• ​Integers are represented in Python by numeric values with no decimal point.

• ​Integers can be positive or negative.

​ e.g.+12,-15,3000

• ​Missing + or - symbol means it is positive number

​Types of Integers

​Integers(Signed)

• Represents the whole numbers​.

• ​Integers in python can bein any length.

• ​It has single Data Type "int()"

• ​It is signed representation.i.e.,the integers can be positive or negative.

​Booleans

• ​It represents True and False which represents 1 and 0.

• ​It is a subtype of integer.

• ​Data Type is "bool(0)" and "bool(1)"

• ​It returns True and False

​Floating Point Numbers

• ​A number having fractional part is a floating -point number.

​i.e.,3.14159

• ​The decimal point signals that it is a floating number not an integer.

​Floating Point Forms

​1. Fractional Form (Normal Decimal Notation)

​ e.g., 3500.75, 0.00005, 147.9101

​2. Exponent Notation

​ e.g., 3.50075E03, 0.5E-04, 1.479101E02

​

​Advantages of Floating Point Numbers

• ​They can represent values between the integers.

• ​They can represent a much greater range of values.

Disadvantages of Floating Point Numbers

• ​Floating - point operations are usually slower than integer operations.

​Note : In Python, the Floating point numbers have precision of 15 digits (double-precision)

​Complex Numbers

• ​Python represents complex numbers in the form A+Bj

• ​Python uses j or J in place of traditional i.

e.g., a=0+3.1j b=1.5+2j

• ​Here : a has the real component as 0 and imaginary component as 3.1;

• b had the real part as 1.5 and imaginary part is 2.

• Python represents complex numbers as a pair of floating point numbers.​

​

• ​Python displays complex numbers in parentheses when they have a non zero real part.

​                 

                  >>>c=0+4.5j

​                   >>>d=1.1+3.4j

                   >>>c

                   ​4.5j

​                   >>>d

                   (1.1+3.4j)

​

• ​In Python complex numbers area a composite quantity made of two parts :

              Syntax:   real part  - variable_name.real

​                imaginary part -  variable_name.imag

• ​Both are represented internally as float values.

• e.g., >>>z=(1+2.56j)+(-4-3.56j)

>>>z

(-3-1j)

>>>z.real

-3.0

>>>z

-1.0​