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Data Handling - Chapter:8

Data Handling - Chapter:8

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Computers

11th Grade

Hard

Created by

Farveen banu

Used 13+ times

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13 Slides • 0 Questions

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Data Handling - Chapter:8

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Chapter - 8

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Topics :

  • ​Introduction

  • ​Data Types

  • ​Mutable and Immutable

  • ​Operators

  • ​Expressions

  • ​Introduction to Python Standard Library Modules

  • ​Debugging

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​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 .

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​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.​

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​Numbers

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​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

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​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

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​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.

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​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

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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)

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​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.​

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  • 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)

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  • 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​

Data Handling - Chapter:8

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Chapter - 8

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