Pattern - 2

    
1111111111
2222222222
3333333333
4444444444

5555555555
6666666666
7777777777
8888888888
9999999999

Code 1:

1 2 3 4 5

n=int(input("Enter the number of rows: ")) for j in range(1,n+1): for i in range(1,n+1): print(j,end=" ") print()

Pattern-1

  

Code 1:

1 2 3 4 5

n=int(input("Enter the number of rows: ")) for j in range(1,n+1): for i in range(1,n+1): print("*",end='') print()

Code 2:

1 2 3

n=int(input("Enter the number of rows: ")) for j in range(1,n+1): print('*' * n)

How to draw patterns using Python?

Data types in Python- Lecture 3

float data type:

We can use float data type to represent floating point values (decimal values)

Eg:

f=1.234

type(f)

<class ‘float’>

We can also represent floating point values by using exponential form (scientific notation)

Eg:

f=1.2e3

print(f)

1200.0 instead of 'e' we can use 'E'

The main advantage of exponential form is we can represent big values in less memory.

***Note: We can represent int values in decimal, binary, octal and hexadecimal forms. But we can represent float values only by using decimal form.

Eg:

>>> f=0B11.01

File "<stdin>", line 1

f = 0B11.01

^

SyntaxError: invalid syntax

>>> f=0o123.456

SyntaxError: invalid syntax

 >>> f=0X123.456

SyntaxError: invalid syntax

Complex Data Type:

A complex number is of the form a and b contain integers or floating point values

Eg:

3+5j

10+5.5j

0.5+0.1j

In the real part if we use int value then we can specify that either by decimal,octal,binary or hexadecimal form. But imaginary part should be specified only by using decimal form.

 >>> a=0B11+5j

 >>> a

 (3+5j)

 >>> a=3+0B11j

 SyntaxError: invalid syntax

Even we can perform operations on complex type values.

 >>> a=10+1.5j

 >>> b=20+2.5j

 >>> c=a+b

 >>> print(c)

 (30+4j)

 >>> type(c)

 <class 'complex'>

Note: Complex data type has some inbuilt attributes to retrieve the real part and imaginary part

c=10.5+3.6j

c.real--->10.5

c.imag--->3.6

We can use complex type generally in Scientific Applications and Electrical engineering Applications.

 

Data type in Python-Lecture 2

int data type:

We can use int data type to represent whole numbers (integral values)

Eg:

a=10

type(a) #int

Note:

In Python2, we have long data type to represent very large integral values. But in Python3 there is no long type explicitly and we can represent long values also by using int type only.

We can represent int values in the following ways

1. Decimal form

2. Binary form

3. Octal form

4. Hexadecimal form

1. Decimal form(base-10):

It is the default number system in Python. The allowed digits are: 0 to 9

Eg: a =10

2. Binary form(Base-2):

The allowed digits are: 0 & 1 Literal value should be prefixed with 0b or 0B

Eg: 

a = 0B1111 

a =0B123 

a=b111

3. Octal Form(Base-8):

The allowed digits are: 0 to 7 Literal value should be prefixed with 0o or 0O.

Eg: 

a=0o123

a=0o786

4. Hexa Decimal Form(Base-16):

The allowed digits are: 0 to 9, a-f (both lower and upper cases are allowed) Literal value should be prefixed with 0x or 0X

Eg: a =0XFACE a=0XBeef a =0XBeer

Note: Being a programmer we can specify literal values in decimal, binary, octal and hexa decimal forms. But PVM will always provide values only in decimal form.

a=10

b=0o10

c=0X10

d=0B10

print(a)10

print(b)8

print(c)16

print(d)2

Base Conversions

Python provide the following in-built functions for base conversions

1. bin():

We can use bin() to convert from any base to binary

Eg:

>>> bin(15)

'0b1111'

>>> bin(0o11)

'0b1001'

>>> bin(0X10)

'0b10000'

2. oct():

We can use oct() to convert from any base to octal

Eg:

>>> oct(10)

'0o12'

>>> oct(0B1111)

 '0o17'

 >>> oct(0X123)

'0o443'

3. hex():

We can use hex() to convert from any base to hexadecimal

Eg:

>>> hex(100)

'0x64'

>>> hex(0B111111)

'0x3f'

>>> hex(0o12345)

      '0x14e5'