Python Numbers Types:integers,floating and complex

x = 10
y = 5
print(x + y) # Output: 15
print(x - y) # Output: 5
print(x * y) # Output: 50
print(x / y) # Output: 2.0
print(x % y) # Output: 0

Using Floating-point numbers in python 

Floating-point numbers are represented by the float data type in Python. You can perform arithmetic operations on floats using the same operators as for integers:

x = 3.14
y = 2.5
print(x + y) # Output: 5.64
print(x - y) # Output: 0.64
print(x * y) # Output: 7.85
print(x / y) # Output: 1.256
print(x % y) # Output: 0.64

Using Complex numbers in python

Complex numbers are represented by the complex data type in Python.

You can create a complex number by specifying its real and imaginary components using the syntax a + bj, where a is the real part and b is the imaginary part:

z = 2 + 3j
print(z.real) # Output: 2.0
print(z.imag) # Output: 3.0
print(abs(z)) # Output: 3.605551275463989

You can perform arithmetic operations on complex numbers using the same operators as for integers and floats:

z1 = 2 + 3j
z2 = 1 - 2j
print(z1 + z2) # Output: (3+1j)
print(z1 - z2) # Output: (1+5j)
print(z1 * z2) # Output: (8-1j)
print(z1 / z2) # Output: (-0.4+1.6j)

Built-in functions in python

Python provides several built-in functions for working with numbers. For example, you can use the round() function to round a floating-point number to a specified number of decimal places:

x = 3.14159265359
print(round(x, 2)) # Output: 3.14

You can use the abs() function to get the absolute value of a number

x = -10
print(abs(x)) # Output: 10

You can use the pow() function to raise a number to a power:

x = 2
y = 3
print(pow(x, y)) # Output: 8

You can use the min() and max() functions to find the minimum and maximum values in a set of numbers:

x = [1, 2, 3, 4, 5]
print(min(x)) # Output: 1
print(max(x)) # Output: 5

Converting between data types in python

You can convert a number from one data type to another using type conversion functions like int(), float(), and complex(). For example:

x = 10
y = float(x)
z = complex(x)
print(y) # Output: 10.0
print(z) # Output: (10+0j)

Using mathematical functions from the math module in python

The math module provides a wide range of mathematical functions that can be used to perform complex calculations. To use the functions in the math module, you need to import it first using the import statement. For example:

import math

x = 3.14
print(math.sin(x)) # Output: 0.0015926529164868282
print(math.exp(x)) # Output: 23.103866858722185
print(math.sqrt(25)) # Output: 5.0

Working with large numbers in python

Python supports arbitrary-precision integers, which means that you can work with extremely large numbers without worrying about overflow errors. For example:

x = 2**100
print(x) # Output: 1267650600228229401496703205376

Using external libraries for numerical computation in python

Python has several external libraries that are specifically designed for numerical computation, such as NumPy and SciPy. These libraries provide highly optimized functions for working with arrays, matrices, and other numerical data structures. For example:

import numpy as np

x = np.array([1, 2, 3, 4])
y = np.array([5, 6, 7, 8])
print(x + y) # Output: [ 6 8 10 12]
print(x * y) # Output: [ 5 12 21 32]

These are just a few examples of how to use numbers in Python.

The language offers a wide range of features and functions for working with numerical data, making it a versatile tool for scientific computing and data analysis.

Formatting output in python

• You can use the format() method to format the output of numerical values.
• This can be useful for rounding values or displaying them in a specific format.

For example:

x = 3.14159
print("{:.2f}".format(x)) # Output: 3.14
print("{:.4f}".format(x)) # Output: 3.1416
print("{:.2e}".format(x)) # Output: 3.14e+00

Working with fractions in python

• Python provides a built-in Fraction class in the fractions module for working with rational numbers.
• This can be useful for avoiding floating-point precision errors when working with decimal values.

For example:

from fractions import Fraction

x = Fraction(3, 4)
y = Fraction(1, 3)
print(x + y) # Output: 13/12
print(x * y) # Output: 1/4

Using the decimal module in python

• The decimal module provides a Decimal class for working with decimal values.
• This can be useful for precision calculations where floating-point rounding errors can cause issues.

For example:

from decimal import Decimal

x = Decimal('0.1')
y = Decimal('0.2')
z = x + y
print(z) # Output: 0.3

Using bitwise operators in python

• Python provides several bitwise operators for working with binary values.
• These operators include & (bitwise AND), | (bitwise OR), ^ (bitwise XOR), ~ (bitwise NOT), << (bitwise left shift), and >> (bitwise right shift).

For example:

x = 0b1010
y = 0b1100
print(bin(x & y)) # Output: 0b1000
print(bin(x | y)) # Output: 0b1110
print(bin(x ^ y)) # Output: 0b0110
print(bin(~x)) # Output: -0b1011

These are just a few more examples of how to use numbers in Python. With its wide range of features and capabilities, Python is a powerful language for working with numerical data.

Using the random module in python

The random module provides functions for generating random numbers. This can be useful for generating test data or for simulations.

For example:

import random

x = random.random() # Generate a random number between 0 and 1
print(x)

y = random.randint(1, 10) # Generate a random integer between 1 and 10
print(y)

z = random.choice(['apple', 'banana', 'cherry']) # Choose a random element from a list
print(z)

Using the statistics module in python

The statistics module provides functions for calculating statistical values such as the mean, median, and standard deviation.

For example:

import statistics

data = [1, 2, 3, 4, 5, 6, 7, 8, 9]
mean = statistics.mean(data)
median = statistics.median(data)
stdev = statistics.stdev(data)

print(mean) # Output: 5
print(median) # Output: 5
print(stdev) # Output: 2.7386127875258306

Using the math module for trigonometry in python

The math module provides functions for performing trigonometric calculations.

For example:

import math

x = math.sin(math.pi/2)
y = math.cos(math.pi/4)
z = math.tan(math.pi/3)

print(x) # Output: 1.0
print(y) # Output: 0.7071067811865476
print(z) # Output: 1.7320508075688772

Using the math module for logarithmic and exponential functions

The math module provides functions for performing logarithmic and exponential calculations.

For example:

import math

x = math.log(10)
y = math.log10(100)
z = math.exp(2)

print(x) # Output: 2.302585092994046
print(y) # Output: 2.0
print(z) # Output: 7.3890560989306495

These are just a few more examples of how to use numbers in Python. With its vast collection of built-in modules and third-party libraries, Python is a versatile language for working with numerical data.

Using the numpy module in python

The numpy module provides powerful numerical computing tools for working with arrays and matrices.

For example:

import numpy as np

x = np.array([1, 2, 3])
y = np.array([4, 5, 6])
z = np.dot(x, y)

print(z) # Output: 32

Using the pandas module in python

The pandas module provides tools for working with data in a tabular format.

This can be useful for cleaning and analyzing data sets.

For example:

import pandas as pd

data = {'name': ['omar', 'Gogo', 'Adam'], 'age': [18,13, 5]}
df = pd.DataFrame(data)
print(df)

Output:

name            age
0 omar         18
1 Gogo         13
2 Adam        5

Using the sympy module for symbolic mathematics in python

• The sympy module provides tools for performing symbolic mathematics.
• This can be useful for solving equations and simplifying expressions.

For example:

import sympy

x = sympy.Symbol('x')
y = sympy.Symbol('y')

expr = (x + y)**2
simplified_expr = sympy.simplify(expr)

print(simplified_expr)

Output:

x**2 + 2*x*y + y**2