Python Numbers Helper

In our previous tutorial on datatypes, we gained a basic understanding of Python Numbers. Now, get ready to take a deep dive into the captivating world of Python numbers. We’re going to cover everything you need to know about handling numbers in Python, ensuring that you have a solid foundation to conquer any numerical challenge that comes your way. So, let’s dive right in and explore Python numbers together!

What are Python numbers?

Python numbers refer to the data types and operations used for working with numerical values in the Python programming language. Python numbers come in different flavors. The primary numeric data types are integers, floating-point numbers, and complex numbers, along with various operations and functions for performing mathematical calculations..

Let’s take a closer look at each of them and explore how they work.

I. Integers

Integers are whole numbers, both positive and negative, without any decimal points. They are used in a variety of scenarios, from counting items to performing mathematical operations and representing discrete quantities. Imagine you have a group of friends and each of them owns a certain number of cats. Let’s see how Python integers can help us count the total number of cats:

Example Code
alice_cats = 3 bob_cats = 5 charlie_cats = 2 total_cats = alice_cats + bob_cats + charlie_cats print("The total number of cats is:", total_cats)

In above example, we assign the number of cats owned by Alice, Bob, and Charlie to their respective variables. Then, we calculate the total number of cats by adding the individual counts together. Finally, we display the result:

The total number of cats is: 10

II. Floating-Point Numbers

Floating-point numbers, or floats, are a type of numerical data in Python that allow for precise representation of decimal values. They are used when dealing with numbers that require fractional precision or scientific notation. Understanding floats is crucial for accurate calculations involving measurements, financial data, and scientific computations. Let’s imagine we want to calculate the net worth of a popular celebrity using Python floats. We’ll use the example of Taylor Swift, a globally recognized artist known for her successful music career:

Example Code
assets = 50000000.00 liabilities = 15000000.00 net_worth = assets - liabilities print("Taylor Swift's net worth is:", net_worth)

In the code above, we assign Taylor Swift’s assets and liabilities to the respective variables. By subtracting the liabilities from the assets, we determine her net worth. The output will be:

Taylor Swift’s net worth is: 35,000,000.00

III. Complex Numbers

Complex numbers are a fascinating aspect of mathematics, and Python provides built-in support to work with them. A complex number consists of a real part and an imaginary part, represented as “a + bj,” where “a” is the real part, “b” is the imaginary part, and “j” represents the imaginary unit. Complex numbers find applications in various fields, including engineering, physics, and signal processing.

Let’s examine how to add complex numbers using Python. Consider the following two examples involving popular celebrities:

Example Code
jay_z = 5000000 + 2000000j beyonce = 4000000 - 1000000j total_wealth = jay_z + beyonce print("Our combined wealth is:", total_wealth)

In this example, we have complex numbers representing the wealth of two popular celebrities: Jay-Z and Beyoncé. By adding these complex numbers together, we obtain the total wealth of the couple. The output will be:

Our combined wealth is: (9,000,000 + 1,000,000j)

Python also provides functions to calculate the conjugate and absolute value of a complex number. Let’s use examples to demonstrate their usage:

Example Code
complex_num = 3 + 4j conjugate_num = complex_num.conjugate() print("The conjugate of", complex_num, "is:", conjugate_num)

For this example, we define a complex number 3 + 4j. By calling the conjugate() function on the complex number, we obtain its conjugate. The output will be:

The conjugate of 3+4j is: 3-4j

Now let’s Calculate the Absolute Value:

Example Code
complex_num = -5 + 12j abs_value = abs(complex_num) print("The absolute value of", complex_num, "is:", abs_value)

Above, we define a complex number -5 + 12j. By using the abs() function and passing the complex number as an argument, we calculate its absolute value. The output will be:

The absolute value of -5+12j is: 13.0

To visualize complex numbers, let’s plot a few points on the complex plane using Python. We’ll use the example of the iconic Eiffel Tower in Paris:

Example Code
import matplotlib.pyplot as plt point1 = 2 + 3j point2 = -4 + 2j point3 = 1 - 5j plt.scatter(point1.real, point1.imag, color='red', label='Point 1') plt.scatter(point2.real, point2.imag, color='blue', label='Point 2') plt.scatter(point3.real, point3.imag, color='green', label='Point 3') plt.xlabel('Real') plt.ylabel('Imaginary') plt.title('Plotting Points on the Complex Plane (Eiffel Tower)') plt.legend()

In the code above, we create three complex numbers representing points on the complex plane near the Eiffel Tower. Using the matplotlib library, we plot these points with different colors and labels. The resulting plot visualizes the locations of the points in the complex plane. Don’t worry, You’ll soon dive into the wonderful world of matplotlib in our upcoming articles. We’ll take a detailed look at this amazing library and explore all its exciting features together.

Underscores in Numbers

In Python, you can use underscores _ as visual separators within numeric values. These underscores are completely ignored by the interpreter and have no impact on the actual value of the number. Instead, they serve as visual aids to enhance readability, especially for large or complex numeric literals.

Let’s say we have a large number representing the world's population. Without underscores, it can be challenging to read and comprehend the magnitude of the value. However, by using underscores, we can make the number more manageable and easier to understand:

Example Code
world_population = 7_900_000_000 print("The current world population is approximately", world_population)

Above, we define the world population as 7_900_000_000, with underscores separating the digits into groups of three. This format helps us quickly grasp the approximate value of the world population. The output will be something like:

The current world population is approximately 7,900,000,000

Underscores can also be used in floating-point numbers to improve readability. They can be placed anywhere between digits, except at the beginning or end of the number. Let’s consider a monetary value representing a popular celebrity’s net worth. Using underscores, we can make the number more readable and easier to interpret:

Example Code
celebrity_net_worth = 1_500_000_000.75 print("The celebrity's net worth is $", celebrity_net_worth)

Above, we define the celebrity’s net worth as 1_500_000_000.75, with underscores separating the digits for clarity. By using underscores, we make it easier to identify the major digits and the decimal portion. The output might be:

The celebrity’s net worth is $1,500,000,000.75

Python Random Numbers

Random numbers play a vital role in various applications, from games and simulations to cryptography and statistical analysis. Python provides a robust random number generation module that allows you to generate pseudo-random numbers using different algorithms. These numbers appear random and are crucial for introducing unpredictability and variability into your programs.

Example: Rolling the Dice Let’s kick things off with a classic example involving a popular game – rolling dice. Imagine we’re in the vibrant city of Las Vegas, and we want to simulate rolling two six-sided dice:

Example Code
import random dice1 = random.randint(1, 6) dice2 = random.randint(1, 6) print("We rolled a", dice1, "and a", dice2)

Above, we import the random module and use the randint() function to generate random integers between 1 and 6, simulating the roll of two dice. We then display the results using friendly and conversational language. The output will be something like:

We rolled a 3 and a 6

Python random numbers can use with functions to make random choices from a list of items. This can be handy when you want to introduce variability or simulate random selection scenarios. Let’s imagine you’re planning a dream vacation and need some inspiration. We have a list of popular vacation destinations and want to randomly select one using Python:

Example Code
import random destinations = ["Maldives", "Bora Bora", "Santorini", "Maui", "Bali"] chosen_destination = random.choice(destinations) print("Our next vacation spot is", chosen_destination)

In this example, we import the random module and create a list of popular vacation destinations. Using the choice() function, we randomly select one destination from the list and display it with a friendly message.

Python random numbers also allows you to shuffle elements within a list. Let’s shuffle a deck of cards and display a few random cards from the shuffled deck:

Example Code
import random cards = ["Ace", "2", "3", "4", "5", "6", "7", "8", "9", "10", "Jack", "Queen", "King"] random.shuffle(cards) random_cards = random.sample(cards, 5) print("Our random cards are:", random_cards)

For this example, we import the random module again and create a list representing a deck of cards. By using the shuffle() function, we randomly shuffle the order of the cards. Then, we use the sample() function to select five random cards from the shuffled deck. The output could be something like:

Our random cards are: [‘Ace’, ‘8’, ‘Jack’, ‘2’, ‘King’]

What is 1e 5 in Python?

In Python, 1e5 is a way to represent a number using scientific notation. Specifically, 1e5 represents the number 1 multiplied by 10 raised to the power of 5, which is equal to 100,000.

Here’s an example of how 1e5 can be used in Python:

Example Code
number = 1e5 print(number)

When you run this code, it will output 100000, which is the numerical value represented by 1e5.

Scientific notation is commonly used to express large or small numbers in a concise and readable format. The e in 1e5 stands for exponent, and the number following it indicates the power of 10 by which the base number (in this case, 1) is multiplied. In the case of 1e5, the base number 1 is multiplied by 10 raised to the power of 5.

How do you write 10 3 in Python?

To express 10 to the power of 3 in Python, you can use the double asterisk operator ** to perform exponentiation. Here’s an example:

Example Code
result = 10 ** 3 print(result)

In this code, 10 ** 3 calculates 10 raised to the power of 3, which equals 1000. The result is stored in the result variable. When you run this code, the output will be:


In conclusion, Python Numbers offer a diverse range of data types and operations for working with numerical values in the Python programming language. By understanding these concepts, you are equipped with the tools to tackle any numerical challenge that comes your way.

We explored the different types of Python numbers, including integers, floating-point numbers, and complex numbers. We saw how integers can be used for counting and performing mathematical operations, while floats are essential for precise calculations involving decimal values. Complex numbers, with their real and imaginary parts, find applications in various fields. We also learned how to calculate the conjugate and absolute value of complex numbers and even plotted points on the complex plane using matplotlib.

We also discovered a handy technique in Python numbers: using underscores in numbers. By using underscores as visual separators within numeric values, we can enhance readability, especially for large or complex numbers. This technique can be applied to both integers and floating-point numbers, making it easier to comprehend their magnitude.

With this newfound knowledge and a solid understanding of Python Numbers, you are well-prepared to embark on exciting numerical adventures and unleash the full potential of Python in your programming endeavors. So, embrace the power of numbers and continue your journey into the captivating world of Python!

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