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Compound Interest in Python: Function, Calculation and Examples

Published:  at  08:00 PM

Have you ever wondered how to work magic with your money, transforming small savings into considerable fortunes over time? The answer lies in compound interest, and we are going to unravel its mystery with a Python function. ✨

🔮 Problem Statement

Maria needs a tool that allows her to visualize the growth of her investments thanks to the power of compound interest. The challenge is to create a function in Python that calculates the future value of an investment given an initial amount, an annual interest rate, and a period of time in years.

Parameters:

Return Value:

Example:

>>> compound_interes(10000, 0.1, 20) # initial capital = $10,000; annual interest = 10% = 0.1; years = 20
67275.0
>>> compound_interes(100000, 0.08, 20)
466095.71
>>> compound_interes(100000, 0.08, 30)
1006265.69

Additional Notes:

In our case, we will simplify the formula considering that interest is compounded annually (n=1).

🧩 Step-by-Step Solution

The heart of our solution lies in the direct application of the compound interest formula, adjusted for our annual case. Let’s break down each part to understand its function.

1. Function Definition:

def compound_interes(money, i, years):

Here we define the compound_interes function that will take as arguments the initial capital (money), the annual interest rate (i), and the number of years (years). This clear structure facilitates data entry and code reuse.

2. Calculation of Compound Interest:

return round(money * pow(1 + i, years), 2)

This line is the magic in action. Let’s analyze each component:

Complete Solution:

def compound_interes(money, i, years):
	"level: medium; points: 4"
	return round(money * pow(1 + i, years), 2)

🧠 Key Concepts

Compound interest is a fundamental concept in finance, and its understanding is based on the application of the power function (pow) to model exponential growth. The pow function raises a number to a specified power, simulating how interest accumulates on previously earned interest in previous periods. This exponential growth is what differentiates compound interest from simple interest, where interest is calculated only on the initial capital. 💰

The round function is equally important, although often underestimated. While internal computation can handle a high degree of precision, the presentation of financial results requires a specific granularity (usually two decimal places). round ensures that the information displayed is clear and understandable to users, avoiding information overload and potential interpretation errors.

Did you know that the pow function in Python, in addition to accepting two arguments (base and exponent), can also receive a third argument that represents the modulus? This allows you to calculate (base ** exponent) % modulus more efficiently than calculating the power and then applying the modulo operator. It is useful for cryptography and modular mathematics!

💫 Final Thoughts

This function, although simple, encapsulates a powerful financial principle. We could improve it by adding input validations (ensuring that the years are positive, for example) or extending it to handle different compounding frequencies (monthly, quarterly, etc.). It would also be interesting to integrate this function into a graphical interface so that Maria can experiment with different investment scenarios interactively.

The code we have built is a solid starting point for exploring the world of compound interest and its implications. I encourage you to experiment with different values, rates and periods to visualize the impact of time on the growth of your investments. Knowledge is power, and understanding how compound interest works is a crucial step in taking control of your financial future!

If you found this article interesting, I invite you to explore other topics on our blog. Perhaps the next article will help you optimize the performance of your code or discover a new tool to automate your tasks! See you in the next post! 👋



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