Álgebra with python

My programming BootCamp certificate: FreeCodeCamp

These projects represent the culmination of my university-level Algebra course, incorporating Python programming to apply theoretical concepts in practical computational implementations. Through these endeavors, I have synthesized mathematical knowledge gained throughout the course into tangible algoritmic solutions, fostering a deeper understanding of both algebraic principles and programming methodologies. This integration of mathematical theory with computational tools has not only enriched my academic experience but also equipped me with valuable skills for real-world problem-solving in mathematical modeling and analysis.

Technologies Used: Python 3.11 - Jupyter Lab (IDE) for testing - VSCode (IDE) for structuring each algorithm.

Libraries: pandas, numpy, SimPy, and matplotlib.

Project Description:

All projects are represented as .ipynb files created in Google Colab, and at the end of each notebook is the final project, which incorporates all essential aspects learned in the topic.

Algebraic Calculator

This project contains a series of functions that perform basic algebraic and mathematical operations, as well as functions to detect prime numbers, generate prime factors of a number, and simplify the square root. Available operations include addition, subtraction, multiplication, and division, along with solving linear equations and prime number detection. Additionally, it provides the capability to generate the prime factors of a given number and simplify the square root of a number. The program interacts with the user through a selection menu and prompts for the necessary input to perform the desired operation.

Graphic Polynomials Calculator.ipynb

This project contains a series of functions to perform algebraic and graphical operations. It includes the ability to display a graph and a table of values for any equation of the form y = f(x), solve a system of two equations, graph two equations and show their point of intersection, and find and graph the vertex of a quadratic equation. The program interacts with the user through a selection menu and prompts for the necessary input to perform the desired operation.

Three Math Games

This projects contains three different games:

1. Scatter Plot Game: The game generates random points on a Cartesian plane, and the player must input coordinates (x, y) to try to get close to one of the generated points.

2. Algebra Practice Game: In this game, random equations with one or two variables and random coefficients are generated, and the player must solve them to find the value of the unknown variable.

3. Simple Projectile Game: The player must adjust the angle and velocity of a projectile to try to overcome a wall of random height and position. If the projectile reaches a distance greater than or equal to the position of the wall, the player wins.

Financial Calculator

This project contains a program that offers the user four options related to financial calculations:

1. Mortgage Payment: Calculates the monthly payment of a mortgage given the borrowed amount, annual interest rate, and number of years.

2. Investment Balance: Calculates the balance of an investment after a certain number of years, considering an initial amount, annual interest rate, and additional monthly contributions.

3. Time to Double Money: Determines the time needed for a sum of money to double with continuous growth, given an initial amount and an annual interest rate.

4. Rates of Growth: Calculates the future value of an investment compounded annually, compounded multiple times a year, and compounded continuously, given the principal, interest rate, time, and number of times compounded per year.

Graphic Polynomials Calculator

This project parses an XML file containing data on drug overdose death rates in the United States. It uses the requests library to fetch the XML file content from a URL and xml.etree.ElementTree to parse and structure the XML data. Then, it uses pandas to create a DataFrame with the data and display the first rows of the DataFrame. Additionally, basic data analysis is performed afterward, and more visualizations of the obtained data are created.

Conclusión

This "Algebra with Python" repository is a testament to my passion for learning, my ability to integrate theoretical concepts with practical applications, and a demonstration of commitment to continuous improvement. It is a valuable resource for both students and professionals interested in exploring the intersection between algebra and programming with Python.