gic-calculator 2.0.4

CalculateGIC interets and payout with comparison and plots.

gic_calculator

Summary

Project Summary

This project involves developing a Python package designed to assist users in understanding and analyzing the financial returns from Guaranteed Investment Certificates (GICs). This link explains what a GIC is in more detail. The package focuses on calculating the interest returns over different investment periods, comparing these returns, and providing a visual representation of the differences. This utility will be particularly useful for investors and financial advisors who need to make informed decisions regarding GIC investments.

Website: https://gic-calculator.readthedocs.io/en/latest/

Functions Included in the Package

interest_calc(principal, term_length, gic_rate=None): Calculates the interest earned on a GIC after a specified number of years.

calculate_gic_difference(term_length_n1, term_length_n2, principal, interest_rate1=None, interest_rate2=None): Calculates the difference in total returns (interest + principal) of a GIC between two different investment periods.

gic_plotting(principal, term_lengths, gic_rates=None): Generates a bar plot to visually represent the difference in returns as calculated by interest_calc.

Fit into the Python Ecosystem

There are several Python packages focused on financial calculations and investment analysis, such as numpy-financial or pandas, which are used for a wide range of financial computations and data analysis. However, a specialized package focusing exclusively on GIC investment analysis, particularly one that compares returns over different investment periods and visualizes these comparisons appears to be unique. This package would thus fill a niche for those specifically interested in GIC investments.

By providing targeted functionality, the proposed package offers a more user-friendly and focused approach for individuals specifically dealing with GIC investments, setting it apart from more general financial analysis tools.

Contributors

gic_calculator was created by Tony Shum(@tonyshumlh), Ruocong Sun (@sungg888), Alysen Townsley (@AlysenTownsley).

Installation

1. Clone this GitHub repository down to your local computer.

2. Create and activate a virtual environment using conda

$ conda create --name <your-env-name> python=3.9 poetry -y
$ conda activate <your-env-name>

3. Navigate to the root directory of the package and install the package

$ poetry install

Usage

gic_calculator can be used to calculate interest accrual on a GIC of varying term lengths or GIC rates, as follows:

from gic_calculator.interest_calculator import interest_calc
interest_calc(5000, 1)
interest_calc(5000, 1, 5.5)

gic_calculator can be used to calculate the difference in total return (interest + principal) of a GIC between two different investment periods, as follows:

from gic_calculator.gic_difference import calculate_gic_difference
calculate_gic_difference(1, 3, 5000)
calculate_gic_difference(1, 3, 5000, 5.5, 3.5)

gic_calculator can be used to create a bar plot to visually represent the difference in returns as calculated by interest_calc, as follows:

from gic_calculator.gic_plotting import gic_plotting
gic_plotting(5000, [1, 3])

Developer notes

Tests

We have included tests and test data for functions used in our analysis in the tests folder. The test suite can be run at the root directory of the project using the pytest command below:

pytest tests/*

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

gic_calculator is licensed under the terms of the MIT license.

Credits

gic_calculator was created with cookiecutter and the py-pkgs-cookiecutter template.

References

1. Jacob VanderPlas, Brian Granger, Jeffrey Heer, Dominik Moritz, Kanit Wongsuphasawat, Arvind Satyanarayan, Eitan Lees, Ilia Timofeev, Ben Welsh, and Scott Sievert. Altair: interactive statistical visualizations for python. Journal of open source software, 3(32):1057, 2018.
2. Guido Van Rossum and Fred L. Drake. Python 3 Reference Manual. CreateSpace, Scotts Valley, CA, 2009. ISBN 1441412697.
3. Krekel et al., pytest 7.4, 2004. https://github.com/pytest-dev/pytest
4. TD Canada Trust. (n.d.). What is a GIC? Retrieved January 30, 2024, from https://www.td.com/ca/en/personal-banking/personal-investing/products/gic/what-is-a-gic
5. D'Andrea et al., DSCI 524: Collaborative Software Development Course Notes, 2022. https://pages.github.ubc.ca/MDS-2023-24/DSCI_524_collab-sw-dev_book/materials/lectures/
6. Choosealicense.com. (n.d.). Licenses. Retrieved February 2, 2024, from https://choosealicense.com/licenses/
7. Creative Commons. (n.d.). License Chooser. Retrieved February 2, 2024, from https://chooser-beta.creativecommons.org/