University of Kwazulu-Natal

Building A Personal Finance Tracker In Python

Bonisiwe Shabane
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building a personal finance tracker in python

Managing personal finances is more than just tracking income and expenses. As your financial situation grows more complex, you may need a more sophisticated tool to keep track of investments, budgets, savings goals, and financial forecasting. In this blog, we’ll walk through building an advanced personal finance tracker using Python. This script will not only track your transactions but also provide insights into your spending patterns, help you set and achieve savings goals, and even predict your future financial status. Using matplotlib and plotly for interactive visualizations. Implementing budgeting and savings goals.

Financial forecasting with time series analysis. In addition to pandas and matplotlib, we’ll use plotly for interactive charts and statsmodels for financial forecasting. Building a personal finance tracker with Python and SQLite is an essential project for anyone looking to manage their finances effectively. It allows users to track their income, expenses, savings, and investments in a centralized and organized manner. In this tutorial, we will guide you through the process of building a personal finance tracker using Python and SQLite. We will cover the technical background, implementation guide, code examples, best practices, testing and debugging, and conclude with key takeaways and further learning resources.

Before diving into the implementation, let’s discuss the core concepts and terminology involved in building a personal finance tracker. The personal finance tracker will consist of three main tables: When a user creates a new transaction, the system will insert a new record into the transactions table. The system will also update the corresponding account balance in the accounts table. This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules. Currently, two official plugins are available:

Managing personal finances can feel like a daunting task. With bills, savings, investments, and unexpected expenses, it’s easy to lose track of where your money goes. Fortunately, technology can help simplify this process. By building a personal finance tracker using Python, you can gain better control over your finances and make informed decisions. This article will guide you through the steps to create your own finance tracker, complete with code snippets and explanations. Python is a versatile programming language that is easy to learn and use.

It has a rich ecosystem of libraries that can help you manage data, perform calculations, and even visualize your financial information. Whether you are a beginner or an experienced programmer, Python provides the tools you need to create a functional finance tracker. Before you start coding, you need to set up your development environment. Here’s what you’ll need: Before jumping into the code, it’s important to outline what features you want in your finance tracker. Here are some basic functionalities you might consider:

Let’s start by creating a simple structure for our finance tracker. We will use a CSV file to store our data. Here’s how to set it up: Python is a very powerful programming language, and I've made a lot of projects in it. From Amazon price trackers to Spotify recommenders, it can do a bunch of different things, and my most recent project has been to build a financial dashboard that can graph data from a CSV. It trracks expenditure, savings, and expenditure per category, and it can give you a quick overview of your spending month to month.

Naturally, there are a ton of options out there that you can use, including many templates in Excel. However, this is one that you completely control, and you can modify it pretty easily if you're proficient with Python. I do a lot of data analysis in Python, because it's a powerful programming language with some great, easy to use modules for analysis and graphing. On top of that, Flask is a module that you can use to host websites in Python, and you can combine those graphing modules with Flask to insert graphs into a webpage when it... For this project, I used Flask and I created a basic Material Design page where I could upload a CSV file split into date, category, and the amount of expenditure. It then groups that expenditure into both a month and into categories, showing the total amount earned, spent, saved, and then how much was spent in individual categories.

This data is then graphed using Plotly, as it's a browser-based graphing library that you can easily insert into webpages. From there, images are inserted into the HTML template from the CSV the user submits, and it can give an overview of all of your spending habits. I created a sample CSV for analysis to show it works, using randomized income and expenditure values, which in turn changed the amount in savings, too. Finally, an average is calculated for how much of your income is going to savings. Personal budget tracker is used to manage your income and expenses. Here, we will create personal budget tracker in Python using different approaches.

Dictionaries are the most convenient form of working with sets of values, therefore, our income and expenses will be managed in the same manner. This method makes it easy for us to classify our financial data and normal tasks such as entry of new data, computation of totals and preparation of summary can be done effortlessly. We create two dictionaries: one for income and one for expenses. Every type (like "Salary" or "Rent") is key in the dictionary, and the every corresponding amount is the value. This allows us to categorize and sum our income and expenses easily. The script prints out a summary of all income and expenses, along with the total income, total expenses, and net savings (income minus expenses).

We implement OOP principles into our budget tracker in order to improve its modularity. In other words, it helps to organize the data and the functionality into an easily understandable form and easily reuse them. This approach also facilitates easy management, modification and scalability in future hence meets the modern learning institution’s needs. Intro: Morning! Another simple project under my belt and could be under yours! With the tutorial guidance of Tim from Tech with Tim at: Youtube Link I was able to program a personal finance tracker.

This project used a csv file to store transactions from the terminal line with pandas and uses matplotlib to plot the data for you to see. This is a great project for python beginners looking to explore popular libraries! Project: The program prompts users to enter transaction details such as date, amount, category (Income or Expense), and description, which are then stored in a CSV file. Users can view a summary of their income, expenses, and net savings for any given period, and generate plots to see trends and patterns in their financial data. The project was both challenging and rewarding. Validating user inputs to ensure data integrity, handling CSV files for data storage, and creating meaningful visualizations were some of the key tasks.

This experience highlighted the importance of robust input validation, efficient data handling, and the power of data visualization in understanding financial habits. To Do: This project and concept is a great base to make something bigger! Ideas I can think of is making a simple GUI that implements the original functions, or perhaps creating a django site. You could add more functionalities. The sky's the limit. Lesson: Following projects is a great tool for learning, but working on your own idea or building off an idea yourself is equally important.

I will work off this project and be back to share my creation. In addition, following these projects are crucial for building a greater computer science background and experience. I plan to learn about webscraping, ai chatbots, and django with youtube. Following different topics through videos extends your knowledge a ton and can allow you to start thinking of ways to connect them all. Youtube is the best.

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