SpendDash

SpendDash is a free online dashboard that allows you to keep track of your spending habits over time.
The live version of the app can be found here.
A backup is hosted here.

Introduction

SpendDash is an online dashboard designed to show how your expenses change over time, on a monthly or daily basis. At a glance, you can see whether your latest expenses are on the rise or on the decline when compared to your usual monthly average. Furthermore, if you have labelled your expenses as belonging to certain categories, you can compare the monthly averages for each category over a period, or look up the expenses for only certain categories.

Written in R (4.3.2) with the Shiny framework. Tested on Google Chrome v121.

Instructions

  • Open the app
  • The app starts up using sample data. Load your own via the Read data from file button
  • Change between daily and monthly view using the Days and Months buttons.
  • Change the timespan of expenses used in calculations using the Start date and End date panes in the sidebar.
  • Specify categories of expenses to use by clicking on the checkboxes in the Categories pane in the sidebar. By default, all the categories found in the data are used.

The initial layout uses sample data, which is taken from this Kaggle dataset.

Using your own data

For using your own data, you can either construct the data yourself (you can use this example Excel workbook as a starting point) or adapt data you acquired from other sources. E.g. if you can download your financial data from your bank’s services or a finance tracking app, just make sure the column names are the same as described below and you’re good to go!
Supported filetypes: .xlsx and .csv.

Valid data should look similar to this:
Data separated into Date, Amount, Category columns.

The file must contain columns named “Date” and “Amount” to be properly loaded. If a column called “Category” also exists, features related to charting and selecting individual categories will be enabled. The dashboard will accommodate any category found in the data, they are not restricted to those shown for sample data.

Privacy

Any data you upload can be viewed only by you and is deleted at the end of the session. No persistent storage accomodates user privacy.

Closing words

Comments and feature requests are welcome. Feel free to open a GitHub issue. The GitHub page provides a more detailed README and up-to-date development information. If you find the application useful, consider buying me a coffee and supporting development.