We have built this transaction and expenditure analyser as people often do not often realise and lose track of how their money is spent. Spending aggregates and this eats into their monthly income. We aim to make the users more aware about their financial decision making quality.
Our project has been built entirely using Python. We have created our data sets with consumer expenditures and transactions. Using numpy we have calculated an ideal amount they should spend based on their past transactions. Further we have created graphs displaying users total expenditure as well as their savings in a given year.
Once we have read a list of transactions from a CSV file we analyse each individual transaction and give it a smart score which measures how sensible that transaction was. This score is calculated using a function which takes the necessity and how much they spent on this transaction relative to others.
Initially we were not very familiar with Git but over time we improved our collaboration skills. We did spend a lot of time generating our data sets and figuring out how to analyse transactions.
We are happy with what we achieved in our small diverse team of 3 especially in the short time frame. Given more time we would like to provide users more information so that they can increase their savings rate as well as make better financial decisions.
Built With
- matplot
- matplotlib
- pdfpages
- python
- tkinter
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