Net worth dashboard Python package

Introduction

Example

A driver file can be as simple as:

import networthdash as nwd
cfg = nwd.Config(
    csv = "nwd_example.csv" ,
    datefmt = "%Y-%m-%d",
    born_yr = 1981 ,
    retire_age = 67 ,
)
nwd.dashboard(cfg)

With a CSV data file which looks like:

          ,Shares, Cash,  Super,    Expend,Income,  Income,  Income
Date      ,  VDHG,Daily,SuperSA, BuyShares,   Pay,Dividend,Interest
2022-01-01,  2750, 7500, 100000,      2750,  8000,        ,     375
2022-02-01,  5984, 6694, 100889,      2750,  8000,     138,     335
2022-03-01,  9139, 7616, 101778,      2750,  8000,        ,     381
...
2024-10-01,151402, 2972, 130223,      3250,  8500,        ,     149
2024-11-01,163005, 3326, 131167,      3250,  8500,    7570,     166
2024-12-01,167117, 3962, 132111,      3250,  8500,        ,     198

(you would create/edit this file in a CSV editor.)

This produces the following:

Example of the Net Worth Dashboard.

Sell it to me

Once you start taking finances seriously, it becomes clear quickly that you need to keep track of certain things over time. The amount in your savings account from month to month; the income from stock market dividends; growth of income from year to year; and so on. Often it makes sense to compare some of these metrics against each other.

If you're anything like me, you might have dabbled in a few ways to do this: a spreadsheet like Microsoft Excel, Apple Numbers, or Google Sheets; some other kind of online service or proprietary app. For me, none of these options grabbed me. Vendor lock-in can be a long term problem, and data accessibility is important. Despite their increasing power, spreadsheets are still hard to create really top-notch dashboards in. Complex labelling and analysis is nigh impossible in a dynamic sense.

My solution is to keep all data that you want to track in a single CSV file. Yes, there are a lot of columns, but it is very easy to update and edit. Unlike a spreadsheet, there's no way to accidently break formulae by changing entries incorrectly, or adding rows/columns. The CSV data can be easily and robustly postprocessed into a dashboard, and the data remains available for other tools without need for exporting. This package uses matplotlib and ausankey to do this.

The long term intention is to provide a suite of customisations. For now much of the dashboard is hard-coded for my own needs.

Getting started

I use iOS to develop and use this code. I am unaffiliated with but recommend the following apps for doing so:

To run this package on your phone, the most transferrable approach across platforms and apps is as follows. Download or clone the repository in a standard location for the app. Both networthdash and ausankey are designed to be run directly out of their repo code. So let's say we are using Pythonista on iPhone. You might have:

iCloud Drive/Pythonista 3/
    mynetworth.csv
    mynetworth.py
    ausankey/
    networthdash/

Put your financial data into mynetworth.csv and construct your own driver file mynetworth.py based on the example provided.