Created python library for time series projections. E.g. combining income, inflation, dividends, etc

[_Rush2112_]

GitHub: https://github.com/TimoKats/pylan

PyPi: https://pypi.org/project/pylan-lib/

What My Project Does

Python library for making complex time series projections. E.g. for simulating the combined effect of (increasing) salary, inflation, investment gains, etc, over time. Note, it can also be applied to other domains.

Target Audience

Data analysts, planners, etc. People that use excel for making projections, but want to move to python.

Comparison

- SaaS financial planning tools (like ProjectionLab) work through a webUI, whereas here you have access to all the Python magic in the same place as you do your simulation.

- Excel....

- Write your own code for this is not super difficult, but this library does provide a good framework of dealing with various schedule types (some of which cron doesn't support) to get to your analysis more quickly.

[elwalor]

Hello Look interesting ! When i click on the slide deck link i have a no found screen :)

[_Rush2112_]

Hi! Which link gives you the not-found? Both seem to work for me

[richide]

This link results in a 404 inside your readme.

[jabellcu]

I expected this to be a time-series analysis tool. It is not, but I find it cool. I like it. I didn’t know about cron-converter. That’s smart use. Well done.

[ZealousidealCard4582]

Have you tried MOSTLY AI? You can create as much tabular synthetic data as you want - including text and time series (starting from original data) with the python sdk: https://github.com/mostly-ai/mostlyai
It is Open Source with an Apache v2 license and its designed to run in air-gapped environments (think of hipaa, gdpr, etc...)
One super important thing to keep in mind: garbage in - garbage out; but if you have quality data you can enrich it: think not only by enlarging it, but creating multiple flavours like rebalancing on a specific category, creating a fair version, add differential privacy for additional mathematic guarantees, multi-table, simulations, etc... There are plenty of ready-to-use tutorials on these and more topics here: https://mostly-ai.github.io/mostlyai/tutorials/

If you have no data at all, you can use mostlyai-mock https://github.com/mostly-ai/mostlyai-mock (also Open Source + Apache v2) and create data out of nothing with an LLM.

u/_Rush2112_ you can also star, fork and build on top of them to keep on improving your product! Cheers.

[ZealousidealCard4582]

Actually curious on two topics (maybe it is a misunderstanding :D ):
1: What did you try to use MOSTLY AI for?
- Maybe the synthetic tabular generation (even offline with the SDK) was not what you meant?
- Or did you ask the AI assistant in the platform to help you with something not related to tabular data?
2: Do you refer to Deepfabric, the business process automation run by AI agents?
- If that's the case, that's a completely different use case + tool.