Combining 2 different datasets

Hi everybody,

I am quite a beginner in the statistics world, but I am struggling with some data

I have 2 datasets:
- one with ID's (each subject has a different ID), groups (there are several subjects in one group) and some characteristics of these individuals (e.g. weight, growth, etc.)
- one with climate data (each group is observed for three months, with climate data collection every 10 minutes. So each group has 90 days* 144 datapoints per day = +/- 13,000 datapoints per group). It is important to state that the groups can have overlapping data, furthermore not each group was observed for exactly 90 days, but the observation time varies around 90 days. To make this more clear, an example:
group one: 12-3-2022 till 18-6-2022
group two: 16-4-2022 till 7-7-2022
group three: 1-1-2022 till 24-3-2022

Both datasets are rather big: lets say 7000 ID's (an 70 groups) and almost one million climate data points. And these datasets will continue to grow.

I want to work with my data in Python, but cannot really figure out what is the best way to combine my datasets without losing any data (e.g. taking the average temperature of the whole observation period).
I reckon I just have to work with 2 different datasets where I recall a certain group (because that is the only common demoninator between the both datasets). However, I want to combine my whole dataset (and not just one group at a time) and look at the relations between weight/growth/etc and climate.
Does anybody know how to solve this issue?

I really hope the text above is clear enough and someone can help me

Thanks in advance!

P.S. I unfortunatelly cannot share my dataset due to it being sensitive and private data.