[Python] Train machine learning model with scikit learn for time-series prediction

I need to train a model with scikit-learn to predict possible time for less people in a room.

Here is how my dataset looks like:

Time PeopleCount
---------------------------------------------
2019-12-29 12:40:10 50
2019-12-29 12:42:10 30
2019-12-29 12:44:10 10
2019-12-29 12:46:10 10
2019-12-29 12:48:10 80
and so on...


This data will be available for 30 days.

Once the model is trained, I will query the model to get the possible time when there will be fewer people in the room between 10.AM and 8.PM. I expect the machine learning model to respond back with the 30-minute accuracy, ie. "3.00 PM to 3.30PM"

What algorithm can I use for this problem and how can I achieve the goal? Or are there any other Python libraries than SciKit-Learn which can be used for this purpose?

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