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I'm trying to forecast Real estate Price , it's not a prédiction. But a forecast Like the Price of a an appartement in 2023 or 2024, i'm asking about how should be my dataset ? Can I use a dataset from 2018 to 2021 of 13 columns You can find the dataset here:

https://www.kaggle.com/datasets/mrdaniilak/russia-real-estate-20182021

Date, area, kitchen_are, nb_rooms Please note that every row is a new house indépendant from others, I'm having this dataset by scrapping a website of ads announcements and my data is not related, i don't have like a history of the price of each apartment it's not like the price was 1 million euros in 2018 and become for the same apartment 1.5 million euros Can I don't multivariate time series with my dataset ? Can I use neural fb prophet ? Which algorithm can solve my problem ?

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This is the typical problem where you have to really model the phenomenon. You are supposed to use a pencil and paper and actually do some choices.

One thing you can do is to create a function with an aggregated price over time depending on features. By doing so, you are able to have a "price curve" over time for each feature. And so you can actually forecast.

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