Apparently, you have a target variable (y) and a set of input variables (input variables (X). This seems like a supervised problem. A regression analysis can be a solution to implement.
Feature engineering needs to be completed before running a machine learning model. Such as text field columns can be encoded with Label Encoder and One Hot Encoder.
Irrelevant input columns for analysis can be dropped. If the city variable is same all the way, meaning the all of the data is from a single city. Also N/A and null values need to be cleaned.
In some models, normalization of the data can produce better results.
As a Machine Learning model, starting from Linear Regression would be feasible. Later Random Forest Regressor, Lasso, Ridge Regression can be examined.