I have a dataset of date (dd-mm-yyyy format) of an event and production count. the dataset is large enough. I used anderson, shapiro and D’Agostino’s K^2 Test to check normal distribution of the data but it is not normally distributed. now I want to perform a statistical analysis to find significant difference between MEAN_1 (mean of production count 3 days before the event date) and MEAN_2 (mean of production count 3 days after the event date). the idea is to figure out if the event significantly changes the after the event has happened. Kindly suggest which statistical test will be best for this scenario.

NOTE: i am working on python (pandas dataframe) where the ‘datetime’ of an event is taken as index and ‘counts’ is the column. datetime of an event is on x-axis and production count is on y-axis.