How to use Pandas to find the strongest month of sale for a product
Well, I am not sure about how is your data so not sure if the answer will help but from what you said is that you are trying to check the month of the highest sales, so giving the product you will probably want to use the pandas groupby using the month and you will have a DataFrame with every month grouped.
imagine a DF named Data:
mean_buy = Data.groupby(months).mean()
with months = np.array([1,2,3,4,5,6,7,8,9,10,11,12]*number_of_years)
I am new to python pandas, and I am trying to find the strongest month within a given series of timestamped sales data. The question to answer for n products is: when is the demand for the given product the highest?
I am not looking for a complete solution but rather some ideas, how to approach this problem.
I already looked into seasonal_decomposition to get some sort of seasonality indication but I feel that this might be a bit too complicated of an approach.