Python

Google Trends Enhanced revolutionizes keyword research by allowing users to search more than five keywords simultaneously. It groups keywords, obtains search interest data, and merges results into an Excel file. The tool overcomes data comparison challenges by using a benchmark keyword for scaling. It also provides daily data for periods exceeding nine months, offering greater flexibility for various analytical purposes.

When you try to read a csv file in Python, pd.read_csv() is the most common method. However, the process of decoding sometimes causes errors as below, and it may not work even you tune several arguments.

Iterating a path to list all subdirectories and files is an extremely helpful function. You can read bulk excel files with several pretty simple codes. As a lazy guy like me, wrap it to a function make me write code effectively. The code below seems huge, but it contains multiple pieces of functions. All of them are used to operate lists, and the main function to list paths and files is os_get_dir_list()

Apriori is a common algorithm for retail analysis. But it will be heavy if you load huge transaction data. You may want to focus on association rules of specific SKU (or called CUG) in some cases. Based on apyori package 1.1.2 for Python, I hacked it to be liter and faster. Most of the arguments are the same with apyori, but with an additional list argument, target.

Custom Python packages enhance productivity. Create your toolkit, like my “Arsenal” package. Clone it to new projects for version control. Import using sys.path modification. This method prevents conflicts and allows continuous optimization without breaking existing projects. Remember, path changes are temporary.