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Hey guys. I wanted to enquire about the best practices

for analysing data that has a lot of ID columns. These are numerical data points but serve more of a categorical value if that makes sense? In a lot of preparing dataset people have simply dropped the ID columns. The ID themselves are randomly generated however the thing they denote might have a seasionality based on that ID column for example a table with a lot of product details and only a few numerical columns and/or categorical columns.

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try pandas.describe method

Change the type of those columns to "object" or "category". Then, pandas will treat the columns as strings or factors, respectively. For instance df["id_column"] = df["id_column"].astype("category")

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