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3 thoughts on “Converting excellent spreadsheets to tidy data”

  1. Great post!
    It’s worth pointing out that making your data tidy is a generally useful process, i.e. it facilitates processing and visualization in other programming languages as well.

    In Python, for example, complex operations on DataFrames using the Pandas library are often much easier when the data is tidy. In addition, Seaborn, a Python library for plotting statistical data, can very easily reveal complex relationships between variables if the datasets are tidy.

    In summary, while it seems that tidy data concepts grew out of the R community, these concepts are equally valid in any data analysis pipeline.

  2. Hi, I have a requirement where the end user wants the data to be stored in database in tidy format. The data has a list of products and set of characters that measures this product. This set of characters are not constant it might change in future and it is a really huge dataset.
    Would you suggest converting the data into tidy format after it is extracted from the database or to convert the data into tidy format with in the database (I suggested the latter).

    Thank you,

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