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This repository has been archived by the owner on May 15, 2024. It is now read-only.
I prefer to work with pandas dataframes over Excel. Cost Explorer itself - and this project - use a wide data format. I prefer to work with relational data, with ("Index", "TimePeriod","CostAmount") as the column headers, and the rows containing tuples such as [(0, "2019-01-01", 272.11022), (1, "2019-02-01", 271.292)].
Currently I have to "melt" the dataframe to transpose (unpivot) it from wide and shallow to tall and skinny.
Have you considered using a data-science friendly data shape? Would you like a PR submitted or is this on a roadmap?
The text was updated successfully, but these errors were encountered:
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This project is fantastic, thank you!
I prefer to work with pandas dataframes over Excel. Cost Explorer itself - and this project - use a wide data format. I prefer to work with relational data, with ("Index", "TimePeriod","CostAmount") as the column headers, and the rows containing tuples such as [(0, "2019-01-01", 272.11022), (1, "2019-02-01", 271.292)].
Currently I have to "melt" the dataframe to transpose (unpivot) it from wide and shallow to tall and skinny.
Have you considered using a data-science friendly data shape? Would you like a PR submitted or is this on a roadmap?
The text was updated successfully, but these errors were encountered: