Dear Numpy Team, I am writing to propose the addition of quarterly date units (Q) to the datetime64 and timedelta64 data types in Numpy.
While Numpy currently supports various date units, including years, months, weeks, and days, the absence of quarterly units limits its usability in numerous applications. Users are often forced to use cumbersome workarounds such as writing custom code or relying on external libraries, which detracts from the simplicity and efficiency of using Numpy. Quarters are a fundamental temporal unit, particularly used in finance, business, and economics (it is probably the most analyzed frequency in macroeconometrics). Many time series datasets are reported at quarterly intervals, making native support for quarterly units essential for simplifying data handling and manipulation within Numpy. Although alternative methods exist for representing quarters, native support would improve consistency across codebases and enhance interoperability with other libraries and frameworks. Ultimately it leads to improving the overall user experience using dates data types in Numpy. I would like to discuss this proposal further and would be happy to open an issue on GitHub to initiate the conversation if the proposal sounds reasonable. Your feedback would be appreciated. Best regards, Oyibo _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
