Mailman 3 March 2024 - Pandas-dev

pandas new infrastructure (OVH donation)
by Marc Garcia Sept. 21, 2024

Sept. 21, 2024

Hi all, pandas has received a donation from OVHcloud <https://www.ovhcloud.com/> to support the project infrastructure, with OVHcloud public cloud credits (an initial amount of 10,000 EUR for a period of one year). OVH is open to sponsor longer term and also other projects of the ecosystem (or NumFOCUS as a whole), but we started with this to have feedback at a smaller scale first. The credits will be used initially for: - Hosting of the pandas website - Running the pandas benchmarks - Speeding up the project CI I detail next what I have in mind to set up for each. If anyone is interested in getting involved, or has ideas, comments... please let me know. I'll publish updates here as there is progress on this. Website: I'm planning to experiment on splitting the website in two (it'll be transparent for users). The website and the stable docs which receive most of the traffic can probably be stored in Cloudflare pages. We're already using Cloudflare as a CDN, so instead of using it as a cache, we can publish the documents there. The rest of the docs (old versions and the dev version) can be hosted in bucket storage of the OVHcloud. Response times may be a bit slower, but our website is bigger than the Cloudflare quota, and having old docs rarely accessed in a CDN seems unnecessary anyway. - Benchmarks: OVHcloud instances have guaranteed hardware, and we'll be checking if this is enough for the results of the benchmarks to be consistent over runs, or if there is too much variability and we need dedicated hardware. If consistency is good enough that would be great, since our benchmarks mostly use one core, and using dedicated hardware is likely to be a decent waste of resources, since most servers will likely have 16 cores or more. We'll discuss with OVH if dedicated hardware is needed, as at the moment their public cloud doesn't offer it (there is an alpha for providing dedicated instances, but we need to check with them). - Faster CI: Our GitHub runners are small, and most builds take around one hour or more to finish. We should be able to use bigger OVH instances for our existing CI pretty easily, via their OpenStack API and CIrun.

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February 2023 bi-monthly community meeting (Wednesday February 8, UTC 18:00)
by Joris Van den Bossche Sept. 11, 2024

Sept. 11, 2024

Hi all, A late reminder that the next bi-monthly (twice a month) dev call is today in a bit more than 1 hour (Wednesday, February 8) at 18:00 UTC. Our calendar is at https://pandas.pydata.org/docs/development/meeting.html#calendar to check your local time. The pandas Community Meeting is a regular sync meeting for the project's maintainers which is open to the community. All are welcome to attend! Video Call: https://us06web.zoom.us/j/84484803210?pwd=TjUxNmcyNHcvcG9SNGJvbE53Y21GZz09 Meeting notes: https://docs.google.com/document/u/1/d/1tGbTiYORHiSPgVMXawiweGJlBw5dOkVJLY-… Joris

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Is it time for a bi-weekly pandas call?
by Marco Gorelli May 13, 2024

May 13, 2024

Currently, there's a monthly pandas call, which has been in place for several years. Seeing as there's now more people working on pandas as part of their jobs, might it be time to increase the frequency? E.g. to meet every 2 weeks, instead of once a month?

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Possible bug fix
by diogojarodrigues＠icloud.com March 25, 2024

March 25, 2024

Hi everyone! For the past weeks I have been trying to fix this issue <https://github.com/pandas-dev/pandas/issues/57411#issuecomment-1984860263>. For what I could understand that error is being raised on the function “pandas_dtype” in the file common.py. The error occurred when you call the function np.dtype when the argument is a pyarrow list, numopy doesn’t recognize it. So to solve this I make a simple if statement like this: Do you think this is a good solution? I also have a scrypt to run the code. I will attach to images with the script and the output. Thanks for your thoughts, Diogo Rodrigues

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Relatively simple process for multi column Fuzzy Merge > possible enhancement to merge_asof??
by Bucknall, John March 11, 2024

March 11, 2024

HI I have a suggestion for a relatively simple addition to the pandas merge tools as I just had to code up a join on some columns with fuzzy merge of multiple columns in pandas. I noted on a few stack overflow threads that a multi column fuzzy merge was lacking > so is this of interest and who do I chat to that knows how to build it as a pandas function? I seemed to go round the block about 9 times to get there but its seems to work well for my application. Kind regards John Bucknall CEng Marketing Effectiveness Data Scientist Castrol Global Marketing • Mobile: +44 (0)7880 926 331 [cid:image001.png@01DA73A8.2588E740]  > Want to know more? check out our Neurodiversity bitesize<https://web.microsoftstream.com/video/8f7c7756-ead7-47ce-99a6-9a9b26233ea2> Without a breadth of data you can’t have lateral thinking… BP International Limited. Registered office: Chertsey Road, Sunbury on Thames, Middlesex, TW16 7BP. Registered in England and Wales, number 542515.

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