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Cake day: September 16th, 2023

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  • I’m also in my late 20s, and I’m an immigrant (changed continents)

    When I meet new people, ai usually have a hard time coming up with something to talk about, so I had (still have) a hard time making new friends.

    What helped me was to have continuous contact with people in a focused environment, for example: with around 6 months of office attendance I started warming up to my new colleagues (which eventually became friends), even though we were usually talking about work back then, we started to talk about it less and less up to a point where we don’t even work together anymore, but keep in touch

    I found another of such environments in sports practices as well: don’t want to talk about anything? Fine, let’s just keep this ball rolling back and forth" but then eventually (again after a few months of continuous contact with the same group of people) things started to warm up a little

    So to sum it up I’d say: patience is key, it usually takes a while before prople start to get along well










  • @tequinhu@lemmy.worldtoScience Memes@mander.xyzPandas
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    9 months ago

    I didn’t know about lazy loading, that’s cool!

    Then I guess that the meme doesn’t apply anymore. Though I will state that (from my anedoctal experience) people that can use Panda’s most advanced features* are also comfortable with other data processing frameworks (usually more suitable to large datasets**)

    *Anything beyond the standard groupby - apply can be considered advanced, from the placrs I’ve been

    **I feel the urge to note that 60Mb isn’ lt a large dataset by any means, but I believe that’s beyond the point


  • It really depends on the machine that is running the code. Pandas will always have the entire thing loaded in memory, and while 600Mb is not a concern for our modern laptops running a single analysis at a time, it can get really messy if the person is not thinking about hardware limitations