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annnd I'm making my own version now. I'm getting help for depression, but most of the battle is on my own time, especially with the feeling that the days just slip away. Hopefully a coloring book in form of a spreadsheet can help me get a sense of progress.

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this guy [tracked his activities on an hourly basis](businessinsider.com/i-track-ev) for 5 years. The data he collected makes a brilliant visualization.

> So now that you can process packets offline, what do you want to do with them? I don’t know about you, but aside from obvious applications to network analysis, I’d like to use this data for trending, visualization, or even generative art and sound. But then again I’m weird. What are you gonna do?

-- Tony Lukasavage on [offline packet capture analysis](tonylukasavage.com/blog/2010/1)

another great find today - [crafter](github.com/hrbrmstr/crafter) R library.

> Life’s too short to export to CSV/XML. There’s no reason R should not be able to read binary PCAP data.

I think I need to add the /s tag for clarity. The quote is taken out of context deliberately. Go read the full blog post, it's worth it

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data cleaning _is_ analysis.
knowing your data _is_ key.

I'm so glad I found [this blog](counting.substack.com/p/data-c) today. Someone else saying exactly what I'm thinking quietly is a nice reassurance.

> We just call it data cleaning because somehow it’s “not the real analysis I’m doing”, it’s “the stuff that comes before”. The Real Work™ is using algorithms with names, not “find and replace”. I’m just forced to do this menial labor step so that I can achieve my true glory as the bringer of truth.

today I met my manager's manager for the first time. He snuck up by my desk:
-- so, you're our data person?
-- yes, I am, nice to meet you.
-- tell me, what do I need to know about our data? *laughs*
-- *me staring into the monitor failing to generate a joke answer within a couple of seconds*

colleague across the room:
-- she's smart though.

spotted a golden nugget that made me think: [here](qoto.org/@ruut/109716733771860), the chapter dedicated to Richard Owen, 52 sentences describe his ideas, and 1 sentence describes his character:

> Although admired for his anatomical research, Owen was a difficult man from the accounts of those who worked or tangled with him.

what's something that your peers would feel compelled to mention about your character?

Kardong - Vertebrates: Comparative anatomy, function, evolution / 2nd ed.

@freeschool absolutely positive feelings about giving away the books - nice to know they've found a new purpose. I don't work in the medical field, but absolutely admire the _science_ behind it (not so much the practice, like you also point out). So I kept a couple of books to remind myself of the science part

I closed the chapter of my medical studies a long time ago.

all the books I had collected in that era have found their next owners. One of the few I couldn't give away is Kardong's Comparative Anatomy. I've picked it up again out of nostalgia / and recent lack of motivation in my current profession.

nothing makes me feel more connected to the universe / or whatever you prefer to call it / than diving deep into the very imperfect scheme of living things. I might just start posting my daily readings / just to fight off the lack of general motivation

my New Year's party of choice is browsing live videos of my favorite bands. Starting now, why not.

good evening!
[Night Verses](yewtu.be/watch?v=qIU5VuPBG2s)

after solid 2 years of working from home, we're bringing office days back again.

so I went to the office yesterday, sat down with a colleague and discussed probably months and months worth of ideas in 1.5 hours. Super productive & motivating meeting.

also / unintentionally - heard _everything_ about other colleagues' sick kids, upcoming appointments, gossip about another stay-at-home colleague, vaccination drama, views on some minorities, and other whispers I'm glad I didn't catch.

I'm still recovering.

@Joel make sure I don't throw out the baby with the bathwater, and then dump the bathwater, so to speak

> Sometimes, there are large datasets that contain too many redundant or similar samples.

Pešek et al.
_Active Learning Framework to Automate Network Traffic Classification_
2022

> If you do not like coffee, pretend it is about tea

Christoph Molnar
[Interpretable Machine Learning](christophm.github.io/interpret)

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