You Know How Mathematicians Have The Journal Of Recreational Mathematics, Right? Where They Publish Stuff

short comic based off that one post where sevika first meets silco by mistaking him for a butch lesbian (idk how the timelines work don't think too hard abt the ages lol)

Quilava (best boy) if you still want pkmn requests

They were bald for 98% of this.

It is with the deepest frustrations that I must report Microsoft has pushed out Copilot onto Microsoft Word no matter what your previous settings were. If you have Office because you paid for it/are on a family plan/have a work/school account, you can disable it by going to Options -> click on Copilot -> uncheck 'Enable Copilot'.

(Note, you may not see this option if you haven't updated lately, but Copilot will still pop up. Updating should give you this option. I will kill Microsoft with my bare hands.)

In addition, Google has forced a roll-out of it's Gemini AI on all American accounts of users over 18 (these settings are turned off by default for EU, Japan, Switzerland, and UK, but it doesn't hurt to check).

To remove this garbage, you must go to Manage Workspace smart feature settings for all your Gmail/Drive/Chat and turn them off. Go to Settings -> See all settings -> find under "Genera" the "Google Workspace smart features" -> turn smart feature setting off for both Google Workspace and all other Google products and hit save. (If you turned off the smart settings in your Gmail, it never hurts to open Drive and double-check that they're set to off there too.)

Quick Edit: I found the easiest way to get to the Smart Feature settings following the instructions above was to do it through Drive. Try that route first.

Now is the time to consider switching to Libre Office if you haven't already.

Check it out, my anxious friends

Hey guys! Those of you who’ve followed me for a while already know I get anxiety, caused by anything from too much sugar, any amount of caffeine, or having to talk to someone in the grocery store. So I wanted to share this lovely thing I’ve found to help deal with it!

This is Morpheus, my sleepy time anxiety companion. (Isn’t he cute?) I found a mention online and these guys are meant to help address anxiety and sleep issues! Here’s how it works.

There’s a little egg in his tummy, when I hit the button Morpheus starts to pulse out a heartbeat rhythm. What’s really cool about this is lots of studies show that our heartbeats will slow down and match another heartbeat. So the beat will start measured and a bit loud (this is relative, you can’t hear or feel the pulse without touching the plush friend directly). Slowly it gets softer and further apart. When the button is pressed it goes through a 20 minute cycle. Generally I take about 45+ minutes to fall asleep as my mind decides that sleepy time is the best time to worry and fret over problems, but now I often fall asleep before the cycle completes. 

Morpheus has also been a help during full blown panic attacks, my breathing and heartbeat will start to match his almost immediately, which is more than I could’ve hoped for. I’m sure that results may vary, but if you have anxiety, panic attacks, or trouble sleeping, you can find them here. (They also come in puppy friends!) They ship from Japan, and all instructions are in Japanese, but he was so simple to use, it hasn’t been a problem, but you might have to wait a bit for your own sleep time friend.

Your Essential Guide to Python Libraries for Data Analysis

Here’s an essential guide to some of the most popular Python libraries for data analysis:

 1. Pandas

- Overview: A powerful library for data manipulation and analysis, offering data structures like Series and DataFrames.

- Key Features:

  - Easy handling of missing data

  - Flexible reshaping and pivoting of datasets

  - Label-based slicing, indexing, and subsetting of large datasets

  - Support for reading and writing data in various formats (CSV, Excel, SQL, etc.)

 2. NumPy

- Overview: The foundational package for numerical computing in Python. It provides support for large multi-dimensional arrays and matrices.

- Key Features:

  - Powerful n-dimensional array object

  - Broadcasting functions to perform operations on arrays of different shapes

  - Comprehensive mathematical functions for array operations

 3. Matplotlib

- Overview: A plotting library for creating static, animated, and interactive visualizations in Python.

- Key Features:

  - Extensive range of plots (line, bar, scatter, histogram, etc.)

  - Customization options for fonts, colors, and styles

  - Integration with Jupyter notebooks for inline plotting

 4. Seaborn

- Overview: Built on top of Matplotlib, Seaborn provides a high-level interface for drawing attractive statistical graphics.

- Key Features:

  - Simplified syntax for complex visualizations

  - Beautiful default themes for visualizations

  - Support for statistical functions and data exploration

 5. SciPy

- Overview: A library that builds on NumPy and provides a collection of algorithms and high-level commands for mathematical and scientific computing.

- Key Features:

  - Modules for optimization, integration, interpolation, eigenvalue problems, and more

  - Tools for working with linear algebra, Fourier transforms, and signal processing

 6. Scikit-learn

- Overview: A machine learning library that provides simple and efficient tools for data mining and data analysis.

- Key Features:

  - Easy-to-use interface for various algorithms (classification, regression, clustering)

  - Support for model evaluation and selection

  - Preprocessing tools for transforming data

 7. Statsmodels

- Overview: A library that provides classes and functions for estimating and interpreting statistical models.

- Key Features:

  - Support for linear regression, logistic regression, time series analysis, and more

  - Tools for statistical tests and hypothesis testing

  - Comprehensive output for model diagnostics

 8. Dask

- Overview: A flexible parallel computing library for analytics that enables larger-than-memory computing.

- Key Features:

  - Parallel computation across multiple cores or distributed systems

  - Integrates seamlessly with Pandas and NumPy

  - Lazy evaluation for optimized performance

 9. Vaex

- Overview: A library designed for out-of-core DataFrames that allows you to work with large datasets (billions of rows) efficiently.

- Key Features:

  - Fast exploration of big data without loading it into memory

  - Support for filtering, aggregating, and joining large datasets

 10. PySpark

- Overview: The Python API for Apache Spark, allowing you to leverage the capabilities of distributed computing for big data processing.

- Key Features:

  - Fast processing of large datasets

  - Built-in support for SQL, streaming data, and machine learning

 Conclusion

These libraries form a robust ecosystem for data analysis in Python. Depending on your specific needs—be it data manipulation, statistical analysis, or visualization—you can choose the right combination of libraries to effectively analyze and visualize your data. As you explore these libraries, practice with real datasets to reinforce your understanding and improve your data analysis skills!

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what makes art special is that it's hard to make

This deep into his disaster of a time running Twitter and people are still reporting "Elon Musk said he'd give Wikipedia a billion dollars to change their name to DICKipedia xDDDDD" as a wacky story, Which first of all implies the sad possibility that there are people who still find his "let that sink in" shtick funny, but his questioning of Wikipedia is uh. Actually p. sinister

Like, it's easy to go "haha, he doesn't know about hosting costs!" But he. Clearly does know that hosting one of the world's top ten most visited websites costs a lot of money. He wants to sow doubt and conspiracies, and it's working, judging by his replies

Also, he's a rich guy who loves spreading misinformation, mad that Wikipedia doesn't allow it. He also is baffled by the idea he can't buy it, that it's not trying to make money

He doesn't even have any specific criticisms of Wikipedia. Jimmy Wales called him out for removing verification with very specific criticisms, and he just responded "please fix Wokipedia". Ladies and gentlemen...got 'em!!!!!1!

Ngl i prefer the 2016 version purple on the right.