bonkers | Small utility to work with the Big Red Button

So I've added a feature to write percentages efficiently, all you would have to do is have a number, say 6, then press percentage, and the calculator would automatically write out 0.06. It's all working well when you start to type out the expression for the calculator:

But when you press the equal sign, thats when things go bad:

Now because I'm horrible at math, I literally thought this was the correct answer, so now i can finally move on to other things, right? But when I googled it, it said that 6*0.06 is 0.36, not 36.

Here's where things get a little bonkers again, when I do 6/0.06, I get 1, not 100, so that means whenever I divide, I get something 100 times lower than the actual answer, whenever I multiply, I get something 100 times higher than what I asked for.

Here is the percent function:

I am trying to remove the 'em dash' from a pandas DataFrame. I have tried a bunch of different suggestions. But none of them are working.

This is what I have got

This seems bonkers so I'm hoping I didn't find a big security gap... I have Powershell JEA (just enough administration) successfully set up on a server to allow only certain administrative functions. Specifically, I don't have the "net" command allowed at all. If I do the below:

I have a react component with a simple form and an area to display output on submit.

I have manually tested and confirmed that submitting the form outputs the values as expected. However I cannot get React Testing Library to make the same assertion.

From what I can gather it doesn't seem to be seeing the updated page content.

Here's the output of the test failure:

So I am looking at a problem which is similar in principle to computing partitions for a large N. My problem is similar to the following hypothetical problem.

Let's say that I have a random variable X which has possible outcomes of 1,2,..., 10, each of which occurs with corresponding probabilities P1,P2,...,P10. My hypothetical problem: if I generate 20 random and independent samples of X and sum them together, what is the likelihood of the resulting summations of 10,11,12,... 200.

A few approaches which occurred to me which are workable-in-theory but computationally-not-close-to-possible are as follows.

Idea 1) List out the partitions of 200. Remove any partition categories which use a number greater than 10. Calculate the probabilities of each and sum up for each sum (sum = 10,11,...,200). This is ezpz for small N, completely and totally bonkers for 'huge in this context' N like 200.

Idea 2) List out all the possible 20 item sample results (ie 1-1-1-1-1-1-1-1-1-2,1-1-1-1-1-1-1-1-1-2,etc), note the probability of each, and sum up for each sum (sum = 10, 11, ... , 200). Again, ezpz for small N, completely infeasible in this context.

I also had the following idea, but I was not able to get it to work. Idea 3) Modify your favorite 'generate the partitions' algorithm so that any number greater than 10 cannot be used in a partition. Similar to Idea 1 in principle, however we generate a small list and don't have to trim down a huge list. My two issues with this idea, a) I am not sure how to do this for any partition generation algorithm, and b) even if I could I am not convinced it would be computationally feasible.

Any points on how I can tackle this? At the end of the day it is similar to any host of other problems in the bucket of [enumerate all possible outcomes, compute the probability of each, aggregate the probabilities for each aggregate sum, and you have your answer]. However the sample space is so huge.

This would be really easy to approximate via monte carlo, but that approach leaves a bad taste in my mouth as so many of the theoretically possible outcomes will not show up, even 10 billion+ iterations or so.

Any thoughts on how to tackle this?

[I am flexible on the language of choice, but I have a bias towards using Python where possible]

I'm editting a .tsx-file and are reaching upon this bonkers file-formatting:

... If I enlarge the window a bit, then it makes more sense:

But I would still like to change it, so value and onClick aren't aligned all that way to the right. Ideally, it would try to align them with the opening bracket (as they do), unless the opening bracket is more than 35 characters, from the line start. Or something like that.

Now, I assume that it's the TypeScript-formatting that dictates the Code Style for a .tsx-file. But when I open the settings: Editor >> Code Style >> TypeScript then there are BAZILLIONS of settings.

Which leads me to three questions:

1. Does anyone know what I need to change, so object-attributes doesn't follow the opening-brackets width?
2. Could I find the name of what I'm looking for, in some smart way? I tried hovering over the massive space, hoping that the little yellow light-bulb could shine some light on, what I was after.
3. Are there any presets, to be found somewhere? So I don't need to engineer a new Code Style, if I dislike the default.

I'm building a discord bot with Discord.py and i am running into some trouble when using the *arg / **kwarg when getting the msg.content. Here's what the code looks like.

I'm trying to get a Pandas exercise done and it's driving me bonkers.

I have a dataset containing the number of cyclists that went by a certain zone of the city every hour of each day, so something like this:

et cetera. There are much many more rows and columns. The "zone" columns contain how many cyclists were recorded for that zone at that time.

The exercise asks to group this dataframe by year, month, and day, and then take the sum on the grouped dataframe. I do that like this:

I have a dataset from yahoo finance that I'm trying to group by month (which I've done) and then plot the average % change for that month on a yearly cycle (data goes back 21 years). For example, I'd have 21 Januaries with average % increase/decrease for the sum of Januaries, 21 Februaries with average % increase/decrease for the sum of Febriaries, etc.

After around 2 hours of playing with things, I cannot get it clustered properly and it's driving me bonkers. I have tried using pd.Grouper and pd.groupby and variations of playing with datetime to isolate the month, or give the month an assigned number to group by, but I've had no luck.

My intended outcome that I'm looking for should look like (~ is placeholder for datetime YYYYMMDD format)