Perception | driven memory game with animated graphics | Keyboard library

I'm currently running principal component analysis. For the interpretation I want to create a profile (pattern) plot to visualize the correlation between each principal component and the original variables. Is anyone familiar with a package or code to create this in R? I'm using the prcomp() function in R.

See examples:

https://canadianaudiologist.ca/predicting-speech-perception-from-the-audiogram-and-vice-versa/ https://blogs.sas.com/content/iml/2019/11/04/interpret-graphs-principal-components.html

This is similar data to my db:

I want to make a randomizer for the SPECIAL stats from Fallout New Vegas, i've built most of the code, but there's cases that the sum of the variables exceed/are below the cap of 40.

Is there a way to limit them, or in cases that the sum is below or over 40, distribute the difference?

I am still relatively new to the Unity environment and am currently working with reinforcement learning and ML agents. For this I wanted to add an agent to the 2D platformer.

I have attached two ray perception sensors to my agent. Unfortunately I can't get any hits with these sensors, at least they are not displayed as usual with a sphere in the gizmos.

The sensors are casting rays, but like you see in the image, they are not colliding.

The ray perception sensor are childs of the agent, defined in its prefab. I defined the sensors to collide with 4 tags: Untagged, ground, enemy and coin

I assigned the coin tag to the token, the enemy tag to the enemy and the ground tag to the tilemap forming the ground. The token has a circle collider, while the enemy has an capsule collider. On the tilemap there is a tilmap collider.

I would now expect the sensor to collide with the token, enemy and ground and display these hits in spheres, but it does not.
So, what am I doing wrong?

While trying to traverse the inner contents of the ShapeContainer, I wanted to differentiate between XSSFPictures which are children of XSSFShapeGroup and which are not by checking it's parent:

I am trying to follow a textbook example of training a perception, but I keep running into an index out of bounds error. I am following the textbook 'Natural Language Processing In Action by Hobson Lane, Cole Howard, & Hannes Max Hapke'.

This is the data:

I have a 3 deep array. Currently, the code will isolate a record based on one field ($profcode) and show the heading. Eventually, I am going to build a table showing the information from all the other fields. The code so far is using in_array and a function that accepts $profcode. I am unsure if (and how) I need to use array_keys() to do the next part when I retrieve the "Skills" field. I tried:

I am attempting to obtain sentiment scores on comments in a data frame with two columns, Author and Comment. I used the command

I want to make the font bigger on the axes on a collated plot. I'd like both the axes on the collated plot, as well as the axes on each individual plot to be bigger. Is there an easy way to do this without individually going into each of the plots I've collated together and changing the font size- for example, can I add anything to the plot_grid() function to do this? Code for context is included below.

I would like to guide the reader's attention to just some columns (or rows and columns) in a heatmap, while still retaining the full context.

I can use alt.condition to alter color and opacity. Both work to some extent. But changes in opacity visualize in a similar way as changes in value. And using a different color changes the perception of values. What I would like to do instead is to put yellow or red borders around the consecutive columns I want to highlight.

This is what I have now. Any other ideas?