dummy | Generating dummy data , perhaps for integration

I have the following dictionary of exchange rates:

So I was really ripping my hair out why two different sessions of R with the same data were producing wildly different times to complete the same task. After a lot of restarting R, cleaning out all my variables, and really running a clean R, I found the issue: the new data structure provided by vroom and readr is, for some reason, super sluggish on my script. Of course the easiest thing to solve this is to convert your data into a tibble as soon as you load it in. Or is there some other explanation, like poor coding praxis in my functions that can explain the sluggish behavior? Or, is this a bug with recent updates of these packages? If so and if someone is more experienced with reporting bugs to tidyverse, then here is a repex showing the behavior cause I feel that this is out of my ballpark.

I am new to jQuery and built this code that I modified to make it work right away in fiddle etc.

When the select changes, it is supposed to create a table but it does not do anything. However, if I place the

I am writing code to answer the following LeetCode question:

Given the head of a linked list and an integer val, remove all the nodes of the linked list that has Node.val == val, and return the new head

Example 1 ...

I am trying to dynamically generate the following html table, as seen on the screenshot

I was able to manually create the table using dummy data, but my problem is that I am trying to combine multiple data sources in order to achieve this HTML table structure.

SEE STACKBLITZ for the full example.

The Data looks like this (focus on the activities field):

Let's say I have data test (dput given) where a list-col say items:

I'm reading the official Django documentation, but I can't find an answer to my question.

Right now I have this query implemented, working with a custom MariaDB connector for Django:

When running the first "almost MWE" code immediately below, which uses conditional panels and a "renderUI" function in the server section, it only runs correctly when I comment out the 3rd line from the bottom, observeEvent(vector.final(periods(),yield_input()),{yield_vector.R <<- unique(vector.final(periods(),yield_input()))}). If I run the code with this line activated, it crashes and I get the error message Error in [: subscript out of bounds which per my research means it is trying to access an array out of its boundary.

I am very new to Python. I have a dummy dataset (25 X 6) for practice. Out of 6 columns, I have 1 target variable (binary) and 5 independent variables (4 categorical and 1 numeric). I am trying to view my target distribution by the values within each of the 4 categorical columns (and without writing code for separate columns - but with a for loop usage so that I can scale it up for bigger datasets in the future). Something like below:

I am already successful in doing that (image above), but since I could only think of achieving this by using counters inside a for loop, I don't think this is Python elegant, and pretty sure there could be a better way of doing it (something like CarWash.groupby([i,'ReversedPayment']).size().reset_index().pivot(index = i,columns = 'ReversedPayment',values=0).axes.plot(kind='bar', stacked=True). I am struggling in handling this ax = setting) Below is my non-elegant Python code (not scalable):