bagel | Basic Academic Graphical Engine Library

I am trying to see how word frequency correlates with phonotactic probability using R, but there are a few issues. First, and most generally, I don't know merge these two graphs together (i want them to appear on the same axis).

This leads to a second problem because the first graph's y values are in probabilities, and the second is a count, so the scales are not the same. Should I combine data frames first, or is there a simpler way to merge two graphs?

Here is the reproducible sample, and the code for my graphs:

I have website visitor data that resembles the example below:

I would like to transform to below, where I can count the amount of times they have visited a part of my site that deals with specific content. A general count of all pageviews, delimited by comma, would be great as well.

I have the option to perform in SQL or Python but I am not sure what is easier, hence why I am asking the question.

I have referenced following questions but they are not serving my purpose:

• Count the number of occurrences of a character in a string (this was close but I am not sure how to apply to a dataframe)

• count occurencies of a word

• Counting word occurrences in a table column

• Counting word occurrence with SQL query

I have data in a dataframe that looks like this, where each column is a KEYWORD and each row is an observation of how many times each ID said the word:

I am trying to get it to a form where I can see what the most popular word is overall, something where the columns themselves are new columns and the TOTAL row transforms to a column that can be sorted:

I have tried melt and stack but I dont think I am using either one correctly. Any help is appreciated.

I'm trying to scrape a website which has a structure like this:

In the last few months, many developers have reported NavigationLinks to unexpectedly pop out and some workarounds have been published, including adding another empty link and adding .navigationViewStyle(StackNavigationViewStyle()) to the navigation view.

Here, I would like to demonstrate another situation under which a NavigationLink unexpectedly pops out:

When there are two levels of child views, i.e. parentView > childLevel1 > childLevel2, and childLevel2 modifies childLevel1, then, after going back from level 2 to level 1, level 1 pops out and parentView is shown.

I have filed a bug report but not heard from apple since. None of the known workarounds seem to work. Does someone have an idea what to make of this? Just wait for iOS 15.1?

Below is my code (iPhone app). In the parent view, there is a list of persons from which orders are taken. In childLevel1, all orders from a particular person are shown. Each order can be modified by clicking on it, which leads to childLevel2. In childLevel2, several options are available (here only one is shown for the sake of brevity), which is the reason why the user is supposed to leave childLevel2 via "< Back".

I have some text stored in a .docx file:

Let's say I have two data frames like so:

I'm working on a personal project that is a dating app. The tech stack I'm using is React Native with Firebase to handle all backend functionalities (auth, firestore, cloud functions).

I want my app to be scalable, but I'll admit that backend isn't a huge strong suit for me. Here are the main features:

• Each user will receive 4 profiles per day that match their preference for 'Men', 'Women', or 'Everyone'. Location/Proximity or Age is not a part of the preference. This is similar to Coffee Meets Bagel where each user receives a limited number of 'Bagels' per day.
• When Tammy likes Dave's profile, Tammy will show up on Dave's home screen with a label that reads: "She likes you".
• At that point, Dave can match with Tammy and the two will open a chat window.

My current structure just has 1 collection: singles, and it contains documents of every user. For example, I could retrieve all user's details by going to the path singles/userId.

One possible solution I have thought about:

• Let's say that the profile circulation will not start until there are 1000 singles on the platform, with at least 40% women and 60% men. I run a scheduled job that creates a collection of Men (150 documents, each with 4 document references), Women (100 documents, each with 4 document references), and a collection of mixed (250 documents, each with 4 document references). When Tammy opens the app today, she will see a random document of the Male group that she has not seen before. When she sees that group, we will write her userId into a subcollection of that document so that we can keep track that she has seen it (and therefore not surface it again). For Dave, we can do the same thing, except show him a random document of 4 women, and write his userId into a subcollection of that document. Then, for every 4 new male sign ups, we can trigger a cloud function to write a new document into the Male collection. And for every 4 new female sign ups, we can write a new document into the Female collection. That way, to the users who want to see men, we have content for 150+ days as a head start. And for women, there is a 100+ day head start, and for those who want to see everyone, there's a 250+ day head start.

Let me know if my proposed solution makes any sense. I am also trying to reduce the number of read/writes in these scheduled jobs and operations.

I'm working on a project for school. I was able to get my function to work the way I need it to, using all of the parameters that the teacher wanted, except when it displays. I need it to pull from two lists, which it does, and display both lists next to each other, which it does. However in the teacher's version, the display/output looks like this: