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I'd like to update values in a column ['D'] of my data frame based on the substrings contained in column ['A']

I have dataframe df, where column D is an exact copy of column A. Column A has list of different cereal names. But I want to check if A contains a certain word and if so, then column D updates to show that word.

For example, If A contains the word Bran then D should update to show Bran. And if column A contains none of the criteria we are looking for then it should return Other.

So far I have tried this, but I am not able to change the rest of the columns without any criteria words to 'Other'

This is doing my nut in!

Simply updating VS 2022 to ver. 17.1.0 has broken the ability to drag the header of a floating window towards the header of another window and allow them to merge into one single floating window with a tabbed view layout.

This has ruined my productivity in being able to have multiple files open between a multi monitor layout. Is anyone aware of a option/setting that might have been disabled from the update?

The screenshot below shows where I would usually drag one floating window towards another an if i left go of the mouse in the right place, the two windows would usually snap tpgather into one window with multiple tabs:

Edit: Futher observations conclude the latest VS 17.1.0 have changed the way we can group floating windows together.

By default, my tabs are configured to display along the top, however the only way i can group together the windows is if i change the tab location from the TOP to the Side, but this changes the tab layout in the main IDE as well as floating windows, so it screws eveything up.

Merging the windows together:

Incidentally if I revert back to displaying the Tabs at the TOP, then we have the affect i wanted BUT I stil cannot merge any further windows in that mode:

Consider the following simple function:

I'm processing some very big files, and my simple Go program to do this is taking 2 minutes to run instead of the 15 seconds it takes for the equivalent C program (https://gist.github.com/g2boojum/5729bf75a41f537b8251af25a816c2fc). Clearly I'm missing something important. (It's also my first Go program, so I'm sure the code is idiomatically poor, too.)

The files I'm processing are csv files, which look like the following, and the only issue is that they're GB in size.

I am new in Git and I have used git pull origin in most of the time to get the changes from remote repository.

However, as I get some experience, I have observed that git fetch is preferred more, but reading several topics e.g. What is the difference between 'git pull' and 'git fetch'? and Git: Fetch and merge, don’t pull, now I am confused and need a clarification if there is a valid reason to prefer it except from checking changes before getting them.

The general idea behind this, git pull is git fetch + git merge, nut of course there are several drawbacks, etc.

So, could you please clarify me on:

1. How I should update my local branch from remote?

2. As far as I see, the difference between git pull origin and git pull origin, the latter gets all the branches from origin besides . Is that true? And which one should I prefer?

... and it's driving me nuts trying to understand what I'm doing wrong!

Playground: https://go.dev/play/p/ZQP8Y-gwihQ

The example looks contrived but it's drawn from code that I have where the error arose. In my code I'm hashing the bytes buffer and want the process to be predictable.

I have some code which takes input from the user and stores it in a list. The list may have an odd or even number of elements, for example: my_list = ['Beef','Chicken','Eggs','Lamb','Nuts','Pork'] (even number of elements)

or my_list = ['Beef','Chicken','Eggs','Lamb','Nuts','Pork','Potatoes'] (odd number of elements)

I want to store my_list in a string variable, such so that when I print(var) or create a tkinter messagebox, my program will output two columns like this:

I'm trying to include a black box likelihood function in a pymc3 model. This likelihood function just takes a vector of parameter values and returns the likelihood (all data is already included in the function).

So far I've been following this guide and have modified the code as follows to accommodate the fact my model only has one parameter k.

I'm trying to make a boxplot where my MFR (manufacturers) are displayed on the x axis and the rating is on the y axis. However I want to color the different boxplots based on the mean shelf value. (Shelf is a value between 1 and 3)

I tried this code: