toy | A Simple , basic and not suitable for production web | Application Framework library

I need to check if there are some duplicates value in one column of a dataframe using Pandas and, if there is any duplicate, delete the entire row. I need to check just the first column.

Example:

I am in the process of learning SQLAlchemy and I am stuck on the below filter as it returns nothing for some reason.

Im trying to create a multithreaded namedpipe server as outlined in the msdn sample here https://docs.microsoft.com/en-us/windows/win32/ipc/multithreaded-pipe-server but Im trying to restrict the namedpipe to access by adminstrators group members only.

The example works correctly when no SECURITY_ATTRIBUTES structure is specified but when an SA is specified the first call is successful, but following calls to CreateNamedPipe fail as long as the first pipe is listening or communicating with a client. The create call fails, usually with ACCESS_DENIED, but sometimes with error 1305 The revision level is unknown. When the first pipe closes due to client disconnecting the following call will be successful for the next createnamedpipe call but will in turn fail once that pipe has a client.

I have tried multiple values for the grfInheritance field with no avail. This is my first adventure into explicitly specifying SECURITY so forgive me if I have missed something obvious. Note that in the Function that calls createnamedpipe I create a new SA structure with each create attempt but I have also tried creating one and sharing it outside the create loop.

Relevant code follows:

function that creates the pipe:

I'm very new to python and don't know how to proceed. I have a csv file with over 100k rows in following structure:

I want to make the knight could move to any square (NOT follow the game rule). So I change the function: canMoveKnight in file Game.js like this:

I wrote an AppleScript to synch my Reminders (via export to JSON). It runs great... from the Script Editor. As soon as I tried to run it on the command line via osascript, I discovered it hits a wall when it tries to access reminders. After maybe a minute and a half, I get this error:

How can I use column-wise operations in dplyr to divide multiple column values by a specified row? This question has been answered several times for the case of individual columns, but I am trying to find a solution for multiple columns using dplyr's column-wise across function. (The only relevant answers that I could find use the superseded mutate_at function.)

Here's an example of what I'm trying to accomplish, using a toy dataset:

I have a large dataframe (approx. 10^8 rows) with some sparse columns. I would like to be able to quickly access the non-null values in a given column, i.e. the values that are actually saved in the array. I figured that this could be achieved by df.[]. However, I can't see how to access directly, i.e. without any computation. When I try df..index it tells me that it's a RangeIndex, which doesn't help. I can even see when I run df..values, but looking through dir(df..values) I still cant't see a way to access them.

To make clear what I mean, here is a toy example:

In this example is [0,1,3].

EDIT: The answer below by @Piotr Żak is a viable solution, but it requires computation. Is there a way to access directly via an attribute of the column or array?

Background

This is the client side Javascript, where I make a post request to update the respective tables with the form parameters. My database has two tables-Rabbit table, and MyStuff table, and MyStuff table holds a foreign key to the rabbit table. Now, I first update the Rabbit table by making a post request which not only updates the Rabbit table but also updates the value of the rabbitID variable in the server, and the second request updates the MyStuff with the respective form parameters, and also makes use of the rabbitID variable just updated.