outliers | Find outliers in a dataset | Predictive Analytics library

I have written a function that draws random variates from a normal distribution with outliers. However I now want to take the mean of this data and append it to an empty vector 1000 times (so essentially a vector with 1000 different means using my function) Here is my attempt so so far.

I want to remove outliers from a variable MEASURE after grouping by TYPE. I tried the following code but it didn't work. I've searched and I've only came across how to remove outliers for the whole dataframe or one column. But not by after grouping.

I have the following dataframe and then a calculation to identify outliers:

I have a .csv of species occurrences with individual lat-long points, but I am trying to aggregate them all into a singular 'average' coordinate point per species. From some digging I see there can be issues with a simple average (high altitude or low altitude outliers can cause issues). Does anyone have a suggestion on how to do this easily/quickly in R? Thanks

Data is seen up like this but I have 71,000+ occurrences total.

I have this dataset:

Im trying to remove outliers using numpy (without using pandas). I have an array I created who looks like this:

Relatively new to Dash, and this is a problem that has been vexing me for months now. I am making a multi-page app that shows some basic data trends using cards, and graphs embedded within cardbody. 30% of the time, the app works well without any errors and the other 70% it throws either one of the following:

1. ImportError: cannot import name 'ValidatorCache' from partially initialized module 'plotly.validator_cache' (most likely due to a circular import) OR
2. ImportError: cannot import name 'Layout' from partially initialized module 'plotly.graph_objects' (most likely due to a circular import)

Both these appear quite randomly and I usually refresh the app to make them go away. But obviously I am doing something wrong. I have a set of dropdowns that trigger callbacks on graphs. I have been wracking my head about this. Any help/leads would be appreciated. The only pattern I see in the errors is they seem to emerge when the plotly express graphs are being called in the callbacks.

What am I doing wrong? I have searched all over online for help but nothing yet.

Sharing with some relevant snippets of code (this may be too long and many parts not important to the question, but to give you a general idea of what I have been working towards)

I can't figure out why my loop isn't working.

I have a database (36rows x 51columns, its name is "Seleccio") consisting of 3 factors (first 3 columns: Animal (12 animals), Diet (3 diets) and Period (3 periods)) and 48 variables (many clinical parameters) with 36 observations per column. It is a 3x3 crossover design so I want to implement a mixed model to include the Animal random effect and also Period and Diet fixed effects and the interaction between them.

A sample of the data (but with less rows and columns):

I am reading an image, getting objects that have a certain brightness value, and then plotting the X and Y coords to the image.

But, there is a huge group of outliers, which are all located in a rectangular part of the image, Its X and Y coords are 1110-1977 (width) and 1069-1905 (height). From here, I'm looping through this little square portion of the image, and from my pre-created x and y arrays any values that have the same coords as shown there are removed.

However, this removes a lot more coords, which, for example, have X in the range 1110-1977. So the end result is a cross pattern filtering when I only want the square in the center to be filtered. How would I do this?

Code