crp | Chinese Restaurant Process Clustering in Julia and Python

I hope someone may be able to help me. I have a list of IDs and blood results in output

dput(output)

I trying to compare two groups of patients (control and intervention) for multiple study visits.

Example of measurements: Hemoglobin, Troponin, Myoglobin, Creatinin, C reactive Protein (CRP)

This means I would like to see a difference between these groups for different Visits, e.g. intervention group has lower CRP at visit 2 than controls. Additionally, I would like to compare the patients with themselves, e.g. patient 2 has lower CRP at visit 3, than at visit 2.

Ultimately, I would like to show my data graphically (for a mean of the interventions and controls a line, one plot for every marker) and primarily do descriptive statistics without testing (since my sample size is pretty small and this is more explorative.

So far I have created a .csv with all data where I made columns indicating, if patients are control or intervention. This table is sortable by visit, control/intervention and patient ID.

i want to remove duplicate data from the array that i am getting from api and i have tried sorting, compairing, toSet().toList() but nothing seems to work. below is the data that i am getitng -:

I'm still new to this R program and hanging around with this program. And I got a trouble with counting values.

I'm trying to count rows that can be grouped by another cols but I can't find ways.

My data is like this

I am trying to remove outliers from a subset of observations grouped by a categorical variable. So that I can plot the boxplot without outliers and also get the t-stat of the new dataset.

I tried both 'group by' with data.table and aggregate with lists. However, always outliers are removed considering the whole dataset. Not from each subset.

Here is a part of the dataset. There are 40 column variables and 62 observations

I am trying to remove outliers using the following code

I have a table with multiple character variables (named First, Second etc.) Each of these variables contain a number of possible strings (e.g. "DBP", "Low PA"). I want to assign a background colour to each of these strings (e.g. "DBP" or "SBP = red, "Low PA" = blue).

I'd like to be able to this is one mutate statement, rather than writing seperate case_when statements for each column:

I have two dataframe which I want to join normally i do inner_join which gives only the one which are present in both dataframe and rest and not shown in my output.

How to do innerjoin and keep all the rows and assign label

First dataframe

I am hoping for help from the swarm intelligence! In preparing my dataframe of laboratory values across different time points, I encounter the following issue. My dataframe is in long format consisting of 5 variables: the subject ID (sid), timepoint (zeitpunkt), intervention group of the clinical trial (gruppe), the laboratory parameter (parameter), the actual value of the parameter (messwert) and the unit of the value (einheit).