screening | An R package for efficient variable screening method | Machine Learning library

I have a list of df lst1. I would like to generate an excel file for each subject ID and each file will contain mutiple sheets, which equal to the df in lst. And at the end, I would like to add label on top the col names from dfs in lst.

I have a list of df lst1 and a df for variable name and label Label. How can I bind Label with each df in lst. I understand that all cols in lst will be charters and won't be able to used again for analysis. But that is what I want. How should I do that?

I try to write a function to filter a list that has muti df by ID and then add label to each dataset. However my codes did not work. Could anyone take a look of my codes and give me some guidance on what I did wrong? I am not that good working with list using map.

My codes are:

I'm currently trying to create an analyzer that will match a part of a query. The main use case is with this term "3D mammogram", for some reason using my autocomplete analyzer down below, produces no results. Upon removing the "operator" : "AND" option, elastic started to return results but still the results that are expected are with less score for some reason.

Here are the settings and the mappings for my index:

MAPPINGS:

Sorry for such silly question. I have a df that looks like this:

I want to split tx with data.frame(do.call("rbind", strsplit(as.character(df$tx), "\\s{2,}" )), stringsAsFactors=FALSE) , how can I keep Form in the new df? Also, how can i avoid the split results auto fill if it is empty?

sample df can be build using:

Is it a way to tell what charToRaw() outcome means?

I have a df like this:

I am trying to migrate to the new functional programming model for Spring Cloud Stream, replacing conditional StreamListener annotations like this

I have been using the R function gtsummary, but have now run into a problem with variables existing in subsets of each other. I have two screening tests that can independently be positive of one another which has created an issue with using by = with tbl_summary. This lead me to create two separate tables and combine them with the tbl_merge function.

However, I would like to calculate p-values for differences between the tests. Is there any way to do this with an object in the table_merge format or to extract information from it and calculate the statistics I need?

Per request, I post a code example from the mtcars database.

Screenshot of Website with inspect element

I am trying to press the "Integrations" button by using