GAF | GAF

I have a data frame like below and I am looking for simple solution for count of variable for column names start with number. after adding second row in dataframe.

I'm trying to get a combobox to update when I delete one Item but i can't get it to work.
I'm filling the ObservableCollection form an XML, then I bind it to the combobox, this part works just fine. When i click on the button delete i'am removing from the xml, and iI don't know how to trigger the removal from the observable collecion.

Here's my attempt so far :

ChargementScenario.Xaml

Goal: I would like to export these results from a zip code with the company name and address from this GAF website database. The last error it gave me was a df error in a Jupyter interpreter. The output of the search isn't as clean as other databases I have used. Any tips would be helpful. Would like to extract the phone number as well, seems you have to click on the record then hover of the phone number for that.

I am fairly new to pyspark. I have pyspark dataframe which has information about number of times a particular person has got message from a brand. It has three columns id, brand and count, as show below.

Been pulling my hair out over this one for several days. The Shiny app I'm building opens a database which regularly gets updated. As such, values in the columns can change, and I want to make sure the users can filter based on these values. Problem is: the checkboxes need to appear in seperate boxes (for organization purposes).

So, imagine a user sees:

Severity

[] CGI

[] GAF

Alliance

[]WAI

[]STAR

There's no problem creating these boxes. Initially, I made them all so the selected values were stored in "measures". Problem is: you can't have multiple checkboxGroupInput all sending values to 'measures' (i.e. input$measures) and filter on them (i.e. table_data %>% filter(Measure %in% input$measures).

I solved this issue by giving them all unique inputID's. I.e. input$Severity , input$Alliance . I am able to make the filtering work by manually writing: table_data %>% filter(Measure %in% input$Alliance| Measure %in% input$Severity)

But the moment I try to make the inputID's that I want to filter on automate, it simply won't work.

For instance:

I have the following JSOn response from a webhook call

My app is using Firebase Realtime Database to store information of each user. The tableView works fine. I added a searchBar and when I type letters in the searchBar, I can see that the amount of rows presented in the tableView is equal to the amount of users which contain these letters in their names. The problem is that the rows presented in the tableview (after typing letters in the search bar), contain the information of the first user till x user (x = amount of users which contain these letters in their names).

I am using mlr package in R to compare two learners, i.e. random forest and lasso classifier, on a binary classification task. I used nested cross-validation to compute performance. Then, I would like to compute the features' importance for the best classifier, random forest in this case. To achieve this I am using generateFeatureImportanceData() which: "Estimate how important individual features or groups of features are by contrasting prediction performances. For method “permutation.importance” compute the change in performance from permuting the values of a feature (or a group of features) and compare that to the predictions made on the unmcuted data." As I specified measure = auc, does the output res provides the decrease in auc for each feature from permuting its value?

library(easypackages)

I am trying to transform a file to dictionary but having error.