visualizations | InPhO project is to bring graphical representations

Let's say you want to use some library. Let its name be ABC. ABC has some function, let's say function1. If you write

While it is possible to filter the data in Python, it can introduce significant network overhead depending on the data size (the data is transferred from the server to the client each time the filter changes). If you do the filtering client side, you only have to transfer the data once, i.e. the performance difference can be dramatic.

The client side filtering can be implemented by adding a JavaScript asset (i.e. a .js file placed in the assets folder) with the filtering function as per the documentation,

You forgot to specify the axis for each plot, so it is plotting them all on the same axis.

The 5,95 is calculated from the percentage score which is obtained via a separate JSON request. The value is calculated as 100 - (100 * score):

I suspect you are able to pick out the correct chunk of the Object, i.e. res.data.value but I think the issue here is that your initial state is undefined. If your render doesn't account for this then it's likely throwing a "Cannot access ... of undefined" error.

1. Provide valid initial state. Since res.data.value is an array I'll make the assumption that's what you are trying to render into a table. Start with an initial empty array for the data state.

Please try adding

The workbooks steps do not understand things like the fork operator which can return many tables of data, it only knows how to visualize the first table.

The easiest way to get what you want is to use a [merge data source] to duplicate a query result (https://github.com/microsoft/Application-Insights-Workbooks/blob/master/Documentation/DataSources/DataSources.md#merge-data-from-different-sources)

1. Create your query, returning all the columns you want, vizualized the way you want. Give it a useful name, like you've shown in the screenshot.

2. Add another query step, this time in the data source dropdown, choose merge

3. in the merge step's setting, use the "Add Merge" option, and in the popup that appears, chose the merge type "Duplicate Table", and pick the step named in step 1

4. the merge step allows you to add calculated columns as well, if you need to do math on 2 other columns, like computing percentages/rates, etc. use the "add new item" item in the toolbar of the merge step. you can also rename, reorder, remove columns of data

5. then run the merge step and choose the other visualization

The merge step can do other kinds of merges/unions/joins as well, between disparate sources. so you can merge together data from Azure Resource Graph (like properties/tags) with data from metrics, and data from logs into one grid. And the merge step can do all of that work in just one merge step, you don't need to add multiple merge steps (x = a union b, then another step of y = x union c, you can do it as multiple joins/unions in the one merge step.),

if you use merge this way to join/union data sources, you can hide the original sources, and the merge will still work. however, merges cannot depend on hidden merges yet, hence my suggestion that people use one merge step that does multiple joins instead of multiple merge steps that each do one.

For this particular situation if you don't use the deafault filebeaat-* index there are issues getting the prebuilt dashboards to spin up. I dropped the custom indexing that I had in my configuration and I was able to get the dashboards to load properly.

First of all try dplyr::mutate...

Anyway: Use across rather then mutate_at -> Scoped verbs (_if, _at, _all) have been superseded by the use of across() in an existing verb

This code is explicitly on your Dem_edu columns and it should work now