restyle | enforced system for building UI components | User Interface library

I've put together a suggestion that builds on previous contributions of mine using JupyterLab. You may find that it's a bit messy. But if this is what you're looking for conceptually, then we can clean it up. And alswo rewrite the whole thing to use "pure" Dash and not JupyterDash. The code snippet below will produce the following figure with:

1. a radio-item to lets you select one market, and
2. a checklist that will let you select any and all categories I believe are your Goals: ['Goal', 'Q1]

Here are a few scenarios for different combinations of selections:

You're not really looking to change the marker, but rather change the underlying data the the markers represent, since:

In my real dataset i want a button that allows to group by values in one columA (attribute A) or colulmB(attributeB)- to better display relations

And this can quickly become very painful following your setup. But it's both easy and elegant using Plotly Dash. So if you can use that instead, you should. The following setup lets you switch between two figures where the first is the original where the data is represented by df['species']. The second figure shows the same data, but for a different category defined in the column df['AttributeB'], and is a random choice between three fictional categories ['science', 'fiction', 'flowers']

I have fixed this now, i was relying on this working much like Python or R where colour is essentially figured out by the script rather than being explicitly given to it.

I'm aware this is still rough and i have alot to learn but i'm posting this in case it helps any future prospective js student.

In this case you can conditionally update the trace as shown here.

First when you add each trace give it a name (using 'linear' and 'sqrt' in this case):

Below is a complete setup that will give you the following three figures for these options:

This is just a guess from the documentation but there is no add_data() call so maybe try this for your first line:

I think this tutorial from plotly explains some of the issues in your code. Probably worth having a look!

1. The title is an attribute of the whole plot and not of each individual trace of the plot. So when you are setting layout(title='graph #') when you add each trace to the plot, you are setting it for the whole plot and overriding the value set in the previous trace. Since the last one you set is layout(title='graph 4'), this is the one you see when the plot is created.

2. You need to set the initial value of the visible attribute when you create each trace, so when the plot is created you see only one trace. In this case, when you create the traces, you need to set visible=TRUE for A and visible=FALSE for the rest.

3. Because you want to update the title of the plot, you cannot use the restyle method (take a look at the tutorial link above). You have to use the update method, which is used to change both the attributes of each trace and also to change the layout of the plot. With the update method, the value of arg is a list of lists. The first element of the main list is a list with the named values for updating the traces (just as you did before with restyle). The second element of the main list is another list with the named values for changing the layout.

Here is my code.

I am not sure which plot from that page you are trying to implement. Here is a way to implement first 2 of them.

Data :

The example you should look at the tutorial is the last one (with the sine waves). It hides and shows different traces of the plot depending on the value of the selection in the dropdown menu.

You just need to change the format of your dataframe to wide.