mplcursors | Interactive data selection cursors for Matplotlib | Data Visualization library

You have overwritten function loadChart() by the following line:

Without knowing much about the libraries you are using I can see you are creating these annotation objects and then assigning them to a global variable that is re-assigned later and thus you lose the right object to make it visible.

Instead you could keep the annotation objects into a dictionary and try to retrieve them later when you need them based on an object.

I used a list to show you the idea, but you need a dictionary I guess to identify the right objects.

I modified your code a bit and it shows the desired behaviour if you resize the window...I guess you have to find a way to refresh the plot also:

The problem seems to be that G.nodes() isn't a list of labels. You can get the node numbers or labels via converting it to a list (list(G.nodes())).

An updated version could look like:

To have mplcursors only interact with some elements, a list of those elements can be given as the first parameter to mplcursors.cursor(). The list could be built from the return values of the calls to ax.scatter.

To modify the annotation text shown, a custom function can be connected. In the example below, the label and the y-position are extracted from the selected element and put into the annotation text. Such label can be added via ax.scatter(..., label=...).

(Choosing 'none' as the color for the "invisible" elements makes them really invisible. To make the code more "Pythonic" explicit indices can be avoided, working with zip instead of with enumerate.)

• The IndexError occurs because of df.columns.tolist()[x.target.index]
  • df.columns.tolist() is a list of 7 columns, which is then indexed by [x.target.index].
• df.iloc[x.target.index, :].to_dict() will get the desired row data for the point as a dict
  • A list comprehension creates a list of strings for each key value pair
  • '\n'.join(...) creates a string with each column separated by a \n

Here is an approach, moving the first curve over the given distance. Numpy arrays are used to simplify the loops. relim() and autoscale_view() recalculate the x and y limits to fit everything again inside a margin (this step can be skipped if the expected displacement is small).

Your code seems to be working for me, or what is exactly the problem?

Is it not the output that you are trying to achieve?

mplcursors automatically create annotations with the x and y positions. Only when you need extra information, you'd need to write a function to change the annotation depending on the selected point.

Here is some code, using a random image to show how it would work:

It's a bit unclear how you create your plot and how it looks like. The approach below assigns a label to each of the little bars. A broken_barh can only have one label for the whole set, so instead of drawing ax.broken_barh(), individual rectangles are created, each with their own label. An additional possibility is to also assign individual colors to each rectangle (the example below supposes a maximum of 20 colors).

In that case, mplcursors default generates an annotation with label, x and y position of the cursor. You can change the default annotation, for example only using the label.

Note that mplcursors.cursor(..., hover=True) shows an annotation while hovering. The default only shows the annotation when clicking.