Plotly-for-python | YouTube playlist on data visualization using Plotly | Data Visualization library
kandi X-RAY | Plotly-for-python Summary
kandi X-RAY | Plotly-for-python Summary
Files for my YouTube playlist on data visualization using Plotly with Python.
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QUESTION
This is a question that derives from a previous one, which can be found here: Multiple opacities in Mapbox - Plotly for Python
I was having some issues regarding having multiple opacities for multiple traces on a Mapbox map, each opacity associated with a particular value of the dataframe.
After following Rob's helpful answer (see link above), which led to the solution on the first topic, I found myself in another problem, as I want now kind of twist on his code.
While my first approach was to only have variations on the opacity of the traces, I would now need to have both variations on the opacity and the width of each trace, corresponding each of them to a different value on a particular dataframe.
I proceed to copy-paste the first part of Rob's answer, where he declares some functions and creates a dataframe:
...ANSWER
Answered 2022-Jan-03 at 18:00- given you are using same column to define width and opacity you only need one loop
- for width I think linear space is better than geometric space, hence have created
width_a
as below - both
opacity
andwidth
will move in step as it's cutting same column by same number of bins
QUESTION
I have the current figure in plotly (jupyter notebook code below), and was hoping to create the effect whereby when you hover or click over each trace, the whole trace is highlighted a different colour (in this example red). I tried implementing these examples from SOF: Plotly in Python: how to highlight a trace on hover? & How do I highlight an entire trace upon hover in Plotly for Python? with no luck. If anyone could help that would be amazing. Currently each trace remains lightgrey.
...ANSWER
Answered 2020-Sep-15 at 13:11So this was a problem in 2 parts as it turns out:
- The problem for me was that the widgets extension had not been enabled correctly (as I could check from executing jupyter nbextension list, the output was empty), which is why the fig would not render without .show() and why the on_click function did not work. You can fix this by first checking jupyter nbextension list, if it’s empty can you try in your conda env:
QUESTION
I have a basic dash application with the following app.py
file:
ANSWER
Answered 2020-Apr-03 at 17:13I think I managed to resolve half of the problem.
First, if you are using a method to generate your figure, you need to save it into a separate object:
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