PyQtGraph VS plotly

Very interesting and promising package.

I especially like that there is a PyQt interface which might provide an alternative to another great package: pyqtgraph[0].

[0] https://github.com/pyqtgraph/pyqtgraph

PyQtGraph - Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.

Image, 3D, or data visualization applications using OpenCV and the SciPy ecosystem. The Graphics View Framework can display an image and let the user interact with it, and the Python ecosystem is very rich for image processing, data analysis, and visualization. For example, LabelMe for image labeling, PyQtGraph for scientific graphics, or custom QWidget integration in Maya.

I don't think that's related to your error though - from the backtrace, it looks like the plotWidget has plotItem attribute that's somehow been assiged to itself (or maybe some other PlotWidget) , so is just endlessly recursing as it tries to proxy the same attribute lookup (presumably 'clear') to itself. Looking at the source, the plotitem is either created as a new PlotItem() object if not provided, or passed in to the constructor, so I'd check how this gets initialised - eg. does this get set as a property in your .ui file? Are you setting it to the widget itself somehow?

I did something like this recently but I used pyqtgraph: https://www.pyqtgraph.org/

# import plotly import plotly.express as px # create your chart type, for more chart types: https://plotly.com/python/ fig = px.bar(df, x = letter, y = frequency) # make chart prettier fig.update_layout( plot_bgcolor="White", height=700 ) # display chart fig.show()

Right off the bat, there’s a massive spike around early 2024–03 that stands out — yet, it’s hard to pinpoint which specific article triggered this rush just by looking at this static chart. To dig deeper and see if a particular article caused this jump, I decided to try something more interactive with Plotly for a clearer view.

plotly

Github: https://github.com/plotly/plotly.py

First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.

my good dude wake up and smell the plotly. Knowing the ins and outs of matplotlib is helpful but doing interactive stuff with jupyter I always use plotly.

Plotly documentation (https://plotly.com/python/)

I don´t know your workflow, but I use 2 markdown based presentations: obsidian advance slides and Quarto presentations. The former is a plugin for Obsidian, which is the software I use to take all my notes, write my thesis, etc., so It makes it extremely easy to make presentations since all my information is in Obsidian. In the other hand, Quarto is a publishing system (articles, presentations, websites books) that can be easily integrated with python and R. This makes it supper convenient for showing my data to my PI since I can analyze my data and at the same time make a presentation for the data. Besides this, Quarto also integrates with my Zotero library, so I can insert citations. Lastly, one thing that made my Quarto presentations infinitely better that the powerpoints, Is that I can insert interactive graphs with plotly, so when I'm showing my data, my PI is able to explore the data inside the presentation.