dash-local-react-components
plotly
dash-local-react-components | plotly | |
---|---|---|
1 | 65 | |
22 | 15,288 | |
- | 1.4% | |
10.0 | 9.4 | |
over 1 year ago | 9 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dash-local-react-components
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Faster prototyping of local ract.js components in Dash Plotly visualizations using the dash-local-react-components package
dash-local-react-components is a small library that helps with speeding up the prototyping phase of Dash visualizations that contain small react components.
plotly
- Yes, Python and Matplotlib can make pretty charts
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/plotly/plotly.py
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How to Create a Pareto Chart 📐
First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.
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For all you computational people: What’s your favorite plotting software?
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.
- What does Power BI offer?
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Other programing options?
Plotly documentation (https://plotly.com/python/)
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Advice on upgrading my Presentation template
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.
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[OC] Clustering Images with OpenAI CLIP, T-SNE, UMAP & Plotly
Plotly GitHub repository: https://github.com/plotly/plotly.py
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Could you recommend some graphing GitHub Repo. for JupyterLab?
I'm using plotly.py now. This is why I love this community.
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Anyone else feel ‘trapped’ in power bi?
Depending on the nature of your reporting requirements, you could output a formatted Excel document with Python and a library such as openpyxl, and shove that into your SharePoint environment. This would be less dynamic than PBI reports can be, but may be sufficient. If you want viz as well, you can use something like ggplot or Plotly. Again, less dynamic than PBI for the same effort.
What are some alternatives?
vizro - Vizro is a toolkit for creating modular data visualization applications.
Altair - Declarative statistical visualization library for Python
TinyFeed - A lightweight, easy-to-use youtube channel & playlist feed aggregator
bokeh - Interactive Data Visualization in the browser, from Python
Dash.jl - Dash for Julia - A Julia interface to the Dash ecosystem for creating analytic web applications in Julia. No JavaScript required.
matplotlib - matplotlib: plotting with Python
MAGI - MAGI system is a cluster of three AI supercomputers that manage and support all task performed by the NERV organization from their Tokyo-3 headquarter.
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
folium - Python Data. Leaflet.js Maps.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
seaborn - Statistical data visualization in Python
bqplot - Plotting library for IPython/Jupyter notebooks