Plotly.NET
plotly
Our great sponsors
Plotly.NET | plotly | |
---|---|---|
4 | 64 | |
567 | 15,067 | |
7.6% | 1.9% | |
8.3 | 9.4 | |
16 days ago | 7 days ago | |
F# | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Plotly.NET
-
Exploratory Data Analysis with F#, Plotly.NET, and ML.NET DataFrames
There are many charting options for .NET in a Polyglot Notebook, including ScottPlot, the older XPlot Library, and Plotly.NET. I'm a big fan of Plotly for data visualization in Python, so I choose it when I can in other languages too. However, Plotly.NET is also becoming the defacto standard for data visualization in .NET notebooks.
-
Best libraries for scientific charts?
You can look at the csharp tests for examples https://github.com/plotly/Plotly.NET/tree/dev/tests/Plotly.NET.Tests.CSharp
-
F# + Plotly.NET + AngouriMath + Interactive: symbolic algebra for research!
Plotly.NET: awesome package for plotting in F# (in that article, it's there).
plotly
-
Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/plotly/plotly.py
-
How to Create a Pareto Chart 📐
First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.
-
Other programing options?
Plotly documentation (https://plotly.com/python/)
-
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.
-
[OC] Clustering Images with OpenAI CLIP, T-SNE, UMAP & Plotly
Plotly GitHub repository: https://github.com/plotly/plotly.py
-
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.
-
FiftyOne Computer Vision Model Evaluation Tips and Tricks – Feb 03, 2023
Because the confusion matrix is implemented in plotly, it is interactive! To interact visually with your data via the confusion matrix, attach the plot to a session launched with the dataset:
-
Create interactive plots with Python and Plotly
I've created a notebook in this Github repo to demo some of Plotly basic capabilities and I highly recommend checking out the official documentations for examples of each plot type and to discover lots of cool stuff that you can put in your notebook/site 🙂.
- GUI for a Dynamically Created Dataframe
-
Инструменты Python. Библиотеки для анализа данных
- plotly (https://plotly.com/python/);
What are some alternatives?
Altair - Declarative statistical visualization library for Python
bokeh - Interactive Data Visualization in the browser, from Python
matplotlib - matplotlib: plotting with Python
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
pygal - PYthon svg GrAph plotting Library
Graphviz - Simple Python interface for Graphviz
Cartopy - Cartopy - a cartographic python library with matplotlib support
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.