n8n-docs
plotly
Our great sponsors
n8n-docs | plotly | |
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6 | 65 | |
125 | 15,247 | |
5.6% | 2.3% | |
9.9 | 9.4 | |
6 days ago | 7 days ago | |
HTML | Python | |
GNU General Public License v3.0 or later | 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.
n8n-docs
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The 20 Most Trending Open Source Tools for Ecommerce
n8n (27.2k)
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Retrospective: Making a contribution to n8n
n8n documentation
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How to get more GitHub Stars and Followers on Open Source Projects ?
Focus on Documentation We get more traffic to our documentation than our main website. A well-documented project is always loved by the community. Open-source projects like Docusaurus make it super easy to build documentation portals that look great just out of the box. Adding links to the repository from the documentation can drive more visitors to your repository. What to include in documentation How to install/deploy the project If the project has a compiled software as the final product, make sure to add installation instructions. If the project is the codebase for a library such as an npm package or a Ruby gem, include details on how to import and use the library. If the project needs to be or can be deployed on platforms like Kubernetes, Docker, Heroku, and others, include separate guides for each of the options. Contributing guide Apart from the contributing guide doc in the codebase, add one to the documentation, too. It should include guides for setting up a local environment on different platforms like Docker, Mac OS, Ubuntu, Windows, and so on. Tutorials and code examples If this is applicable, it can be really helpful. How to guides on using using the project will show other devs how they can actually get started. It can be code examples if the project is a library. Architecture reference It will be helpful for the contributors if the documentation has details on different components of the project. For example, if the project has server and client components, include a diagram on how everything works together. Here are some projects with great documentation: https://docs.nestjs.com/ https://docs.n8n.io/ https://guides.rubyonrails.org/ https://plotly.com/python/ https://docs.mapbox.com/ https://www.github-stars.com or Github24.
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12 ways to get more GitHub stars for your open-source project
Here are some projects with great documentation: a) https://docs.nestjs.com/ b) https://docs.n8n.io/ c) https://guides.rubyonrails.org/ d) https://plotly.com/python/ e) https://docs.mapbox.com/
- Stock market and crypto tracking with open source tools
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How to automatically manage contributions to open-source projects 🏷️
Contribute to n8n: You can work on open issues, create nodes, improve our docs, or write a blog post.
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?
Docker Compose - Define and run multi-container applications with Docker
Altair - Declarative statistical visualization library for Python
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
bokeh - Interactive Data Visualization in the browser, from Python
good-first-issue - Make your first open-source contribution.
matplotlib - matplotlib: plotting with Python
Strapi - 🚀 Strapi is the leading open-source headless CMS. It’s 100% JavaScript/TypeScript, fully customizable and developer-first.
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
Nest - A progressive Node.js framework for building efficient, scalable, and enterprise-grade server-side applications with TypeScript/JavaScript 🚀
folium - Python Data. Leaflet.js Maps.
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]