LiveCharts2
Pandas
LiveCharts2 | Pandas | |
---|---|---|
7 | 396 | |
5,393 | 41,983 | |
- | 0.6% | |
0.0 | 10.0 | |
about 1 year ago | 6 days ago | |
C# | Python | |
MIT License | BSD 3-clause "New" or "Revised" 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.
LiveCharts2
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LiveCharts2 on web assembly
LiveCharts2 is a charting library completely written in C# and it is a full rewrite of LiveCharts, now LiveCahrts can run everywhere MAUI, Uno Platform, Avalonia, Xamarin, WPF, WinForms, WinUI, console and on the server side.
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Roundup of .NET MAUI. - Week of August 15, 2022
LiveCharts2 (v2) is the evolution of LiveCharts (v0), it fixes the main design issues of its predecessor, it's focused to run everywhere, improves flexibility without losing what we already had in v0.
- Graphing Libraries that are as good as Excel?
- There is framework for everything.
- My CSharp project to collect air quality sensor data from Bluetooth device and plot real-time chart
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Chart for performance over time?
You can also look at this: https://lvcharts.net/
Pandas
- PHP Doesn't Suck Anymore
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AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience.
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Pandas reset_index(): How To Reset Indexes in Pandas
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method.
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Deploying a Serverless Dash App with AWS SAM and Lambda
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail. Instead, we'll focus on what's necessary to make it run serverless.
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Help Us Build Our Roadmap – Pydantic
there is pull request to integrate in both pydantic extra types and into pandas cose [1]
[1]: https://github.com/pandas-dev/pandas/issues/53999
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Stuff I Learned during Hanukkah of Data 2023
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.
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Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.
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Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential.
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What Would Go in Your Dream Documentation Solution?
So, what I'd like to do is write a documentation package in Python to recreate what I've lost. I plan to build upon the fantastic python-docx and docxtpl packages, and I'll probably rely on pandas from much of the tabular stuff. Here are the features I intend to include:
What are some alternatives?
Oxyplot - A cross-platform plotting library for .NET
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
ScottPlot - Interactive plotting library for .NET
tensorflow - An Open Source Machine Learning Framework for Everyone
LiveCharts2 - Simple, flexible, interactive & powerful charts, maps and gauges for .Net, LiveCharts2 can now practically run everywhere Maui, Uno Platform, Blazor-wasm, WPF, WinForms, Xamarin, Avalonia, WinUI, UWP.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
OpenTK - The Open Toolkit library is a fast, low-level C# wrapper for OpenGL, OpenAL & OpenCL. It also includes windowing, mouse, keyboard and joystick input and a robust and fast math library, giving you everything you need to write your own renderer or game engine. OpenTK can be used standalone or inside a GUI on Windows, Linux, Mac.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Interactive Data Display for WPF - Interactive Data Display for WPF is a set of controls for adding interactive visualization of dynamic data to your application. It allows to create line graphs, bubble charts, heat maps and other complex 2D plots which are very common in scientific software. Interactive Data Display for WPF integrates well with Bing Maps control to show data on a geographic map in latitude/longitude coordinates. The controls can also be operated programmatically.
Keras - Deep Learning for humans
MVVM Light Toolkit - The main purpose of the toolkit is to accelerate the creation and development of MVVM applications in Xamarin.Android, Xamarin.iOS, Xamarin.Forms, Windows 10 UWP, Windows Presentation Foundation (WPF), Silverlight, Windows Phone.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration