Based on our record, Matplotlib seems to be a lot more popular than QuantConnect. While we know about 98 links to Matplotlib, we've tracked only 9 mentions of QuantConnect. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I use https://quantconnect.com/ to backtest new algos and discover new algos. They support C# and python. Source: over 1 year ago
Use quantconnect.com, their API forces you to use OOP there so it's a good practice. Source: almost 2 years ago
For stocks and crypto: QuantConnect and Backtrader For options: MesoSim and OptionNetExplorer. Source: almost 2 years ago
Only you can teach you how to do it. quantconnect.com has a lot of tutorials and other documentation that should be enough for you to learn from. I'm still learning the process of backtesting and I'm not aware of an "easy" way to perform this type of work. Source: almost 2 years ago
Thanks for the pointer. quantconnect.com and interactive brokers. I have a little fantasy that I'll do this once I retire and hand over 1% of my nest egg to it; see how it does... Hand over some more, etc... Source: over 2 years ago
Matplotlib: for displaying our image result. - Source: dev.to / about 2 months ago
Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / 3 months ago
Data visualization: utilizing Python's Matplotlib for visualizing order book information. - Source: dev.to / 6 months ago
For random, quick and dirty, ad-hoc plotting tasks my default is GNUPlot[1]. Otherwise I tend to use either Python with matplotlib, or R with ggplot2. I keep saying I'm going to invest the time to properly learn D3[4] or something similar for doing web-based plotting, but somehow never quite seem to find time to do it. sigh [1]: http://www.gnuplot.info/ [2]: https://matplotlib.org/ [3]:... - Source: Hacker News / 10 months ago
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 1 year ago
CloudQuant - Crowd based algorithmic trading development and backtesing for stock market trading.
GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.
quantra - A public API for quantitative finance made with Quantlib
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Backtrader - Backtrader is a complete and advanced python framework that is used for backtesting and trading.
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.