Awesome GitHub RepositoriesMatplotlib Subplot Compositions

QuantStats is an open-source Python library that calculates risk and return metrics from a portfolio return series and generates comprehensive HTML tear sheets. It computes dozens of financial statistics—including Sharpe ratio, drawdown, and volatility—in a single pass over the input data, using vectorized pandas operations for efficiency. The library distinguishes itself by combining portfolio performance analysis with Monte Carlo simulation, which models thousands of random return paths to estimate the probability of reaching financial targets or hitting loss thresholds. It produces self-co

mplfinance 是一个基于 Matplotlib 构建的金融时间序列绘图和市场数据可视化框架。它旨在将市场数据帧渲染为专业图表，包括蜡烛图、OHLC 条形图、Renko 砖形图以及点数图（point-and-figure）。 该库的独特之处在于其专用的市场数据框架，该框架管理交易日历和非交易时段，通过在节假日期间折叠间隙来确保准确的时间间隔。它还提供了一个用于技术分析绘图的系统，能够在价格走势图上叠加移动平均线、成交量柱状图和其他技术指标。 该工具包涵盖了广泛的功能，包括组织具有共享轴的垂直堆叠子图以及应用一致的视觉主题。它支持市场标注（如趋势线）、缺失数据处理以及为实时数据源刷新图表的能力。可视化结果可导出为 PDF、SVG、PNG 和 JPG 等多种格式。

Alphalens is a quantitative alpha factor analysis library designed to measure the predictive power of financial factors. It serves as a computational toolset for processing financial time series and calculating performance metrics to evaluate quantitative trading hypotheses. The library distinguishes itself through the use of quantile-based data binning to analyze return distributions across different factor strength levels. It aligns historical alpha signals with forward-looking price changes to isolate predictive effects and transforms these metrics into heatmaps and time-series charts for