17 open-source projects similar to happydasch/btplotting, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Btplotting alternative.
mplfinance is a financial time-series plotter and market data visualization framework built on Matplotlib. It is designed to render market data frames into specialized charts, including candlesticks, OHLC bars, Renko bricks, and point-and-figure columns. The library distinguishes itself through a dedicated market data framework that manages trading calendars and non-trading periods, ensuring accurate temporal spacing by collapsing gaps during holidays. It also provides a system for technical analysis charting, enabling the overlay of moving averages, volume bars, and other technical indicator
dtale is a web-based interactive grid and visualizer for pandas dataframes, designed as an exploratory data analysis tool. It provides a browser-based interface for analyzing tabular data structures, allowing users to calculate statistics, detect outliers, and compute correlations without writing manual code. The project functions as an embedded data viewer that can be integrated into web applications via iframes or custom routes, with specific support for Django, Flask, and Streamlit. It enables the exploration of datasets through a combination of an interactive data grid and a data visualiz
:link: C++17 network / graph visualization library - Qt6 / QML node editor.
This is Datawrapper Core, the open source platform that powers the charting tools hosted as free service on datawrapper.de.
Netron is a visualizer for neural network and machine learning models. It provides a graphical interface that renders model architectures as interactive node-link diagrams, allowing users to inspect internal layers, tensors, and metadata. By performing static analysis, the tool enables the examination of model definitions without executing the underlying machine learning code. The software distinguishes itself through a schema-driven parsing engine that translates diverse proprietary model formats into a unified internal graph structure. This approach ensures interoperability, allowing users
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Portfolio and risk analytics in Python
Library for animated data visualizations and data stories.
AI tool to build charts based on text input