{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis"},{"label":"Visualization","url":"https://skillfed.io/packages/category/scientific-engineering-visualization"},{"label":"Financial","url":"https://skillfed.io/packages/category/office-business-financial"},{"label":"Investment","url":"https://skillfed.io/packages/category/office-business-financial-investment"}],"enrichment":{"capability":"mplfinance provides matplotlib-based visualization for financial market data, enabling candlestick charts, OHLC plots, and technical analysis overlays from pandas DataFrames.","skillfed_tags":["financial-visualization","matplotlib-extension","technical-analysis"],"use_cases":["Plot daily or intraday candlestick charts with volume for stock or futures data stored in pandas.","Generate technical analysis charts with moving averages, support/resistance lines, and fill-between overlays.","Create Renko or Point & Figure charts for alternative price-movement analysis without manual matplotlib configuration.","Build chart exports for trading dashboards or financial reports with custom styling.","Visualize market data with non-trading day handling for weekend and holiday gaps."],"what_it_does":"mplfinance is a matplotlib wrapper that simplifies financial chart creation by automating the matplotlib boilerplate typically required for candlestick, OHLC, and price-movement plots. It accepts pandas DataFrames with Open, High, Low, Close data indexed by date and generates publication-ready financial visualizations with minimal code.\n\nThe package handles common financial charting tasks: rendering multiple plot types (candlestick, OHLC, Renko, Point & Figure), overlaying technical indicators like moving averages, displaying volume bars, and managing non-trading day gaps. It integrates tightly with pandas, making it natural for workflows that already use DataFrames for market data manipulation.","worth_installing":"Yes, if you need quick financial charting from pandas DataFrames and accept dormant maintenance. The package is stable, has no known vulnerabilities, and low install friction. However, do not rely on it for active bug fixes or new features\u2014test compatibility with your matplotlib and pandas versions before production use, and consider it a mature but no-longer-developed tool."},"id":"mplfinance","links":{"html":"https://skillfed.io/packages/mplfinance","md":"https://skillfed.io/packages/mplfinance.md","pypi":"https://pypi.org/project/mplfinance/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2023-08-02","license_spdx":null,"license_treatment":"permissive","name":"mplfinance","python_support":"unspecified","summary":"Utilities for the visualization, and visual analysis, of financial data"},"popularity":{"monthly_downloads":810548,"position":5007,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.12.10b0"}