matplotlib/mplfinance
Mplfinance
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 indicators on price action plots.
The toolkit covers a broad range of capabilities, including the organization of vertically stacked subplots with shared axes and the application of consistent visual themes. It supports market annotations such as trend lines, the handling of missing data, and the ability to refresh charts for real-time data feeds. Visualizations can be exported to various formats including PDF, SVG, PNG, and JPG.
Features
- Matplotlib - Uses Matplotlib's object-oriented API to render financial data into static plots and figures.
- Financial Time-Series Plotters - Provides a specialized framework for rendering OHLC, candlestick, Renko, and point-and-figure charts from market data.
- Non-Trading Gap Management - Manages trading calendars to ensure accurate temporal spacing by collapsing gaps during non-trading periods.
- Candlestick Charts - Renders financial data as candlesticks with adjustable hollow and filled bar styles.
- Financial Market Visualizers - Renders professional financial price charts including candlesticks and OHLC bars from time-series data.
- OHLC Bar Charting - Visualizes open, high, low, and close market data using traditional tick-based price bars.
- Trading Calendar Alignment - Collapses non-trading gaps on the x-axis to ensure accurate temporal spacing of market data.
- Financial Charting Extensions - Implements a specialized plotting toolkit for creating financial charts and technical analysis visualizations using Matplotlib.
- Matplotlib Subplot Compositions - Implements the composition of multiple synchronized subplots within a single figure for price and volume overlays.
- Financial Charting - Generates a comprehensive suite of financial plots including OHLC, candle, line, Renko, and point-and-figure.
- Pandas Financial Frameworks - Builds upon Pandas DataFrames to manage time-series alignment and calculate technical indicators.
- Technical Indicators - Provides capabilities to overlay moving averages and other financial technical indicators on price charts.
- Technical Analysis Visualizers - Overlays moving averages, volume bars, and technical indicators on financial price charts.
- Live Chart Animations - Develops dynamic charts that update in real time to track live streaming price feeds.
- Plot Axis Customizers - Provides controls for adjusting axis titles, date formatting, and coordinate system labels.
- Plot Styling Configurators - Provides tools for setting global plot styling and aesthetic themes across financial charts.
- Renko Charting - Generates price charts based on price movement bricks rather than fixed time intervals.
- Stacked Subplots - Generates vertically stacked subplots sharing a single axis to visualize price action alongside indicators.
- Point and Figure Charting - Plots price reversals using columns of symbols based on configurable reversal parameters.
- Real-Time Plot Updates - Enables dynamic refreshing of charts using animation techniques for streaming market data feeds.
- Chart Generators - Generates specialized financial chart geometries from structured OHLC data based on configurable rules.
- Trading Volume Charts - Adds dedicated volume charts to financial plots to visualize trading activity over time.
- Plot Layout Engines - Organizes multiple financial data panels into a single figure with configurable relative sizes and alignments.
- Chart Visual Style Customizations - Applies consistent visual themes to colors, grid styles, and axis placements using predefined configurations.
- Theme Customization - Allows the definition and saving of aesthetic themes for charts through specific color schemes and font settings.
- Financial Analytics - Visualization tools for financial market data.
- Visualization Tools - Financial market data visualization using Matplotlib.
- Financial Visualization - Matplotlib-based utilities for financial data plotting.
- Visualization Tools - Matplotlib-based visualization for financial market data.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
