{"categories":[{"label":"Visualization","url":"https://skillfed.io/packages/category/scientific-engineering-visualization"},{"label":"Investment","url":"https://skillfed.io/packages/category/office-business-financial-investment"}],"enrichment":{"capability":"Downsamples time series data using the Largest-Triangle-Three-Buckets algorithm to reduce visually redundant points while preserving overall shape, built on numpy.","skillfed_tags":["time-series","data-reduction","visualization"],"use_cases":["Reduce large time series datasets for faster web-based plot rendering without losing visual fidelity.","Compress financial or stock price time series for display in dashboards or reports.","Downsample sensor or monitoring data (CPU usage, temperature, etc.) for visualization while retaining trend shape.","Prepare time series for interactive charting libraries where point count affects performance.","Filter IoT or real-time metric streams for efficient storage and display of historical data."],"what_it_does":"lttb is a numpy-based implementation of Steinarsson's Largest-Triangle-Three-Buckets algorithm, a data reduction technique specifically designed for visual representation of time series. It removes visually redundant data points while preserving the overall shape and variability, making it useful for rendering plots with fewer points and smaller file sizes. It is not a statistical aggregation or smoothing tool\u2014it's a visual filtering method.\n\nThe package provides a single main function, `downsample()`, which takes a 2D array (time values in the first column, metric values in the second) and returns a downsampled version with a specified number of output points. Input validation is configurable: by default it checks for two columns, strictly increasing x-values, and no NaN values, but these checks can be customized or disabled.","worth_installing":"Yes, if you need to downsample time series for visual display. The package is lightweight, has no complex dependencies, and solves a specific problem well. The dormant maintenance status is not a blocker for stable, mature code, but verify that the algorithm meets your specific data characteristics and that you don't need active support."},"id":"lttb","links":{"html":"https://skillfed.io/packages/lttb","md":"https://skillfed.io/packages/lttb.md","pypi":"https://pypi.org/project/lttb/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2024-09-06","license_spdx":null,"license_treatment":"permissive","name":"lttb","python_support":"supports_current","summary":"Largest-Triangle-Three-Buckets algorithm for downsampling time series-like data"},"popularity":{"monthly_downloads":85646,"position":13911,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.2"}