PyAnalySeries Reimagined: A Legacy Tool Reborn
PyAnalySeries is a Python application built on matplotlib, with a PyQt-based graphical interface, making it easily portable across platforms including Linux, macOS, and Windows.
It is designed as a modern continuation of the AnalySeries, the original application on MacOS, aiming to reproduce its core functionalities within a more robust and portable Python environment.
Special attention has been given to ergonomics, emphasizing simplicity and clarity, while offering intuitive interactivity such as zooming, panning, and scrolling, with linked or independent axis.
The core design follows a "Define then Apply" workflow for data processing operations such as filtering, sampling, and interpolation.
Documents are read and saved in an open format spreadsheet (xlsx) with multiple worksheets for organization. It is also possible to import series or pointers directly from the clipboard, following a simple copy (Ctrl+C) and paste (Ctrl+V) operation from an external spreadsheet.
The application leverages robust, well-tested modules for interpolation, notably SciPy, and features an interactive interface for defining interpolation pointers (formerly known as Linage and Splinage), allowing for precise placement and manipulation—either directly on data points or independently.
PyAnalySeries provides access to insolation computations through the Insolation module, including astronomical solutions and derived quantities such as eccentricity, obliquity, precession parameters, and various insolation metrics. It also integrates the Pyleoclim package for time series processing, including detrending, frequency filtering, and power spectral density (PSD) estimation.
Based on: numpy, pandas, matplotlib, scipy, shapely, openpyxl, PyQt, Inso, Pyleoclim
Conception and developments : Patrick Brockmann LSCE/CEA - IPSL
This project is distributed under the CeCILL v2.1 license.
Hevia-Cruz, F., Brockmann, P., Govin, A., Michel, E., and Paillard, D. (2025). Reviving AnalySeries: PyAnalySeries, a modern and collaborative open-source tool for time-series analysis. Past Global Changes Magazine, 33(2), 74–75. https://doi.org/10.22498/pages.33.2.74
A demo session on PyAnalySeries will take place during EGU 2026:
SC2.27 – Processing and visualizing 2-D datasets using the PyAnalySeries software for research and teaching
Wednesday, 06 May, 08:30–10:15 (CEST), Room 0.55
Questions, feedback, or suggestions can be shared here:
#49
The use of the application is detailed in the following Wiki page.
Tutorials can be found from the Wiki page
See installation.md for installation details.
See update.md for update details.
python PyAnalySeries.pypython PyAnalySeries.py test/ws_ex.xlsxpython PyAnalySeries.py test/MD95-2042.xlsx test/GeoB3938.xlsx
See shortcuts.md for shortcut settings.
See releases.md for release details.