Pygoda: a graphical interface to efficiently visualise and explore large sets of geolocated time series

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Yann Ziegler , Jonathan L. Bamber


Modern-day data sets in geosciences may comprise hundreds or thousands of geolocated time series. Despite all the automated tools and new algorithms now available to process and prepare those data before using them in research projects, it can be useful or even necessary to visualise and investigate them manually. Whether it be for data quality assessment, for the preparation of a training data set for machine learning, to gain an understanding of the spatio-temporal characteristics of data, or for the inspection of specific observations in a larger data set, there are many cases where an efficient, dedicated tool would be useful for this task. Existing programming languages, libraries and software tend to be either cumbersome to use when aimed at simple visualisation, or lack functionalities when used in more advanced data exploration. Here we present and describe a new software package, Pygoda (doi:10.5281/zenodo.10009814), developed to provide a graphical interface for displaying and interrogating the spatial and temporal components of geolocated time series, offering a comprehensive insight into the data set properties. Time series from hundreds of observation stations can be plotted simultaneously in Pygoda, which comes with a range of functionalities to explore them, both individually or in groups, to extract or compute different parameters from them and use those in sorting and filtering, or to (semi-)manually categorise the records. At the time of writing, Pygoda remains in active development and future user suggestions and contributions are welcome.



Categorical Data Analysis, Climate, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Monitoring, Environmental Sciences, Environmental Studies, Fresh Water Studies, Geographic Information Sciences, Geophysics and Seismology, Glaciology, Graphics and Human Computer Interfaces, Hydrology, Longitudinal Data Analysis and Time Series, Meteorology, Other Earth Sciences, Other Statistics and Probability, Spatial Science


visualisation, time series, geolocated data, Data analysis, open source, free software, GUI


Published: 2023-10-24 03:16


CC BY Attribution 4.0 International

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