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Showing 2 open source projects for "python time series analysis"
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Deliver trusted data with dbtData teams use dbt to codify business logic and make it accessible to the entire organization—for use in reporting, ML modeling, and operational workflows.
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Windocks - Docker Oracle and SQL Server ContainersWindocks is a leader in cloud native database DevOps, recognized by Gartner as a Cool Vendor, and as an innovator by Bloor research in Test Data Management. Novartis, DriveTime, American Family Insurance, and other enterprises rely on Windocks for on-demand database environments for development, testing, and DevOps. Windocks software is easily downloaded for evaluation on standard Linux and Windows servers, for use on-premises or cloud, and for data delivery of SQL Server, Oracle, PostgreSQL, and MySQL to Docker containers or conventional database instances.
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timetools (for r-cran)
Seasonal/Sequential (Instants/Durations, Even or not) Time Series
Objects to manipulate sequential and seasonal time series. Sequential time series based on time instants and time durations are handled. Both can be regularly or unevenly spaced (overlapping durations are allowed). Only POSIX* format are used for dates and times. The following classes are provided : POSIXcti, POSIXctp, TimeIntervalDataFrame, TimeInstantDataFrame, SubtimeDataFrame ; methods to switch from a class to another and to modify the time support of series (hourly time... -
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Deem
Analyze time-course data with significance tests, clustering, modeling
Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional...
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