Ruffus is an open-source computation pipeline library for Python, used in science and bioinformatics. It is designed to automate scientific and other analyses with a lightweight, standard-Python syntax, and can be installed from the Python Package Index.
Dask is an open-source Python library for parallel computing maintained by contributors across dozens of companies. The site describes uses including Dask DataFrames for pandas, parallel for loops, large arrays with NumPy and Xarray, and machine learning. It can run on a laptop or be deployed on resource managers such as Kubernetes or cloud.
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing statistical graphics, and covers relational, distribution, categorical, regression and multi-plot grids, along with figure theming and color palettes.
Glue is a Python library for exploring relationships within and among related datasets. It provides linked statistical graphics such as scatter plots, histograms and 2D and 3D images, with selections in one graph propagating to others. It supports user-specified links across datasets and scripting through Python's scientific libraries.
Fiber is a Python-based distributed computing library for modern computer clusters. It provides the same API as Python's standard multiprocessing library, uses Nanomsg for communication, and allows dynamic allocation of CPU, memory, and GPU resources. Installation uses pip install fiber.
A book by Brian Caffo, Roger D. Peng and Jeffrey Leek on assembling and leading a data science enterprise, based on the Johns Hopkins Executive Data Science Specialization. It covers a crash course in data science, recruiting and evaluating a team, and the structure of the data science pipeline. Available as PDF and EPUB; printed copies are sold through Lulu.
A book by Roger D. Peng and Elizabeth Matsui, dated 2017, about data analysis as an art. It discusses the thought process behind data analysis and covers R software development for building data science tools, including handling complex data, building R packages and custom data visualizations.
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Dask is an open-source Python library for parallel computing maintained by contributors across dozens of companies. The site describes uses including Dask DataFrames for pandas, parallel for loops, large arrays with NumPy and Xarray, and machine learning. It can run on a laptop or be deployed on resource managers such as Kubernetes or cloud.
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing statistical graphics, and covers relational, distribution, categorical, regression and multi-plot grids, along with figure theming and color palettes.
Glue is a Python library for exploring relationships within and among related datasets. It provides linked statistical graphics such as scatter plots, histograms and 2D and 3D images, with selections in one graph propagating to others. It supports user-specified links across datasets and scripting through Python's scientific libraries.
Fiber is a Python-based distributed computing library for modern computer clusters. It provides the same API as Python's standard multiprocessing library, uses Nanomsg for communication, and allows dynamic allocation of CPU, memory, and GPU resources. Installation uses pip install fiber.
A book by Brian Caffo, Roger D. Peng and Jeffrey Leek on assembling and leading a data science enterprise, based on the Johns Hopkins Executive Data Science Specialization. It covers a crash course in data science, recruiting and evaluating a team, and the structure of the data science pipeline. Available as PDF and EPUB; printed copies are sold through Lulu.
A book by Roger D. Peng and Elizabeth Matsui, dated 2017, about data analysis as an art. It discusses the thought process behind data analysis and covers R software development for building data science tools, including handling complex data, building R packages and custom data visualizations.
