Motivation: Novel machine learning and statistical modeling studies rely on\nstandardized comparisons to existing methods using well-studied benchmark\ndatasets. Few tools exist that provide rapid access to many of these datasets\nthrough a standardized, user-friendly interface that integrates well with\npopular data science workflows.\n Results: This release of PMLB provides the largest collection of diverse,\npublic benchmark datasets for evaluating new machine learning and data science\nmethods aggregated in one location. v1.0 introduces a number of critical\nimprovements developed following discussions with the open-source community.\n Availability: PMLB is available at https://github.com/EpistasisLab/pmlb.\nPython and R interfaces for PMLB can be installed through the Python Package\nIndex and Comprehensive R Archive Network, respectively.\n