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Panda CSS is a styling engine that generates atomic CSS from written styles at build time with no runtime cost. It supports design tokens, semantic tokens and themes, and recipes with variants, all type-safe. It runs through the CLI, PostCSS or a bundler, generating a typed styled-system directory for import.
PandaBomber is a gaming resource for guides, communities, tools, game discovery, or reference links.
PandaCD is a file-sharing community where artists share their own music under Creative Commons and artist-permitted licences. Users can pay what they want with cryptocurrency, and the site lists torrents filtered by tags, licence and payment option.
Paper Panda is an academic paper search platform that provides access to 250 million research papers. Users can locate paper PDFs, verify open access status, explore related citations, and access full-text PDFs in one click. The service reduces time spent navigating paywalls, login requirements, and redirect pages when retrieving research content.
pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. It is described as a data analysis and manipulation tool built on top of Python. Documentation, a user guide and an API reference are available.
Codecademy's Data Scientist: Machine Learning Specialist Career Path is a beginner-level course covering Python 3, SQL, pandas, scikit-learn, Matplotlib, and TensorFlow. The path is listed as taking 95 hours on average and includes 59 projects with no prerequisites, and is described as teaching analysis of data, drawing predictions with machine learning, and building neural networks.
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.
Data School is a blog about data science and machine learning. Its posts cover topics such as the difference between AI and machine learning, learning scikit-learn, AI progress, and using pandas for calculations. Posts are tagged by subject including Python, AI, and machine learning.
Matt Harrison is a personal blog authored by Matt Harrison. The blog covers topics including Amazon book piracy, the Effective Pandas book, Python and data science courses, and general software development content.
Mimi Panda is a service for converting images into coloring pages and paint by numbers, using graphic techniques and algorithms developed by its team. It offers free coloring pages and a paint by numbers converter, an API service for enterprise clients, and a subscription-based Mimi Profile service with higher quality and a personal account.
The Python Data Science Handbook by Jake VanderPlas is published as a website containing the full text, organized into chapters on IPython, NumPy, Pandas, Matplotlib and machine learning. The text is released under the CC-BY-NC-ND license and the code under the MIT license; the content is available on GitHub as Jupyter notebooks.
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. It provides high-level APIs in Java, Scala, Python and R, and supports Spark SQL, pandas API on Spark, MLlib, GraphX and Structured Streaming. The documentation covers downloads, the shell and client applications.
Statsmodels is a Python module providing classes and functions for estimating statistical models, conducting statistical tests, and statistical data exploration. It supports model specification using R-style formulas and pandas DataFrames, and is released under the open source Modified BSD (3-clause) license.
