PyData

PyData
Name	PyData
Type	Community and Conference Network
Founded	2012
Focus	Data science, Python, Open source
Region	International

PyData PyData is an international community and conference network centered on data analysis using the Python ecosystem. It brings together practitioners from industry and academia including contributors to NumPy, pandas (software), SciPy, scikit-learn, and Matplotlib to share techniques, tools, and research. Conferences and meetups attract speakers affiliated with institutions such as Google, Microsoft, Facebook, Amazon (company), and universities like Massachusetts Institute of Technology, Stanford University, University of California, Berkeley, and Harvard University.

Overview

PyData convenes professionals from corporations such as IBM, Intel, NVIDIA, SAP, Oracle Corporation and research labs including Lawrence Berkeley National Laboratory, Los Alamos National Laboratory, CERN, and NASA. The network highlights projects like Jupyter Notebook, Dask, Xarray, statsmodels, Altair (software), Bokeh (company), and Seaborn alongside hardware and cloud platforms such as Amazon Web Services, Google Cloud Platform, Microsoft Azure, Kubernetes, and Docker. Attendees often reference standards and initiatives from OpenAI, Mozilla Foundation, Linux Foundation, Apache Software Foundation, and NumFOCUS.

History

Early gatherings featured contributors to Travis Oliphant, founder-associated projects including NumPy and SciPy and drew representation from labs such as Los Alamos National Laboratory and universities including University of Washington. As community growth continued, events attracted engineers from Spotify (company), Airbnb, Uber Technologies, Lyft, Dropbox, LinkedIn, eBay, and PayPal. Major milestone talks have referenced research from Google Research, Facebook AI Research, DeepMind, and academic groups at University of Toronto, Carnegie Mellon University, Princeton University, and Columbia University.

Community and Events

PyData events have been hosted in cities including New York City, London, Berlin, Paris, Tokyo, Sydney, Toronto, San Francisco, Seattle, Chicago, Boston, Bangalore, São Paulo, Mexico City, Amsterdam, and Zurich. Conferences often feature tutorials from authors of texts published by O'Reilly Media, Addison-Wesley, Springer Nature, and speakers associated with awards like the Turing Award and institutions such as IEEE and ACM. Community-organized meetups interact with groups including Women in Data Science, NumFOCUS, Python Software Foundation, Data Science Salon, Strata Data Conference, and RE•WORK.

Software and Libraries

Presentations cover core packages and related ecosystems: NumPy, pandas (software), SciPy, scikit-learn, TensorFlow, PyTorch, JAX (software), Jupyter Notebook, JupyterLab, Dask, Xarray, CuPy, Rapids (software suite), Apache Arrow, Parquet (software), Feather (file format), HDF5, NetCDF, statsmodels, LightGBM, XGBoost, CatBoost, spaCy, NLTK, Gensim, Transformers (library), Hugging Face, OpenCV, ImageNet, Keras, ONNX, MLflow, Airflow, Prefect (company), Great Expectations (software), TensorBoard, Plotly (company), Matplotlib, Seaborn, Bokeh (company), Altair (software), Holoviews, Panel (HoloViz), and Streamlit.

Governance and Organization

Organizing bodies include local user groups, academic departments at Massachusetts Institute of Technology, University of Cambridge, University of Oxford, ETH Zurich, University of California, Berkeley, and corporate sponsors from Google, Microsoft, Amazon (company), Facebook, IBM, NVIDIA, Intel, Red Hat, and Anaconda (company). Community stewardship often coordinates with nonprofit entities like NumFOCUS, Python Software Foundation, and regional partners such as Open Data Institute and DataKind. Event logistics have interfaced with venues tied to institutions such as Royal Society, British Library, Jacob K. Javits Convention Center, and Moscone Center.

Education and Training

Workshops and tutorials at PyData mirror curricula from universities and publishers: courses from edX, Coursera, Udacity, DataCamp, Kaggle, and textbooks from O'Reilly Media and Springer Nature. Instructors include faculty from Stanford University, Massachusetts Institute of Technology, University of Pennsylvania, University College London, and Imperial College London as well as industry educators from Google, Facebook, Amazon (company), Microsoft Research, and DeepMind. Outreach efforts coordinate with initiatives such as Girls Who Code, Black in AI, Latinx in AI, and Women in Machine Learning to broaden participation.

Category:Data science conferences