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Title: Getting started — datafold 2.0.1 documentation

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Skip to main contenthttps://datafold-dev.gitlab.io/datafold/gettingstarted.html#main-content
https://datafold-dev.gitlab.io/datafold/index.html
Getting started https://datafold-dev.gitlab.io/datafold/gettingstarted.html
Tutorials https://datafold-dev.gitlab.io/datafold/tutorial_index.html
Software documentation https://datafold-dev.gitlab.io/datafold/api.html
Contributing https://datafold-dev.gitlab.io/datafold/contributing.html
References https://datafold-dev.gitlab.io/datafold/references.html
GitLabhttps://gitlab.com/datafold-dev/datafold/
PyPIhttps://pypi.org/project/datafold/
Getting started https://datafold-dev.gitlab.io/datafold/gettingstarted.html
Tutorials https://datafold-dev.gitlab.io/datafold/tutorial_index.html
Software documentation https://datafold-dev.gitlab.io/datafold/api.html
Contributing https://datafold-dev.gitlab.io/datafold/contributing.html
References https://datafold-dev.gitlab.io/datafold/references.html
GitLabhttps://gitlab.com/datafold-dev/datafold/
PyPIhttps://pypi.org/project/datafold/
Introductionhttps://datafold-dev.gitlab.io/datafold/intro.html
https://datafold-dev.gitlab.io/datafold/index.html
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#getting-started
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#quick-links
Source repositoryhttps://gitlab.com/datafold-dev/datafold
Contributing and feedbackhttps://datafold-dev.gitlab.io/datafold/contributing.html
PyPIhttps://pypi.org/project/datafold/
Documentationhttps://datafold-dev.gitlab.io/datafold/
Tutorialshttps://datafold-dev.gitlab.io/datafold/tutorial_index.html
Scientific literaturehttps://datafold-dev.gitlab.io/datafold/references.html
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#what-is-datafold
MIT-licensedhttps://gitlab.com/datafold-dev/datafold/-/blob/master/LICENSE
continuous k-nearest neighbor kernelhttps://arxiv.org/abs/1606.02353
dynamics-adapted cone kernelhttps://epubs.siam.org/doi/10.1137/140954544
this introduction pagehttps://datafold-dev.gitlab.io/datafold/intro.html
scientific literaturehttps://datafold-dev.gitlab.io/datafold/references.html
software documentationhttps://datafold-dev.gitlab.io/datafold/api.html
semantic versioninghttps://semver.org/
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#cite
this paperhttps://joss.theoj.org/papers/10.21105/joss.02283
JOSShttps://joss.theoj.org/
https://doi.org/10.21105/joss.02283https://doi.org/10.21105/joss.02283
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#how-to-get-it
Python>=3.9https://www.python.org/
piphttps://pip.pypa.io/en/stable/
setuptoolshttps://setuptools.pypa.io/en/latest/
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#from-pypi
herehttps://datafold-dev.gitlab.io/datafold/tutorial_index.html
official instructionshttps://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-pkgs.html#installing-non-conda-packages
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#from-source
githttps://git-scm.com/
ziphttps://gitlab.com/datafold-dev/datafold/-/archive/master/datafold-master.zip
tar.gzhttps://gitlab.com/datafold-dev/datafold/-/archive/master/datafold-master.tar.gz
tar.bz2https://gitlab.com/datafold-dev/datafold/-/archive/master/datafold-master.tar.bz2
tarhttps://gitlab.com/datafold-dev/datafold/-/archive/master/datafold-master.tar
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#contributing
issue trackerhttps://gitlab.com/datafold-dev/datafold/-/issues
herehttps://datafold-dev.gitlab.io/datafold/contributing.html
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#dependencies
requirements.txthttps://gitlab.com/datafold-dev/datafold/-/blob/master/requirements.txt
requirements-dev.txthttps://gitlab.com/datafold-dev/datafold/-/blob/master/requirements-dev.txt
Python scientific computing stackhttps://scipy.org/about/
NumPyhttps://numpy.org/
pandashttps://pandas.pydata.org/pandas-docs/stable/index.html
DataFramehttps://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html
scikit-learnhttps://scikit-learn.org/stable/
APIhttps://scikit-learn.org/stable/developers/develop.html
BaseEstimatorhttps://scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html
SciPyhttps://docs.scipy.org/doc/scipy/reference/index.html
#https://datafold-dev.gitlab.io/datafold/gettingstarted.html#how-does-it-compare-to-other-software
scikit-learnhttps://scikit-learn.org/stable/
BaseEstimatorhttps://scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html
set of algorithmshttps://scikit-learn.org/stable/auto_examples/manifold/plot_compare_methods.html#sphx-glr-auto-examples-manifold-plot-compare-methods-py
PyDMDhttps://github.com/PyDMD/PyDMD
Dynamic Mode Decomposition (DMD)https://en.wikipedia.org/wiki/Dynamic_mode_decomposition
PyDMD issue 86https://github.com/PyDMD/PyDMD/issues/86
PySINDyhttps://pysindy.readthedocs.io/en/latest/
previous Welcome to datafold https://datafold-dev.gitlab.io/datafold/index.html
next Introduction https://datafold-dev.gitlab.io/datafold/intro.html
Quick linkshttps://datafold-dev.gitlab.io/datafold/gettingstarted.html#quick-links
What is datafold?https://datafold-dev.gitlab.io/datafold/gettingstarted.html#what-is-datafold
Citehttps://datafold-dev.gitlab.io/datafold/gettingstarted.html#cite
How to get it?https://datafold-dev.gitlab.io/datafold/gettingstarted.html#how-to-get-it
1. From PyPIhttps://datafold-dev.gitlab.io/datafold/gettingstarted.html#from-pypi
2. From sourcehttps://datafold-dev.gitlab.io/datafold/gettingstarted.html#from-source
Contributinghttps://datafold-dev.gitlab.io/datafold/gettingstarted.html#contributing
Dependencieshttps://datafold-dev.gitlab.io/datafold/gettingstarted.html#dependencies
How does it compare to other software?https://datafold-dev.gitlab.io/datafold/gettingstarted.html#how-does-it-compare-to-other-software
Show Source https://datafold-dev.gitlab.io/datafold/_sources/gettingstarted.rst.txt
Sphinxhttps://www.sphinx-doc.org/
PyData Sphinx Themehttps://pydata-sphinx-theme.readthedocs.io/en/stable/index.html

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