Notebooks offered in Noteable
Here are all the Notebook Servers with the respective primary libraries listed, which are currently available in Noteable.
These are not a comprehensive lists, however it does list the libraries and extensions we have specifically chosen to install.
Hover over the library name for a brief description of that library, and the verson installed. Each library should also link you to documentation for that library.
Standard Notebook
Standard Notebook is the default python 3 notebook, with a wide selection of libraries includes.
- Based on the jupyter/minimal-notebook image.
- Includes nbgrader and +GitRepo tools for document sharing.
- Provide rubberband, exercise, and exercise-2 extensions. Note these are not related to nbgrader in any way.
- Enables delete directories with content.
- Data Access libraries: beautifulsoup4, dill, libxml2, lxml, protobuf, sqlalchemy, textblob, unixodbc, and xlrd
- Data Science libraries: pandas and dask
- Data Visualization tools: bokeh, graphviz, ipywidgets, ipympl, k3d, mpld3, plotly, seaborn, widgetsnbextension, and wordcloud
- Image Processing: imagemagick, opencv, scikit-image, and spectral
- Machine Learning libraries: scikit-learn
- Stats & Data Modelling libraries: h5py, hdf5, numexpr, numpy, pytables, quantecon, scipy, statsmodels, and sympy
- Other libraries include: cloudpickle, cython, ffmpeg, netcdf4, nltk, numba, patsy, rise, vega, and vincent
SageMath Notebook
The Sagemath Notebook provides Sagemath 9 in python 3 notebook, with a wide selection of libraries included.
- Based on the sagemath/sagemath image.
- Includes nbgrader and +GitRepo tools for document sharing.
- Provide rubberband, exercise, and exercise-2 extensions. Note these are not related to nbgrader in any way.
- Enables delete directories with content.
- Data Access libraries: beautifulsoup4, dill, libxml2, lxml, protobuf, sqlalchemy, textblob, unixodbc, and xlrd
- Data Science libraries: pandas and dask
- Data Visualization tools: bokeh, graphviz, ipywidgets, ipympl, k3d, mpld3, plotly, seaborn, widgetsnbextension, and wordcloud
- Image Processing: imagemagick, opencv, scikit-image, and spectral
- Machine Learning libraries: scikit-learn
- Stats & Data Modelling libraries: h5py, hdf5, numexpr, numpy, pytables, scipy, statsmodels, and sympy
- Other libraries include: cloudpickle, cython, ffmpeg, netcdf4, nltk, numba, patsy, rise, vega, and vincent
RStudio Notebook
The RStudio UI overlayed on a Jupyter notebook, with an extensive selection of additional libraries included.
- Based on the jupyter/r-notebook image.
- A personal & individual RStudio server providing the RStudio IDE
- Data Manipulation in R: r-arm and r-data.table
- Some open Source data sets: r-nhanes, r-nycflights13, and r-ukbabynames
- Tools for profiling code: r-bench, r-devtools, r-lintr, r-microbenchmark, r-profvis, r-styler, r-testthat, and r-usethis
- Document and article writing in R: r-blogdown, r-bookdown, r-flexdashboard, r-reprex, r-rmarkdown, r-rticles, and r-xaringan
- GeoSpatial tools in R: r-ggally, r-ggforce, r-ggmap, r-leaflet, r-leaflet.extras, r-mapedit, r-mapview, r-rgdal, r-rgeos, r-sf, r-spdep, and r-stars
- Visualisations & graphics uner R: r-cowplot, r-diagrammer, r-fields, r-forecast, r-gganimate, r-ggplot2, r-ggraph, r-igraph, r-magick, r-plotrix, r-vcd, and r-viridis
- A selection of R-Libraries: r-bestglm, r-boot, r-brms, r-car, r-caret, r-coda, r-crayon, r-dbi, r-domc, r-doparallel, r-drat, r-foreach, r-foreign, r-fs, r-furrr, r-future, r-gbm, r-gh, r-glmnet, r-glue, r-gridextra, r-here, r-hexbin, r-htmltools, r-htmlwidgets, r-httr, r-janeaustenr, r-jsonlite, r-kableextra, r-keras, r-knitr, r-rlang, r-lars, r-lasso2, r-lme4, r-lobstr, r-loo, r-lubridate, r-mcmcpack, r-mgcv, r-nlme, r-openxlsx, r-pkgdown, r-plyr, r-pool, r-promises, r-quanteda, r-r2jags, r-randomforest, r-rcpp, r-rcpparmadillo, r-rcppeigen, r-rcurl, r-readxl, r-reshape2, r-rjags, r-rocr, r-rodbc, r-roxygen2, r-rsqlite, r-rvest, r-sessioninfo, r-shiny, r-shinydashboard, r-shinyjs, r-shinythemes, r-smoothmest, r-stargazer, r-tensorflow, r-tidybayes, r-tidygraph, r-tidymodels, r-tidyverse, r-topicmodels, r-tree, r-xml, r-xml2, r-xmlschema, r-xtable, and rpy2
- Data Access libraries: beautifulsoup4, dill, libxml2, lxml, protobuf, sqlalchemy, textblob, unixodbc, xlrd, and xmlschema
- Data Science libraries: pandas and dask
- Data Visualization tools: bokeh, graphviz, ipywidgets, ipympl, k3d, mpld3, plotly, seaborn, widgetsnbextension, and wordcloud
- Image Processing: imagemagick, opencv, scikit-image, and spectral
- Machine Learning libraries: scikit-learn
- Stats & Data Modelling libraries: h5py, hdf5, numexpr, numpy, pytables, quantecon, scipy, statsmodels, and sympy
- Other libraries include: cloudpickle, cython, ffmpeg, netcdf4, nltk, numba, patsy, rise, vega, and vincent
R with Stan Notebook
The R + Stan notebook adds Stan packages to R, with a wide selection of additional libraries included.
- Based on the jupyter/r-notebook image.
- Includes nbgrader and +GitRepo tools for document sharing.
- Provide rubberband, exercise, and exercise-2 extensions. Note these are not related to nbgrader in any way.
- Enables delete directories with content.
- The following R libraries from cran.rstudio.com: alr3, greta, monomvn, repurrrsive, and spBayes
- A selection of R-Libraries: r-base, r-caret, r-crayon, r-devtools, r-forecast, r-hexbin, r-htmltools, r-htmlwidgets, r-lobstr, r-nycflights13, r-openxlsx, r-plyr, r-quanteda, r-randomforest, r-rcurl, r-readxl, r-reshape2, r-rlang, r-rmarkdown, r-rodbc, r-rsqlite, r-shiny, r-tidyverse, r-topicmodels, r-ukbabynames, r-xml, r-xml2, r-xmlschema, and rpy2
- Some Stan-specific libraries: r-bart, r-bas, r-bayesplot, r-bayestree, r-boa, r-brms, r-coda, r-codetools, r-dplyr, r-effects, r-ggplot2, r-irdisplay, r-islr, r-lme4, r-loo, r-mcmcpack, r-nhanes, r-nlme, r-openintro, r-plotmcmc, r-quanteda, r-repr, r-rstan, r-rstanarm, and r-xgboost
- Data Access libraries: beautifulsoup4, dill, libxml2, lxml, protobuf, sqlalchemy, textblob, unixodbc, xlrd, and xmlschema
- Data Science libraries: pandas and dask
- Data Visualization tools: bokeh, graphviz, ipywidgets, ipympl, k3d, mpld3, plotly, seaborn, widgetsnbextension, and wordcloud
- Image Processing: imagemagick, opencv, scikit-image, and spectral
- Machine Learning libraries: scikit-learn
- Stats & Data Modelling libraries: h5py, hdf5, numexpr, numpy, pytables, quantecon, scipy, statsmodels, and sympy
- Other libraries include: cloudpickle, cython, ffmpeg, netcdf4, nltk, numba, patsy, rise, vega, and vincent
Python2 Notebook
The Python 2 notebook provides a selection of libraries under the python 2 environment. It is not actively maintained.
- Python 2 is no longer officially supported by the Python community and was removed from the Jupyter notebook images in summer 2019.
- Based on an old release of jupyter/minimal-notebook image.
- Provide rubberband, exercise, and exercise-2 extensions. Note these are not related to nbgrader in any way.
- Enables delete directories with content.
- Data Access libraries: beautifulsoup4, dill, sqlalchemy, and xlrd
- Data Science libraries: pandas
- Data Visualization tools: bokeh, ipywidgets, matplotlib, mpld3, and seaborn
- for Image Processing: scikit-image and spectral
- Machine Learning libraries: scikit-learn and tensorflow
- Stats & Data Modelling libraries: h5py, hdf5, numexpr, numpy, scipy, statsmodels, and sympy
- Other libraries include: cloudpickle, cython, netcdf4, nltk, numba, patsy, rise, and vincent
Language and Machine Learning
The Language and Machine Learning Notebook is a specialist python 3 notebook, with a selection of libraries that focus on Natural Language Processing and Machine Learning.
- Based on the jupyter/tensorflow-notebook image.
- Includes nbgrader and +GitRepo tools for document sharing.
- Provide rubberband, exercise, and exercise-2 extensions. Note these are not related to nbgrader in any way.
- Enables delete directories with content.
- Data Access libraries: beautifulsoup4, libxml2, lxml, protobuf, sqlalchemy, textblob, unixodbc, and xlrd
- Data Science libraries: pandas and dask
- Data Visualization tools: bokeh, graphviz, ipywidgets, ipympl, k3d, mpld3, plotly, seaborn, widgetsnbextension, and wordcloud
- Image Processing: imagemagick, opencv, scikit-image, and spectral
- Machine Learning libraries: nltk, scikit-learn, spacy, and tensorflow
-
Includes the full nltk data collection (
“all”
), theen_core_web_sm
for spaCY's default model, and the Official Models and datasets for tensorflow - Stats & Data Modelling libraries: numexpr, numpy, pytables, scipy, statsmodels, and sympy
- Other libraries include: cloudpickle, cython, ffmpeg, numba, patsy, rise, vega, and vincent
Julia Notebook
The Julia Notebook Julia on top of R, with a wide selection of libraries includes.
- Based on the jupyter/datascience-notebook image.
- Includes nbgrader and +GitRepo tools for document sharing.
- Provide rubberband, exercise, and exercise-2 extensions. Note these are not related to nbgrader in any way.
- Enables delete directories with content.
- The Julia compiler and base environment with IJulia to support Julia code in Jupyter notebooks.
- The following Julia libraries: Gadfly, HDF5, RDatasets, Plots, PyCall, and QuantEcon
- Data Access libraries: beautifulsoup4, dill, libxml2, lxml, protobuf, sqlalchemy, textblob, unixodbc, xlrd, and xmlschema
- Data Science libraries: pandas and dask
- Data Visualization tools: bokeh, graphviz, ipywidgets, ipympl, k3d, mpld3, plotly, seaborn, widgetsnbextension, and wordcloud
- Image Processing: imagemagick, opencv, scikit-image, and spectral
- Machine Learning libraries: scikit-learn
- Stats & Data Modelling libraries: h5py, hdf5, numexpr, numpy, pytables, quantecon, scipy, statsmodels, and sympy
- Other libraries include: cloudpickle, cython, ffmpeg, netcdf4, nltk, numba, patsy, rise, vega, and vincent
- A selection of R-Libraries: r-base, r-caret, r-crayon, r-devtools, r-forecast, r-hexbin, r-htmltools, r-htmlwidgets, r-irkernel, r-nycflights13, r-openxlsx, r-plyr, r-quanteda, r-randomforest, r-rcurl, r-readxl, r-reshape2, r-rmarkdown, r-rodbc, r-rsqlite, r-shiny, r-tidyverse, r-topicmodels, r-ukbabynames, r-xml, r-xml2, r-xmlschema, and rpy2
Haskell Notebook
The Haskell Notebook comes with a selection of haskell libraries.
- Based on the crosscompass/ihaskell-notebook Jupyter Community image.
- Includes nbgrader and +GitRepo tools for document sharing.
- Provide rubberband, exercise, and exercise-2 extensions. Note these are not related to nbgrader in any way.
- Enables delete directories with content.
- The following haskell libraries are included: GLUT, JuicyPixels, OpenGL, OpenGLRaw, QuickCheck, gloss, gloss-rendering, vector, and split
Geospatial Notebook
The geospatial Notebook is a python 3 notebook, with a wide selection of libraries that includes geospatial libraries.
- Based on the jupyter/minimal-notebook image.
- Includes nbgrader and +GitRepo tools for document sharing.
- Provide rubberband, exercise, and exercise-2 extensions. Note these are not related to nbgrader in any way.
- Enables delete directories with content.
- The following geocentric libraries are included: apsg, basemap, basemap-data-hires, cartopy, contextily, datashader, descartes, earthpy, folium, gdal, geofeather, geopandas, georasters, googlemaps, ipyleaflet, keplergl, landlab, lsdtopotools, momepy, mplleaflet, obspy, osmnx, pygeos, pysal, rasterio, rasterstats, reportlab, sentinelsat, smmap2, smopy, sompy, splot, urbanaccess, windrose, and xarray
- arcgis from ESRI
- Data Access libraries: beautifulsoup4, dill, libspatialite, libxml2, lxml, mysql-connector-python, protobuf, sqlalchemy, textblob, unixodbc, xlrd, and xlsxwriter
- Data Science libraries: dask, pandas, and pointpats
- Data Visualization tools: bokeh, graphviz, hvplot, ipywidgets, ipympl, k3d, matplotlib, mpld3, multicoretsne, palettable, plotly, pykrige, pymc3, seaborn, widgetsnbextension, and wordcloud
- Image Processing: imagemagick, opencv, scikit-image, and spectral
- Machine Learning libraries: dask-ml and scikit-learn
- Stats & Data Modelling libraries: h5py, hdf5, numexpr, numpy, pytables, scipy, statsmodels, and sympy
- Other libraries include: cloudpickle, cmake, cython, ffmpeg, gitdb2, gitpython, ipyparallel, mkl-service, netcdf4, nltk, numba, patsy, polyline, qgrid, rise, tzlocal, vega, and vincent