docker-datascience

Quickstart:

make
make start

Description

A Jupyter Lab based container for data science projects.

Usage

docker run --rm -it -p 8888:8888 nicbet/jupyter-datascience starts the jupyter lab server on port 8888. Then connect to http://localhost:8888 with the token printed to the console.

Included Packages:

• python>=3.6.6
• rpy2>=2.9.4
• r-base=3.4.1
• r-irkernel>=0.8.12
• r-plyr>=1.8.4
• r-devtools>=1.13.6
• r-tidyverse>=1.1.1
• r-irkernel>=0.8.12
• r-plyr>=1.8.4
• r-devtools>=1.13.6
• r-shiny>=1.0.5
• r-rmarkdown>=1.9
• r-forecast>=8.2
• r-rsqlite>=2.0
• r-reshape2>=1.4.3
• r-nycflights13>=1.0.0
• r-caret>=6.0_80
• r-rcurl>=1.95_4.11
• r-crayon>=1.3.4
• r-randomforest>=4.6_12
• r-htmltools>=0.3.6
• r-sparklyr>=0.8.3
• r-htmlwidgets>=1.0
• r-hexbin>=1.27.2
• tensorflow>=1.9.0
• keras>=2.2.2
• pytorch=0.4.*
• chainer=4.3.*
• theano=1..
• opencv
• caffe
• jupyterthemes>=0.19.6
• plotly>=3.1.1
• imbalanced-learn>=0.3.3
• psycopg2>=2.7.5
• tabulate>=0.8.2
• ipywidgets>=7.4.0
• pandas=0.23*
• numexpr=2.6*
• matplotlib=2.2*
• scipy=1.1*
• seaborn=0.9*
• scikit-learn=0.19*
• scikit-image=0.14*
• sympy=1.1*
• cython=0.28*
• patsy=0.5*
• statsmodels=0.9*
• cloudpickle=0.5*
• dill=0.2*
• numba=0.38*
• bokeh=0.12*
• sqlalchemy=1.2*
• hdf5=1.10*
• h5py=2.7*
• vincent=0.4.*
• beautifulsoup4=4.6.*
• protobuf=3.*
• xlrd
• jupyter_nbextensions_configurator=0.4*
• jupyter_contrib_nbextensions=0.5*
• Elixir 1.7
• Julia 1.0