[VIDEO] A Huge Debate: R vs. Python for Data Science

Interesting video: [Video] A Huge Debate: R vs. Python for Data Science (presentation by Eduardo Ariño de la Rubia)

Packages discussed:

• Collecting Data
  • Feather (binary file format for storing data frames fast; interoperable with R and other languages, https://pypi.python.org/pypi/feather-format)
  • IBIS (Python bridge to data sources including SQL databases and Spark; http://docs.ibis-project.org/)
  • ParaText (reading text files very fast, https://github.com/wiseio/paratext)
  • BCOLZ (column storage, https://github.com/Blosc/bcolz)
• Data Visualization
  • Altair (static plots, https://github.com/altair-viz/altair, gallery: https://altair-viz.github.io/gallery/index.html)
  • Bokeh (dynamic plots, http://bokeh.pydata.org/en/latest/, gallery: http://bokeh.pydata.org/en/latest/docs/gallery.html)
  • GEOPlotLib (maps, https://github.com/andrea-cuttone/geoplotlib)
• Clean & Transform
  • Blaze (efficiently dealing with large data, http://blaze.readthedocs.io/en/latest/index.html)
  • Xarray (n-dimensional data, http://xarray.pydata.org/en/stable/)
  • Dask (parallel computing, http://dask.pydata.org/en/latest/)
• Modeling
  • Keras (deep learning, https://github.com/fchollet/keras)
  • PYMC3 (Bayesian statistical modeling, https://pymc-devs.github.io/pymc3/)

• Collecting Data
  • Feather (see also under Python; https://cran.r-project.org/web/packages/feather/index.html)
  • Haven (interoperability with Stata, SPSS, SAS, https://cran.r-project.org/web/packages/haven/index.html)
  • Readr (read csv and other text files fast, https://cran.r-project.org/web/packages/readr/index.html)
  • JSONlite (read/write JSON files, https://cran.r-project.org/web/packages/jsonlite/index.html)
• Visualization
  • GGPLOT2 (everyone knows this already; http://ggplot2.org/, gallery: http://www.r-graph-gallery.com/all-graphs/)
  • HTMLWidgets (dynamic plots; http://www.htmlwidgets.org/)
  • Leaflet (maps; https://rstudio.github.io/leaflet/)
  • tilegamsR (tilegrams in R, http://blog.revolutionanalytics.com/2016/10/tilegrams-in-r.html)
• Clean & Transform
  • dplyr (https://cran.rstudio.com/web/packages/dplyr/vignettes/introduction.html)
  • broom (makes results of fitting commands easier to access, ftp://cran.r-project.org/pub/R/web/packages/broom/vignettes/broom.html) 
  • Tidy_Text (text mining, http://tidytextmining.com/)
• Modeling
  • MXNET (deep learning; https://github.com/dmlc/mxnet)
  • TensorFlow (https://rstudio.github.io/tensorflow/)