Resources

The links that used to close every workshop, gathered here once. All of the software is free.

IQSS

Training materials: https://iqss.github.io/dss-training/
Data Science Services: https://www.iq.harvard.edu/data-science-services
Research Computing Environment: https://iqss.github.io/dss-rce/

R

Software

R and R packages: http://cran.r-project.org
Positron: https://positron.posit.co/download
RStudio: https://posit.co/download/rstudio-desktop/
ESS (Emacs R package): http://ess.r-project.org/

Cheatsheets

Posit cheatsheets, ggplot2 and the tidyverse among them: https://posit.co/resources/cheatsheets/

Tutorials and books

swirl, R lessons inside R: https://swirlstats.com/
R for Data Science: https://r4ds.had.co.nz/
Advanced R: http://adv-r.had.co.nz/
R Markdown lessons: https://rmarkdown.rstudio.com/lesson-1.html
Pluralsight: https://www.pluralsight.com/search?q=R
DataCamp: https://www.datacamp.com/
R for Programmers (Norman Matloff, UC Davis): https://web.cs.ucdavis.edu/~matloff/
Calling C and Fortran from R (Charles Geyer, University of Minnesota): http://www.stat.umn.edu/~charlie/rc/
State of the Art in Parallel Computing with R (Schmidberger et al.): https://www.jstatsoft.org/v31/i01

Documentation and help

R manuals: http://cran.r-project.org/manuals.html
Documentation and tutorials: http://cran.r-project.org/other-docs.html
Recommended packages by topic (CRAN task views): http://cran.r-project.org/web/views/
R-help mailing list: https://stat.ethz.ch/mailman/listinfo/r-help
StackOverflow: http://stackoverflow.com/questions/tagged/r
R-Bloggers: https://www.r-bloggers.com/

Coming from another language

Stata: http://www.princeton.edu/~otorres/RStata.pdf
SAS or SPSS: http://r4stats.com/books/free-version/
Matlab: http://www.math.umaine.edu/~hiebeler/comp/matlabR.pdf
Python: http://mathesaurus.sourceforge.net/matlab-python-xref.pdf

ggplot2

Reference: https://ggplot2.tidyverse.org/reference/
Examples: http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
Tutorial: https://uc-r.github.io/ggplot_intro
Mailing list: http://groups.google.com/group/ggplot2
Wiki: https://github.com/hadley/ggplot2/wiki
Website: http://had.co.nz/ggplot2/
StackOverflow: http://stackoverflow.com/questions/tagged/ggplot

Python

Graphics

Quantitative data analysis

numpy: http://www.numpy.org/
scipy: https://www.scipy.org/
pandas: https://pandas.pydata.org/
scikit-learn: http://scikit-learn.org/stable/
statsmodels: http://www.statsmodels.org/stable/

Text analysis

textblob: https://textblob.readthedocs.io/en/dev/
nltk: http://www.nltk.org/
Gensim: https://radimrehurek.com/gensim/

Web scraping

scrapy: https://scrapy.org/
requests: http://docs.python-requests.org/en/master/
lxml: https://lxml.de/
BeautifulSoup: https://www.crummy.com/software/BeautifulSoup/

Stata

UCLA statistical consulting, Stata pages: https://stats.oarc.ucla.edu/stata/
Stata documentation: http://www.stata.com/help.cgi?contents
Statalist: http://www.stata.com/statalist/