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I created a series for people coming from SPSS to R .
Turning kindle notes into a tidy data Turning kindle highlights into tidy data frames, why? Because EVERYTHING will be done with R in the future! time 15 minutes Writing manuscripts in Rstudio, easy citations Combine the power of rmarkdown, citr, zotero and pandoc time 8 minutes Generate text using Markov Chains (sort of) Create sentences using random words from a corpus time 8 minutes Plotting a map with ggplot2, color by tile plot a map of a country and color by other data. time 14 minutes Submitting your first package to CRAN, my experience What is it like to submit a package to CRAN? What practices did I follow time 10 minutes Introducing Badgecreatr, a package that places badges in your readme Introducing Badgecreatr, a package to create and place badges in your readme.Rmd file on Github. time 1 min Non-standard-evaluation and standard evaluation in dplyr using dplyr inside functions with lazyeval time 1 min Your most valuable collaborator, future-you future-you loves readme, tests and version control, saving time in the long run. time 16 minutes From spss to R, part 4 combining dplyr and ggplot2 advanced ggplot features. time 13 minutes Creating a package for your data set Turning your dataset into a package is very useful for reproducable research. This tutorial is for you, even if you’ve never created a package in r. time 6 minutes From spss to R, part 3 Getting started with ggplot2 time 7 minutes Version control with Git introduction to version control, and simple rstudio git time 12 minutes Tidying your data Reshaping your wide data to long with the tidyr package time 5 minutes From spss to R, part 2 Torturing your spss data untill it gives in time 11 minutes From spss to R, part 1 Just enough information about r and reading in .sav files time 8 minutes Portioning projects Make small modules that do one thing and increment time 5 minutes