R Resources

• janitor

  • tabyl() - https://cran.r-project.org/web/packages/janitor/vignettes/tabyls.html
  • clean_names()

• dplyr - distinct()

• ggpattern

  • developing patterns https://cran.r-project.org/web/packages/ggpattern/vignettes/developing-patterns.html
  • https://cran.r-project.org/web/packages/ggpattern/vignettes/patterns-points.html
  • https://cran.r-project.org/web/packages/ggpattern/vignettes/patterns-stripes.html

https://cran.r-project.org/web/packages/ggpattern/vignettes/developing-patterns.html

• R Markdown: The Definitive Guide:

  • https://bookdown.org/yihui/rmarkdown/pdf-document.html

• tidyselect (https://tidyselect.r-lib.org/reference/language.html):

  • starts_with() ends_with() contains() matches() num_range() Select variables that match a pattern
  • all_of() any_of() Select variables from character vectors
  • everything() last_col() Select all variables or the last variable
  • where() Select variables with a function
  • distinct()

• dplyr notes

  • filter (rows/observations)
    • filter(between(varName,low,high))
    • filter(near(varName,mid, tol=0.5))
  • select (columns/variables, can be used to order columns)
    • starts_with(): starts with a prefix
    • ends_with(): ends with a prefix
    • contains(): contains a literal string
    • matches(): matches a regular expression
    • num_range(): a numerical range like x01, x02, x03.
    • one_of(): variables in character vector.
    • everything(): all variable
  • mutate (add or alter columns/variable)
  • arrange (to sort by row values of one or more columns) - desc()
  • group_by
    • summarize
      • n (count)
      • sum
      • mean
      • row_number (to get ranks within each group?)
  • ungroup (or data.frame() to remove groupings)
  • rename
  • count
  • slice
  • sample_n(), sample_frac()
  • row_number()
  • across [apply a function (or functions) across multiple specified columns]
  • pull
    • e.g: dataFrame %>% filter(variable1 == myValue) %>% pull(variable2)
  • full_join, inter_join, left_join, right_join, semi_join, anti_join

R and Shiny Resources

• https://education.rstudio.com/learn/beginner/

• https://life-sciences-healthcare.youcanbook.me/

• https://swirlstats.com/

• https://www.epirhandbook.com/en/

• Interactive plots in Shiny

• R Shiny Tutorials

• showtext: Using Fonts More Easily in R Graphs

Study/Learn:

Cairo -- https://www.rdocumentation.org/packages/Cairo/versions/1.5-9/topics/Cairo cowplot https://cran.r-project.org/web/packages/cowplot/vignettes/introduction.html

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someone check these out: evaluate, digest, formatR, highR, yami, ropp, htmltools, catools, bitops, jasonlite, base64enc, rproject

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• using/reinstalling and old version of a package
  • shinyURL <- "https://cran.r-project.org/src/contrib/Archive/shiny/shiny_1.3.0.tar.gz"
  • install.packages(shinyURL, repos=NULL,type="source")

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• library(summarytools)
  • freq() : frequency tables
  • ctable() : cross-tabulations
  • descr() : descriptive statistics
  • dfSummary() : data frame summaries

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• tidyr
  • missing value function
    • drop_na()
    • fill()
    • replace_na()

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https://holtzy.github.io/Pimp-my-rmd/

R Graphics Cookbook, 2nd edition Winston Chang

R for Data Science, Garrett Grolemund Hadley Wickham

ggplot2 online version of work-in-progress 3rd edition of “ggplot2: elegant graphics for data analysis"

• https://ggplot2-book.org/

• Zev Ross Blog

• Adding text to plot, e.g.:

  • dat <- data.frame(x = rnorm(5000, mean = 1, sd = 100), y = rnorm(5000, mean = 1, sd = 100))
  • LabelData <- tibble(var1=c(-200,-600),var2=c(200,400), var3=c("HERE","THERE"))
  • ggplot(dat , aes(x, y)) + geom_point(color="grey") + geom_text(data=LabelData,aes(var1,var2,label=var3))

R

• looking at a data object

  • summary()
  • headtail(df) head() tail()
  • glimpse(df)
    • like a transposed version of print: columns run down the page, and data runs across. This makes it possible to see every column in a data frame.
  • class() - what kind of object is it

• tmap

  • https://channel9.msdn.com/Events/useR-international-R-User-conferences/useR-International-R-User-2017-Conference/Exploring-and-presenting-maps-with-tmap
  • color/palette issues: https://github.com/mtennekes/tmap/issues/181

• fs package

  • easy path names with path()
  • getting name part and extension part from file names
    • junk <- dir_info(all=TRUE,recursive = TRUE)
    • path_ext(junk$path) path_file(junk$path)

• haven - to read and write SAS

• function to replace all NA values in a dataframe with, say 0

replace_missings <- function(x, replacement) { is_miss <- is.na(x) x[is_miss] <- replacement message(sum(is_miss), " missings replaced by the value ", replacement) x }

dF <- replace_missings(dF, replacement = 0)

• rvest for "web scraping"

• magick for image processing

• writelxl

• map function in purrr -- learn this!

• lubridate - for working with dates

• stringr package - working with strings

  • str_sub(vec,start,end)
  • str_split
  • str_detect - can use with regular expressions
  • str_extract

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https://www.blueskystatistics.com/Default.asp

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