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"caret" is a front to back package for machine learning. "rmarkdown" is a bundle of packages for creating documents and notebooks (.doc. "shiny" is a tool for creating interactive web applications that can be accessed by end users. "lubridate" is for working with dates and datetimes aka POSIXcts. "stringr" is for working with strings and regular expressions. "purrr" is for working with lists and for mapping functions to the elements of vectors or lists. "tidyr" is for getting your data into a "tidy" format where: a) every row is an observation, b) every column is a variable, c) every cell has an observation or NA "ggplot2" is for your visualization needs. "dplyr" is for your data wrangling and data manipulation needs. While this is not an absolutely comprehensive list and there is some general preference towards more general packages In this video I discuss 10 R packages that I would recommend learning for your average data scientist's need in 2020. Shannon’s day-to-day in R include: fine-tuning ggplots to convey analysis results, contributing to an internal package to automate routine analyses/tasks, streamlining work-flows for repetitive analyses, and developing shiny apps. Shannon is currently a Statistician at Adelphi Research in Doylestown, PA working in pharmaceutical market research. Shannon’s previous work experiences include supporting research on parasitic diseases at the CDC, developing a pilot college-wide intro stats course at the Institute for Quantitative Theory and Methods at Emory University, and instructing R/SAS programming, intro stats, and survival analysis courses at California Polytechnic State University, San Luis Obispo.
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Shannon Pileggi is an enthusiastic statistical collaborator and professional educator with over ten years of experience partnering on data analysis with diverse stakeholders in corporate settings, tech, public health, and clinical research. The accompanying blog post is available at ? Familiarity with pipe or tidyverse is helpful.
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Attendees should be familiar with functions, but will not be writing their own function in this workshop. This workshop is suitable for beginner to intermediate R users. At the end of the hour you should have a working, well-documented package with a single function, as well as a better understanding of the files and file structure required for R packages. The workshop will cover handy one time functions (i.e., use_this::create_package) as well as functions used continuously throughout package development (i.e., devtools::document).
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This workshop is for people looking to learn how to make their own R packages and learn how to use “usethis” and “devtools” for package development. I am not the creator of the mentioned logos, packages, or materials.ĮTH: 0x3CfC599C4c1040963B644780a0E62d45999bE9D8 #LearnR #RPackages #BreakingIntoDataScienceĪll logos used are the property of RStudio. Read hundreds of articles on programming: ?Īnd subscribe for new videos on technology every day: ?
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Learn to code for free and get a developer job: ? ? Watch more free data science courses at ? ? Course created by Barton Poulson from. This is a hands-on overview of the statistical programming language R, one of the most important tools in data science. Learn the R programming language in this tutorial course.