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Introducing R and RStudio IDE
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R is a powerful, popular open-source scripting language
You can customize the layout of RStudio, and use the project feature to manage the files and packages used in your analysis
RStudio allows you to run R in an easy-to-use interface and makes it easy to find help
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R Basics
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Effectively using R is a journey of months or years. Still you don’t have to be an expert to use R and you can start using and analyzing your data with with about a day’s worth of training
It is important to understand how data are organized by R in a given object type and how the mode of that type (e.g. numeric, character, logical, etc.) will determine how R will operate on that data.
Working with vectors effectively prepares you for understanding how data are organized in R.
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R Basics continued - factors and data frames
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It is easy to import data into R from tabular formats into R. However, you still need to check that R has imported and interpreted your data correctly
There are best practices for organizing your data (keeping it tidy) and R is great for this
Base R has many useful functions for manipulating your data, but all of R’s capabilities are greatly enhanced by software packages developed by the community
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Aggregating and Analyzing Data with dplyr
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Use the dplyr package to manipulate dataframes.
Use select() to choose variables from a dataframe.
Use filter() to choose data based on values.
Use group_by() and summarize() to work with subsets of data.
Use mutate() to create new variables.
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Data Visualization with ggplot2
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ggplot2 maps variables in a tidy data frame to visual aesthetics such as position and color.
Plots are built iteratively from different components: data, geoms, scales, and themes.
You can customize any aspect of a plots to best display your data.
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Producing Reports With knitr
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Mix reporting written in R Markdown with software written in R.
Specify chunk options to control formatting.
Use knitr to convert these documents into PDF and other formats.
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