R for plant science: Glossary

R is a programming language. RStudio is a user-friendly interface for coding in R.

R projects help you organize your work and keep file paths simple.

You can get help in the RStudio interface.

There are many resources available online for R help.

Arithmetic operators can do math on numbers.

The assignment operator assigns values to objects.

Objects have types like numeric, character, or logical.

R has built in functions that do basic functions.

The subset operator lets you select data by position or value.

NAs represent missing values.

R stores data tables in a structure called a data frame.

Columns in a data frame must contain values of the same data type.

Subsetting by position is similar as in vectors.

Data frames can also be subset by names.

Factors store characters as integers with text labels.

strings.factors = FALSE can prevent R from reading strings as factors.

The tidyverse is built for data manipulation.

The read_csv function creates tibbles instead of data frames.

The select function picks particular columns based on names.

The filter function picks rows based on values.

The mutate function creates new columns based on the value of other columns.

The group_by and summarize functions can be used to create summary tables.

The write_csv function exports tibbles into a .csv file.

Creating a ggplot require 3 things: data, aesthetics, and geoms

Ggplots are highly customizable.

Faceting lets you make smaller graphs with cleaner plot areas.

Custom and premade themes can applied to any plot.

Linear regression is a quick and easy way to evaluate the direct relationship between two variables.

IT Model Averaging is one approach to evaluate more complex relationships between variables.

There are often many valid approaches to address a question in R and understanding how to interpret R packages can help determine which approach might be most appropriate.