## Introduction to R and RStudio

- Use RStudio to write and run R programs.
- R has the usual arithmetic operators.
- Use
`<-`

to assign values to variables. - Use
`install.packages()`

to install packages (libraries).

## Project Management With RStudio

- Use RStudio to create and manage projects with consistent layout.
- Treat raw data as read-only.
- Treat generated output as disposable.

## Data Structures

- Use
`read.csv`

to read tabular data in R. - The basic data types in R are double, integer, complex, logical, and character.
- Use factors to represent categories in R.

## Exploring Data Frames

- Use
`cbind()`

to add a new column to a data frame. - Use
`rbind()`

to add a new row to a data frame. - Remove rows from a data frame.
- Use
`na.omit()`

to remove rows from a data frame with`NA`

values. - Use
`levels()`

and`as.character()`

to explore and manipulate factors. - Use
`str()`

,`nrow()`

,`ncol()`

,`dim()`

,`colnames()`

,`rownames()`

,`head()`

, and`typeof()`

to understand the structure of a data frame. - Read in a csv file using
`read.csv()`

. - Understand what
`length()`

of a data frame represents.

## Subsetting Data

- Indexing in R starts at 1, not 0.
- Access individual values by location using
`[]`

. - Access slices of data using
`[low:high]`

. - Access arbitrary sets of data using
`[c(...)]`

. - Use logical operations and logical vectors to access subsets of data.

## Data frame Manipulation with dplyr

- 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
`count()`

and`n()`

to obtain the number of observations in columns. - Use
`mutate()`

to create new variables.

## Introduction to Visualization

- Use
`ggplot2`

to create plots. - Think about graphics in layers: aesthetics, geometry, etc.

## Writing Data

- Save plots using
`ggsave()`

. - Use
`write.csv`

to save tabular data.