Introduction to R for Geospatial Data

Key Points

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.
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 `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()` or `pdf()` combined with `dev.off()`. Use `write.csv` to save tabular data.

Reference

Introduction to R and RStudio

Use the escape key to cancel incomplete commands or running code (Ctrl+C) if you’re using R from the shell.
Basic arithmetic operations follow standard order of precedence:
- Brackets: (, )
- Exponents: ^ or **
- Divide: /
- Multiply: *
- Add: +
- Subtract: -
Scientific notation is available, e.g: 2e-3
Anything to the right of a # is a comment, R will ignore this!
Functions are denoted by function_name(). Expressions inside the brackets are evaluated before being passed to the function, and functions can be nested.
Comparison operators: <, <=, >, >=, ==, !=
Use all.equal to compare numbers!
<- is the assignment operator. Anything to the right is evaluate, then stored in a variable named to the left.
ls lists all variables and functions you’ve created
rm can be used to remove them
When assigning values to function arguments, you must use =.

Project management with RStudio

To create a new project, go to File -> New Project
Some best practices:
- Treat data as read-only
- Keep cleaned data separate from raw dirty data
- Treat generated output as disposable
- Keep related data together
- Use a consistent naming scheme

Data Structures

Use read.csv() to import data in memory
class() gives you the data class of your object
R automatic converts data types
The functions: length(), nrow(), head(), tail(), and str() can be useful to explore data.
Factors are a special class to deal with categorical data.
Lists provide a flexible data type.
Data frames are a special case of lists.

Exploring Data Frames

R makes it easy to import datasets storred remotely
Data Frames
?data.frame is a key data structure. It is a list of vectors.
cbind() will add a column (vector) to a data.frame.
rbind() will add a row (list) to a data.frame.

Useful functions for querying data structures:

?str structure, prints out a summary of the whole data structure
?class what is the data structure?
?head print the first n elements (rows for two-dimensional objects)
?tail print the last n elements (rows for two-dimensional objects)
?rownames, ?colnames, ?dimnames retrieve or modify the row names and column names of an object.
?length get the number of elements in an atomic vector
?nrow, ?ncol, ?dim get the dimensions of a n-dimensional object (Won’t work on atomic vectors or lists).
If your data frame contains factors, you need to take extra steps to add rows that contain new level values.
read.csv to read in data in a regular structure
- sep argument to specify the separator
  - ”,” for comma separated
  - “\t” for tab separated
- Other arguments:
  - header=TRUE if there is a header row

Subsetting data

Elements can be accessed by:
- Index
- Name
- Logical vectors
[ single square brackets:
- extract single elements or subset vectors
- e.g.x[1] extracts the first item from vector x.
- extract single elements of a list. The returned value will be another list().
- extract columns from a data.frame
[ with two arguments to:
- extract rows and/or columns of
  - matrices
  - data.frames
  - e.g. x[1,2] will extract the value in row 1, column 2.
  - e.g. x[2,:] will extract the entire second column of values.
[[ double square brackets to extract items from lists.
$ to access columns or list elements by name
negative indices skip elements

Data frame manipulation with dplyr

?select to extract variables by name.
?filter return rows with matching conditions.
?group_by group data by one of more variables.
?summarize summarize multiple values to a single value.
?mutate add new variables to a data.frame.
?count and ?n to tally values in the data frame.
Combine operations using the ?"%>%" pipe operator.

Control flow

figures can be created with the grammar of graphics:
- library(ggplot2)
- ggplot to create the base figure
- aesthetics specify the data axes, shape, color, and data size
- geometry functions specify the type of plot, e.g. point, line, density, box
- geometry functions also add statistical transforms, e.g. geom_smooth
- scale functions change the mapping from data to aesthetics
- facet functions stratify the figure into panels
- aesthetics apply to individual layers, or can be set for the whole plot inside ggplot.
- theme functions change the overall look of the plot
- order of layers matters!
- ggsave to save a figure.

Writing data

write.table to write out objects in regular format

Glossary

argument: A value given to a function or program when it runs. The term is often used interchangeably (and inconsistently) with parameter.
assign: To give a value a name by associating a variable with it.
body: (of a function): the statements that are executed when a function runs.
comment: A remark in a program that is intended to help human readers understand what is going on, but is ignored by the computer. Comments in Python, R, and the Unix shell start with a # character and run to the end of the line; comments in SQL start with --, and other languages have other conventions.
comma-separated values: (CSV) A common textual representation for tables in which the values in each row are separated by commas.
delimiter: A character or characters used to separate individual values, such as the commas between columns in a CSV file.
documentation: Human-language text written to explain what software does, how it works, or how to use it.
floating-point number: A number containing a fractional part and an exponent. See also: integer.
for loop: A loop that is executed once for each value in some kind of set, list, or range. See also: while loop.
index: A subscript that specifies the location of a single value in a collection, such as a single pixel in an image.
integer: A whole number, such as -12343. See also: floating-point number.
library: In R, the directory(ies) where packages are stored.
package: A collection of R functions, data and compiled code in a well-defined format. Packages are stored in a library and loaded using the library() function.
parameter: A variable named in the function’s declaration that is used to hold a value passed into the call. The term is often used interchangeably (and inconsistently) with argument.
return statement: A statement that causes a function to stop executing and return a value to its caller immediately.
sequence: A collection of information that is presented in a specific order.
shape: An array’s dimensions, represented as a vector. For example, a 5×3 array’s shape is (5,3).
string: Short for “character string”, a sequence of zero or more characters.
syntax error: A programming error that occurs when statements are in an order or contain characters not expected by the programming language.
type: The classification of something in a program (for example, the contents of a variable) as a kind of number (e.g. floating-point, integer), string, or something else. In R the command typeof() is used to query a variables type.
while loop: A loop that keeps executing as long as some condition is true. See also: for loop.